Size distribution of retrovirally marked lineages matches prediction from population measurements of cell cycle behavior

NASA Technical Reports Server (NTRS)

Cai, Li; Hayes, Nancy L.; Takahashi, Takao; Caviness, Verne S Jr; Nowakowski, Richard S.

2002-01-01

Mechanisms that regulate neuron production in the developing mouse neocortex were examined by using a retroviral lineage marking method to determine the sizes of the lineages remaining in the proliferating population of the ventricular zone during the period of neuron production. The distribution of clade sizes obtained experimentally in four different injection-survival paradigms (E11-E13, E11-E14, E11-E15, and E12-E15) from a total of over 500 labeled lineages was compared with that obtained from three models in which the average behavior of the proliferating population [i.e., the proportion of cells remaining in the proliferative population (P) vs. that exiting the proliferative population (Q)] was quantitatively related to lineage size distribution. In model 1, different proportions of asymmetric, symmetric terminal, and symmetric nonterminal cell divisions coexisted during the entire developmental period. In model 2, the developmental period was divided into two epochs: During the first, asymmetric and symmetric nonterminal cell divisions occurred, but, during the second, asymmetric and symmetric terminal cell divisions occurred. In model 3, the shifts in P and Q are accounted for by changes in the proportions of the two types of symmetric cell divisions without the inclusion of any asymmetric cell divisions. The results obtained from the retroviral experiments were well accounted for by model 1 but not by model 2 or 3. These findings demonstrate that: 1) asymmetric and both types of symmetric cell divisions coexist during the entire period of neurogenesis in the mouse, 2) neuron production is regulated in the proliferative population by the independent decisions of the two daughter cells to reenter S phase, and 3) neurons are produced by both asymmetric and symmetric terminal cell divisions. In addition, the findings mean that cell death and/or tangential movements of cells in the proliferative population occur at only a low rate and that there are no proliferating lineages "reserved" to make particular laminae or cell types. Copyright 2002 Wiley-Liss, Inc.

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

Stimulus-dependent Maximum Entropy Models of Neural Population Codes

PubMed Central

Segev, Ronen; Schneidman, Elad

2013-01-01

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME) model—a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population. PMID:23516339

Modelling cell population growth with applications to cancer therapy in human tumour cell lines.

PubMed

Basse, Britta; Baguley, Bruce C; Marshall, Elaine S; Wake, Graeme C; Wall, David J N

2004-01-01

In this paper we present an overview of the work undertaken to model a population of cells and the effects of cancer therapy. We began with a theoretical one compartment size structured cell population model and investigated its asymptotic steady size distributions (SSDs) (On a cell growth model for plankton, MMB JIMA 21 (2004) 49). However these size distributions are not similar to the DNA (size) distributions obtained experimentally via the flow cytometric analysis of human tumour cell lines (data obtained from the Auckland Cancer Society Research Centre, New Zealand). In our one compartment model, size was a generic term, but in order to obtain realistic steady size distributions we chose size to be DNA content and devised a multi-compartment mathematical model for the cell division cycle where each compartment corresponds to a distinct phase of the cell cycle (J. Math. Biol. 47 (2003) 295). We then incorporated another compartment describing the possible induction of apoptosis (cell death) from mitosis phase (Modelling cell death in human tumour cell lines exposed to anticancer drug paclitaxel, J. Math. Biol. 2004, in press). This enabled us to compare our model to flow cytometric data of a melanoma cell line where the anticancer drug, paclitaxel, had been added. The model gives a dynamic picture of the effects of paclitaxel on the cell cycle. We hope to use the model to describe the effects of other cancer therapies on a number of different cell lines. Copyright 2004 Elsevier Ltd.

A multiphase model for tissue construct growth in a perfusion bioreactor.

PubMed

O'Dea, R D; Waters, S L; Byrne, H M

2010-06-01

The growth of a cell population within a rigid porous scaffold in a perfusion bioreactor is studied, using a three-phase continuum model of the type presented by Lemon et al. (2006, Multiphase modelling of tissue growth using the theory of mixtures. J. Math. Biol., 52, 571-594) to represent the cell population (and attendant extracellular matrix), culture medium and porous scaffold. The bioreactor system is modelled as a 2D channel containing the cell-seeded rigid porous scaffold (tissue construct) which is perfused with culture medium. The study concentrates on (i) the cell-cell and cell-scaffold interactions and (ii) the impact of mechanotransduction mechanisms on construct composition. A numerical and analytical analysis of the model equations is presented and, depending upon the relative importance of cell aggregation and repulsion, markedly different cell movement is revealed. Additionally, mechanotransduction effects due to cell density, pressure and shear stress-mediated tissue growth are shown to generate qualitative differences in the composition of the resulting construct. The results of our simulations indicate that this model formulation (in conjunction with appropriate experimental data) has the potential to provide a means of identifying the dominant regulatory stimuli in a cell population.

Effect of Dedifferentiation on Time to Mutation Acquisition in Stem Cell-Driven Cancers

PubMed Central

Jilkine, Alexandra; Gutenkunst, Ryan N.

2014-01-01

Accumulating evidence suggests that many tumors have a hierarchical organization, with the bulk of the tumor composed of relatively differentiated short-lived progenitor cells that are maintained by a small population of undifferentiated long-lived cancer stem cells. It is unclear, however, whether cancer stem cells originate from normal stem cells or from dedifferentiated progenitor cells. To address this, we mathematically modeled the effect of dedifferentiation on carcinogenesis. We considered a hybrid stochastic-deterministic model of mutation accumulation in both stem cells and progenitors, including dedifferentiation of progenitor cells to a stem cell-like state. We performed exact computer simulations of the emergence of tumor subpopulations with two mutations, and we derived semi-analytical estimates for the waiting time distribution to fixation. Our results suggest that dedifferentiation may play an important role in carcinogenesis, depending on how stem cell homeostasis is maintained. If the stem cell population size is held strictly constant (due to all divisions being asymmetric), we found that dedifferentiation acts like a positive selective force in the stem cell population and thus speeds carcinogenesis. If the stem cell population size is allowed to vary stochastically with density-dependent reproduction rates (allowing both symmetric and asymmetric divisions), we found that dedifferentiation beyond a critical threshold leads to exponential growth of the stem cell population. Thus, dedifferentiation may play a crucial role, the common modeling assumption of constant stem cell population size may not be adequate, and further progress in understanding carcinogenesis demands a more detailed mechanistic understanding of stem cell homeostasis. PMID:24603301

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

NASA Astrophysics Data System (ADS)

Vagos, Márcia R.; Arevalo, Hermenegild; de Oliveira, Bernardo Lino; Sundnes, Joakim; Maleckar, Mary M.

2017-09-01

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions

PubMed Central

Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-01-01

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics. PMID:24769917

Examining a scaled dynamical system of telomere shortening

NASA Astrophysics Data System (ADS)

Cyrenne, Benoit M.; Gooding, Robert J.

2015-02-01

A model of telomere dynamics is proposed and examined. Our model, which extends a previously introduced model that incorporates stem cells as progenitors of new cells, imposes the Hayflick limit, the maximum number of cell divisions that are possible. This new model leads to cell populations for which the average telomere length is not necessarily a monotonically decreasing function of time, in contrast to previously published models. We provide a phase diagram indicating where such results would be expected via the introduction of scaled populations, rate constants and time. The application of this model to available leukocyte baboon data is discussed.

Cancer heterogeneity and multilayer spatial evolutionary games.

PubMed

Świerniak, Andrzej; Krześlak, Michał

2016-10-13

Evolutionary game theory (EGT) has been widely used to simulate tumour processes. In almost all studies on EGT models analysis is limited to two or three phenotypes. Our model contains four main phenotypes. Moreover, in a standard approach only heterogeneity of populations is studied, while cancer cells remain homogeneous. A multilayer approach proposed in this paper enables to study heterogeneity of single cells. In the extended model presented in this paper we consider four strategies (phenotypes) that can arise by mutations. We propose multilayer spatial evolutionary games (MSEG) played on multiple 2D lattices corresponding to the possible phenotypes. It enables simulation and investigation of heterogeneity on the player-level in addition to the population-level. Moreover, it allows to model interactions between arbitrary many phenotypes resulting from the mixture of basic traits. Different equilibrium points and scenarios (monomorphic and polymorphic populations) have been achieved depending on model parameters and the type of played game. However, there is a possibility of stable quadromorphic population in MSEG games for the same set of parameters like for the mean-field game. The model assumes an existence of four possible phenotypes (strategies) in the population of cells that make up tumour. Various parameters and relations between cells lead to complex analysis of this model and give diverse results. One of them is a possibility of stable coexistence of different tumour cells within the population, representing almost arbitrary mixture of the basic phenotypes. This article was reviewed by Tomasz Lipniacki, Urszula Ledzewicz and Jacek Banasiak.

Effects of the distant population density on spatial patterns of demographic dynamics

NASA Astrophysics Data System (ADS)

Tamura, Kohei; Masuda, Naoki

2017-08-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.

Effects of the distant population density on spatial patterns of demographic dynamics.

PubMed

Tamura, Kohei; Masuda, Naoki

2017-08-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500  m ) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.

Effects of the distant population density on spatial patterns of demographic dynamics

PubMed Central

2017-01-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km. PMID:28878987

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

Modelling Spatially Regulated β-Catenin Dynamics and Invasion in Intestinal Crypts

PubMed Central

Murray, Philip J.; Kang, Jun-Won; Mirams, Gary R.; Shin, Sung-Young; Byrne, Helen M.; Maini, Philip K.; Cho, Kwang-Hyun

2010-01-01

Experimental data (e.g., genetic lineage and cell population studies) on intestinal crypts reveal that regulatory features of crypt behavior, such as control via morphogen gradients, are remarkably well conserved among numerous organisms (e.g., from mouse and rat to human) and throughout the different regions of the small and large intestines. In this article, we construct a partial differential equation model of a single colonic crypt that describes the spatial distribution of Wnt pathway proteins along the crypt axis. The novelty of our continuum model is that it is based upon assumptions that can be directly related to processes at the cellular and subcellular scales. We use the model to predict how the distributions of Wnt pathway proteins are affected by mutations. The model is then extended to investigate how mutant cell populations can invade neighboring crypts. The model simulations suggest that cell crowding caused by increased proliferation and decreased cell loss may be sufficient for a mutant cell population to colonize a neighboring healthy crypt. PMID:20682248

A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast

PubMed Central

Almquist, Joachim; Bendrioua, Loubna; Adiels, Caroline Beck; Goksör, Mattias; Hohmann, Stefan; Jirstrand, Mats

2015-01-01

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability. PMID:25893847

Cell lineage tracing in the developing enteric nervous system: superstars revealed by experiment and simulation

PubMed Central

Cheeseman, Bevan L.; Zhang, Dongcheng; Binder, Benjamin J.; Newgreen, Donald F.; Landman, Kerry A.

2014-01-01

Cell lineage tracing is a powerful tool for understanding how proliferation and differentiation of individual cells contribute to population behaviour. In the developing enteric nervous system (ENS), enteric neural crest (ENC) cells move and undergo massive population expansion by cell division within self-growing mesenchymal tissue. We show that single ENC cells labelled to follow clonality in the intestine reveal extraordinary and unpredictable variation in number and position of descendant cells, even though ENS development is highly predictable at the population level. We use an agent-based model to simulate ENC colonization and obtain agent lineage tracing data, which we analyse using econometric data analysis tools. In all realizations, a small proportion of identical initial agents accounts for a substantial proportion of the total final agent population. We term these individuals superstars. Their existence is consistent across individual realizations and is robust to changes in model parameters. This inequality of outcome is amplified at elevated proliferation rate. The experiments and model suggest that stochastic competition for resources is an important concept when understanding biological processes which feature high levels of cell proliferation. The results have implications for cell-fate processes in the ENS. PMID:24501272

The effect of EIF dynamics on the cryopreservation process of a size distributed cell population.

PubMed

Fadda, S; Briesen, H; Cincotti, A

2011-06-01

Typical mathematical modeling of cryopreservation of cell suspensions assumes a thermodynamic equilibrium between the ice and liquid water in the extracellular solution. This work investigates the validity of this assumption by introducing a population balance approach for dynamic extracellular ice formation (EIF) in the absence of any cryo-protectant agent (CPA). The population balance model reflects nucleation and diffusion-limited growth in the suspending solution whose driving forces are evaluated in the relevant phase diagram. This population balance description of the extracellular compartment has been coupled to a model recently proposed in the literature [Fadda et al., AIChE Journal, 56, 2173-2185, (2010)], which is capable of quantitatively describing and predicting internal ice formation (IIF) inside the cells. The cells are characterized by a size distribution (i.e. through another population balance), thus overcoming the classic view of a population of identically sized cells. From the comparison of the system behavior in terms of the dynamics of the cell size distribution it can be concluded that the assumption of a thermodynamic equilibrium in the extracellular compartment is not always justified. Depending on the cooling rate, the dynamics of EIF needs to be considered. Copyright © 2011 Elsevier Inc. All rights reserved.

Skin Stem Cell Hypotheses and Long Term Clone Survival – Explored Using Agent-based Modelling

PubMed Central

Li, X.; Upadhyay, A. K.; Bullock, A. J.; Dicolandrea, T.; Xu, J.; Binder, R. L.; Robinson, M. K.; Finlay, D. R.; Mills, K. J.; Bascom, C. C.; Kelling, C. K.; Isfort, R. J.; Haycock, J. W.; MacNeil, S.; Smallwood, R. H.

2013-01-01

Epithelial renewal in skin is achieved by the constant turnover and differentiation of keratinocytes. Three popular hypotheses have been proposed to explain basal keratinocyte regeneration and epidermal homeostasis: 1) asymmetric division (stem-transit amplifying cell); 2) populational asymmetry (progenitor cell with stochastic fate); and 3) populational asymmetry with stem cells. In this study, we investigated lineage dynamics using these hypotheses with a 3D agent-based model of the epidermis. The model simulated the growth and maintenance of the epidermis over three years. The offspring of each proliferative cell was traced. While all lineages were preserved in asymmetric division, the vast majority were lost when assuming populational asymmetry. The third hypothesis provided the most reliable mechanism for self-renewal by preserving genetic heterogeneity in quiescent stem cells, and also inherent mechanisms for skin ageing and the accumulation of genetic mutation. PMID:23712735

Skin stem cell hypotheses and long term clone survival--explored using agent-based modelling.

PubMed

Li, X; Upadhyay, A K; Bullock, A J; Dicolandrea, T; Xu, J; Binder, R L; Robinson, M K; Finlay, D R; Mills, K J; Bascom, C C; Kelling, C K; Isfort, R J; Haycock, J W; MacNeil, S; Smallwood, R H

2013-01-01

Epithelial renewal in skin is achieved by the constant turnover and differentiation of keratinocytes. Three popular hypotheses have been proposed to explain basal keratinocyte regeneration and epidermal homeostasis: 1) asymmetric division (stem-transit amplifying cell); 2) populational asymmetry (progenitor cell with stochastic fate); and 3) populational asymmetry with stem cells. In this study, we investigated lineage dynamics using these hypotheses with a 3D agent-based model of the epidermis. The model simulated the growth and maintenance of the epidermis over three years. The offspring of each proliferative cell was traced. While all lineages were preserved in asymmetric division, the vast majority were lost when assuming populational asymmetry. The third hypothesis provided the most reliable mechanism for self-renewal by preserving genetic heterogeneity in quiescent stem cells, and also inherent mechanisms for skin ageing and the accumulation of genetic mutation.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

PubMed

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J

2014-07-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

The Population Biology of Bacterial Plasmids: A PRIORI Conditions for the Existence of Conjugationally Transmitted Factors

PubMed Central

Stewart, Frank M.; Levin, Bruce R.

1977-01-01

A mathematical model for the population dynamics of conjugationally transmitted plasmids in bacterial populations is presented and its properties analyzed. Consideration is given to nonbacteriocinogenic factors that are incapable of incorporation into the chromosome of their host cells, and to bacterial populations maintained in either continuous (chemostat) or discrete (serial transfer) culture. The conditions for the establishment and maintenance of these infectious extrachromosomal elements and equilibrium frequencies of cells carrying them are presented for different values of the biological parameters: population growth functions, conjugational transfer and segregation rate constants. With these parameters in a biologically realistic range, the theory predicts a broad set of physical conditions, resource concentrations and dilution rates, where conjugationally transmitted plasmids can become established and where cells carrying them will maintain high frequencies in bacterial populations. This can occur even when plasmid-bearing cells are much less fit (i.e., have substantially lower growth rates) than cells free of these factors. The implications of these results and the reality and limitations of the model are discussed and the values of its parameters in natural populations speculated upon. PMID:17248761

Deconstructing stem cell population heterogeneity: Single-cell analysis and modeling approaches

PubMed Central

Wu, Jincheng; Tzanakakis, Emmanuel S.

2014-01-01

Isogenic stem cell populations display cell-to-cell variations in a multitude of attributes including gene or protein expression, epigenetic state, morphology, proliferation and proclivity for differentiation. The origins of the observed heterogeneity and its roles in the maintenance of pluripotency and the lineage specification of stem cells remain unclear. Addressing pertinent questions will require the employment of single-cell analysis methods as traditional cell biochemical and biomolecular assays yield mostly population-average data. In addition to time-lapse microscopy and flow cytometry, recent advances in single-cell genomic, transcriptomic and proteomic profiling are reviewed. The application of multiple displacement amplification, next generation sequencing, mass cytometry and spectrometry to stem cell systems is expected to provide a wealth of information affording unprecedented levels of multiparametric characterization of cell ensembles under defined conditions promoting pluripotency or commitment. Establishing connections between single-cell analysis information and the observed phenotypes will also require suitable mathematical models. Stem cell self-renewal and differentiation are orchestrated by the coordinated regulation of subcellular, intercellular and niche-wide processes spanning multiple time scales. Here, we discuss different modeling approaches and challenges arising from their application to stem cell populations. Integrating single-cell analysis with computational methods will fill gaps in our knowledge about the functions of heterogeneity in stem cell physiology. This combination will also aid the rational design of efficient differentiation and reprogramming strategies as well as bioprocesses for the production of clinically valuable stem cell derivatives. PMID:24035899

Immune Response to a Variable Pathogen: A Stochastic Model with Two Interlocked Darwinian Entities

PubMed Central

Kuhn, Christoph

2012-01-01

This paper presents the modeling of a host immune system, more precisely the immune effector cell and immune memory cell population, and its interaction with an invading pathogen population. It will tackle two issues of interest; on the one hand, in defining a stochastic model accounting for the inherent nature of organisms in population dynamics, namely multiplication with mutation and selection; on the other hand, in providing a description of pathogens that may vary their antigens through mutations during infection of the host. Unlike most of the literature, which models the dynamics with first-order differential equations, this paper proposes a Galton-Watson type branching process to describe stochastically by whole distributions the population dynamics of pathogens and immune cells. In the first model case, the pathogen of a given type is either eradicated or shows oscillatory chronic response. In the second model case, the pathogen shows variational behavior changing its antigen resulting in a prolonged immune reaction. PMID:23424603

Immune response to a variable pathogen: a stochastic model with two interlocked Darwinian entities.

PubMed

Kuhn, Christoph

2012-01-01

This paper presents the modeling of a host immune system, more precisely the immune effector cell and immune memory cell population, and its interaction with an invading pathogen population. It will tackle two issues of interest; on the one hand, in defining a stochastic model accounting for the inherent nature of organisms in population dynamics, namely multiplication with mutation and selection; on the other hand, in providing a description of pathogens that may vary their antigens through mutations during infection of the host. Unlike most of the literature, which models the dynamics with first-order differential equations, this paper proposes a Galton-Watson type branching process to describe stochastically by whole distributions the population dynamics of pathogens and immune cells. In the first model case, the pathogen of a given type is either eradicated or shows oscillatory chronic response. In the second model case, the pathogen shows variational behavior changing its antigen resulting in a prolonged immune reaction.

Modelling spatially regulated beta-catenin dynamics and invasion in intestinal crypts.

PubMed

Murray, Philip J; Kang, Jun-Won; Mirams, Gary R; Shin, Sung-Young; Byrne, Helen M; Maini, Philip K; Cho, Kwang-Hyun

2010-08-04

Experimental data (e.g., genetic lineage and cell population studies) on intestinal crypts reveal that regulatory features of crypt behavior, such as control via morphogen gradients, are remarkably well conserved among numerous organisms (e.g., from mouse and rat to human) and throughout the different regions of the small and large intestines. In this article, we construct a partial differential equation model of a single colonic crypt that describes the spatial distribution of Wnt pathway proteins along the crypt axis. The novelty of our continuum model is that it is based upon assumptions that can be directly related to processes at the cellular and subcellular scales. We use the model to predict how the distributions of Wnt pathway proteins are affected by mutations. The model is then extended to investigate how mutant cell populations can invade neighboring crypts. The model simulations suggest that cell crowding caused by increased proliferation and decreased cell loss may be sufficient for a mutant cell population to colonize a neighboring healthy crypt. 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

The Formation of Tight Tumor Clusters Affects the Efficacy of Cell Cycle Inhibitors: A Hybrid Model Study

PubMed Central

Kim, MunJu; Reed, Damon; Rejniak, Katarzyna A.

2014-01-01

Cyclin-dependent kinases (CDKs) are vital in regulating cell cycle progression, and, thus, in highly proliferating tumor cells CDK inhibitors are gaining interest as potential anticancer agents. Clonogenic assay experiments are frequently used to determine drug efficacy against the survival and proliferation of cancer cells. While the anticancer mechanisms of drugs are usually described at the intracellular single-cell level, the experimental measurements are sampled from the entire cancer cell population. This approach may lead to discrepancies between the experimental observations and theoretical explanations of anticipated drug mechanisms. To determine how individual cell responses to drugs that inhibit CDKs affect the growth of cancer cell populations, we developed a spatially explicit hybrid agent-based model. In this model, each cell is equipped with internal cell cycle regulation mechanisms, but it is also able to interact physically with its neighbors. We model cell cycle progression, focusing on the G1 and G2/M cell cycle checkpoints, as well as on related essential components, such as CDK1, CDK2, cell size, and DNA damage. We present detailed studies of how the emergent properties (e.g., cluster formation) of an entire cell population depend on altered physical and physiological parameters. We analyze the effects of CDK1 and CKD2 inhibitors on population growth, time-dependent changes in cell cycle distributions, and the dynamic evolution of spatial cell patterns. We show that cell cycle inhibitors that cause cell arrest at different cell cycle phases are not necessarily synergistically super-additive. Finally, we demonstrate that the physical aspects of cell population growth, such as the formation of tight cell clusters versus dispersed colonies, alter the efficacy of cell cycle inhibitors, both in 2D and 3D simulations. This finding may have implications for interpreting the treatment efficacy results of in vitro experiments, in which treatment is applied before the cells can grow to produce clusters, especially because in vivo tumors, in contrast, form large masses before they are detected and treated. PMID:24607745

Stable Regulation of Cell Cycle Events in Mycobacteria: Insights From Inherently Heterogeneous Bacterial Populations.

PubMed

Logsdon, Michelle M; Aldridge, Bree B

2018-01-01

Model bacteria, such as E. coli and B. subtilis , tightly regulate cell cycle progression to achieve consistent cell size distributions and replication dynamics. Many of the hallmark features of these model bacteria, including lateral cell wall elongation and symmetric growth and division, do not occur in mycobacteria. Instead, mycobacterial growth is characterized by asymmetric polar growth and division. This innate asymmetry creates unequal birth sizes and growth rates for daughter cells with each division, generating a phenotypically heterogeneous population. Although the asymmetric growth patterns of mycobacteria lead to a larger variation in birth size than typically seen in model bacterial populations, the cell size distribution is stable over time. Here, we review the cellular mechanisms of growth, division, and cell cycle progression in mycobacteria in the face of asymmetry and inherent heterogeneity. These processes coalesce to control cell size. Although Mycobacterium smegmatis and Mycobacterium bovis Bacillus Calmette-Guérin (BCG) utilize a novel model of cell size control, they are similar to previously studied bacteria in that initiation of DNA replication is a key checkpoint for cell division. We compare the regulation of DNA replication initiation and strategies used for cell size homeostasis in mycobacteria and model bacteria. Finally, we review the importance of cellular organization and chromosome segregation relating to the physiology of mycobacteria and consider how new frameworks could be applied across the wide spectrum of bacterial diversity.

Quantifying T Lymphocyte Turnover

PubMed Central

De Boer, Rob J.; Perelson, Alan S.

2013-01-01

Peripheral T cell populations are maintained by production of naive T cells in the thymus, clonal expansion of activated cells, cellular self-renewal (or homeostatic proliferation), and density dependent cell life spans. A variety of experimental techniques have been employed to quantify the relative contributions of these processes. In modern studies lymphocytes are typically labeled with 5-bromo-2′-deoxyuridine (BrdU), deuterium, or the fluorescent dye carboxy-fluorescein diacetate succinimidyl ester (CFSE), their division history has been studied by monitoring telomere shortening and the dilution of T cell receptor excision circles (TRECs) or the dye CFSE, and clonal expansion has been documented by recording changes in the population densities of antigen specific cells. Proper interpretation of such data in terms of the underlying rates of T cell production, division, and death has proven to be notoriously difficult and involves mathematical modeling. We review the various models that have been developed for each of these techniques, discuss which models seem most appropriate for what type of data, reveal open problems that require better models, and pinpoint how the assumptions underlying a mathematical model may influence the interpretation of data. Elaborating various successful cases where modeling has delivered new insights in T cell population dynamics, this review provides quantitative estimates of several processes involved in the maintenance of naive and memory, CD4+ and CD8+ T cell pools in mice and men. PMID:23313150

An animated landscape representation of CD4+ T-cell differentiation, variability, and plasticity: Insights into the behavior of populations versus cells

PubMed Central

Rebhahn, Jonathan A; Deng, Nan; Sharma, Gaurav; Livingstone, Alexandra M; Huang, Sui; Mosmann, Tim R

2014-01-01

Recent advances in understanding CD4+ T-cell differentiation suggest that previous models of a few distinct, stable effector phenotypes were too simplistic. Although several well-characterized phenotypes are still recognized, some states display plasticity, and intermediate phenotypes exist. As a framework for reexamining these concepts, we use Waddington's landscape paradigm, augmented with explicit consideration of stochastic variations. Our animation program “LAVA” visualizes T-cell differentiation as cells moving across a landscape of hills and valleys, leading to attractor basins representing stable or semistable differentiation states. The model illustrates several principles, including: (i) cell populations may behave more predictably than individual cells; (ii) analogous to reticulate evolution, differentiation may proceed through a network of interconnected states, rather than a single well-defined pathway; (iii) relatively minor changes in the barriers between attractor basins can change the stability or plasticity of a population; (iv) intrapopulation variability of gene expression may be an important regulator of differentiation, rather than inconsequential noise; (v) the behavior of some populations may be defined mainly by the behavior of outlier cells. While not a quantitative representation of actual differentiation, our model is intended to provoke discussion of T-cell differentiation pathways, particularly highlighting a probabilistic view of transitions between states. PMID:24945794

Discrete and Continuum Approximations for Collective Cell Migration in a Scratch Assay with Cell Size Dynamics.

PubMed

Matsiaka, Oleksii M; Penington, Catherine J; Baker, Ruth E; Simpson, Matthew J

2018-04-01

Scratch assays are routinely used to study the collective spreading of cell populations. In general, the rate at which a population of cells spreads is driven by the combined effects of cell migration and proliferation. To examine the effects of cell migration separately from the effects of cell proliferation, scratch assays are often performed after treating the cells with a drug that inhibits proliferation. Mitomycin-C is a drug that is commonly used to suppress cell proliferation in this context. However, in addition to suppressing cell proliferation, mitomycin-C also causes cells to change size during the experiment, as each cell in the population approximately doubles in size as a result of treatment. Therefore, to describe a scratch assay that incorporates the effects of cell-to-cell crowding, cell-to-cell adhesion, and dynamic changes in cell size, we present a new stochastic model that incorporates these mechanisms. Our agent-based stochastic model takes the form of a system of Langevin equations that is the system of stochastic differential equations governing the evolution of the population of agents. We incorporate a time-dependent interaction force that is used to mimic the dynamic increase in size of the agents. To provide a mathematical description of the average behaviour of the stochastic model we present continuum limit descriptions using both a standard mean-field approximation and a more sophisticated moment dynamics approximation that accounts for the density of agents and density of pairs of agents in the stochastic model. Comparing the accuracy of the two continuum descriptions for a typical scratch assay geometry shows that the incorporation of agent growth in the system is associated with a decrease in accuracy of the standard mean-field description. In contrast, the moment dynamics description provides a more accurate prediction of the evolution of the scratch assay when the increase in size of individual agents is included in the model.

Single-cell quantification of IL-2 response by effector and regulatory T cells reveals critical plasticity in immune response

PubMed Central

Feinerman, Ofer; Jentsch, Garrit; Tkach, Karen E; Coward, Jesse W; Hathorn, Matthew M; Sneddon, Michael W; Emonet, Thierry; Smith, Kendall A; Altan-Bonnet, Grégoire

2010-01-01

Understanding how the immune system decides between tolerance and activation by antigens requires addressing cytokine regulation as a highly dynamic process. We quantified the dynamics of interleukin-2 (IL-2) signaling in a population of T cells during an immune response by combining in silico modeling and single-cell measurements in vitro. We demonstrate that IL-2 receptor expression levels vary widely among T cells creating a large variability in the ability of the individual cells to consume, produce and participate in IL-2 signaling within the population. Our model reveals that at the population level, these heterogeneous cells are engaged in a tug-of-war for IL-2 between regulatory (Treg) and effector (Teff) T cells, whereby access to IL-2 can either increase the survival of Teff cells or the suppressive capacity of Treg cells. This tug-of-war is the mechanism enforcing, at the systems level, a core function of Treg cells, namely the specific suppression of survival signals for weakly activated Teff cells but not for strongly activated cells. Our integrated model yields quantitative, experimentally validated predictions for the manipulation of Treg suppression. PMID:21119631

Model-Based Phenotypic Signatures Governing the Dynamics of the Stem and Semi-differentiated Cell Populations in Dysplastic Colonic Crypts.

PubMed

Nikolov, Svetoslav; Santos, Guido; Wolkenhauer, Olaf; Vera, Julio

2018-02-01

Mathematical modeling of cell differentiated in colonic crypts can contribute to a better understanding of basic mechanisms underlying colonic tissue organization, but also its deregulation during carcinogenesis and tumor progression. Here, we combined bifurcation analysis to assess the effect that time delay has in the complex interplay of stem cells and semi-differentiated cells at the niche of colonic crypts, and systematic model perturbation and simulation to find model-based phenotypes linked to cancer progression. The models suggest that stem cell and semi-differentiated cell population dynamics in colonic crypts can display chaotic behavior. In addition, we found that clinical profiling of colorectal cancer correlates with the in silico phenotypes proposed by the mathematical model. Further, potential therapeutic targets for chemotherapy resistant phenotypes are proposed, which in any case will require experimental validation.

Making sense of snapshot data: ergodic principle for clonal cell populations

PubMed Central

2017-01-01

Population growth is often ignored when quantifying gene expression levels across clonal cell populations. We develop a framework for obtaining the molecule number distributions in an exponentially growing cell population taking into account its age structure. In the presence of generation time variability, the average acquired across a population snapshot does not obey the average of a dividing cell over time, apparently contradicting ergodicity between single cells and the population. Instead, we show that the variation observed across snapshots with known cell age is captured by cell histories, a single-cell measure obtained from tracking an arbitrary cell of the population back to the ancestor from which it originated. The correspondence between cells of known age in a population with their histories represents an ergodic principle that provides a new interpretation of population snapshot data. We illustrate the principle using analytical solutions of stochastic gene expression models in cell populations with arbitrary generation time distributions. We further elucidate that the principle breaks down for biochemical reactions that are under selection, such as the expression of genes conveying antibiotic resistance, which gives rise to an experimental criterion with which to probe selection on gene expression fluctuations. PMID:29187636

Making sense of snapshot data: ergodic principle for clonal cell populations.

PubMed

Thomas, Philipp

2017-11-01

Population growth is often ignored when quantifying gene expression levels across clonal cell populations. We develop a framework for obtaining the molecule number distributions in an exponentially growing cell population taking into account its age structure. In the presence of generation time variability, the average acquired across a population snapshot does not obey the average of a dividing cell over time, apparently contradicting ergodicity between single cells and the population. Instead, we show that the variation observed across snapshots with known cell age is captured by cell histories, a single-cell measure obtained from tracking an arbitrary cell of the population back to the ancestor from which it originated. The correspondence between cells of known age in a population with their histories represents an ergodic principle that provides a new interpretation of population snapshot data. We illustrate the principle using analytical solutions of stochastic gene expression models in cell populations with arbitrary generation time distributions. We further elucidate that the principle breaks down for biochemical reactions that are under selection, such as the expression of genes conveying antibiotic resistance, which gives rise to an experimental criterion with which to probe selection on gene expression fluctuations. © 2017 The Author(s).

Efficient Analysis of Systems Biology Markup Language Models of Cellular Populations Using Arrays.

PubMed

Watanabe, Leandro; Myers, Chris J

2016-08-19

The Systems Biology Markup Language (SBML) has been widely used for modeling biological systems. Although SBML has been successful in representing a wide variety of biochemical models, the core standard lacks the structure for representing large complex regular systems in a standard way, such as whole-cell and cellular population models. These models require a large number of variables to represent certain aspects of these types of models, such as the chromosome in the whole-cell model and the many identical cell models in a cellular population. While SBML core is not designed to handle these types of models efficiently, the proposed SBML arrays package can represent such regular structures more easily. However, in order to take full advantage of the package, analysis needs to be aware of the arrays structure. When expanding the array constructs within a model, some of the advantages of using arrays are lost. This paper describes a more efficient way to simulate arrayed models. To illustrate the proposed method, this paper uses a population of repressilator and genetic toggle switch circuits as examples. Results show that there are memory benefits using this approach with a modest cost in runtime.

Modeling population dynamics of mitochondria in mammalian cells

NASA Astrophysics Data System (ADS)

Kornick, Kellianne; Das, Moumita

Mitochondria are organelles located inside eukaryotic cells and are essential for several key cellular processes such as energy (ATP) production, cell signaling, differentiation, and apoptosis. All organisms are believed to have low levels of variation in mitochondrial DNA (mtDNA), and alterations in mtDNA are connected to a range of human health conditions, including epilepsy, heart failure, Parkinsons disease, diabetes, and multiple sclerosis. Therefore, understanding how changes in mtDNA accumulate over time and are correlated to changes in mitochondrial function and cell properties can have a profound impact on our understanding of cell physiology and the origins of some diseases. Motivated by this, we develop and study a mathematical model to determine which cellular parameters have the largest impact on mtDNA population dynamics. The model consists of coupled ODEs to describe subpopulations of healthy and dysfunctional mitochondria subject to mitochondrial fission, fusion, autophagy, and mutation. We study the time evolution and stability of each sub-population under specific selection biases and pressures by tuning specific terms in our model. Our results may provide insights into how sub-populations of mitochondria survive and evolve under different selection pressures. This work was supported by a Grant from the Moore Foundation.

ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics

PubMed Central

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J.

2014-01-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity. PMID:24992156

Molecular and Functional Characterization of Lymphoid Progenitor Subsets Reveals a Bipartite Architecture of Human Lymphopoiesis.

PubMed

Alhaj Hussen, Kutaiba; Vu Manh, Thien-Phong; Guimiot, Fabien; Nelson, Elisabeth; Chabaane, Emna; Delord, Marc; Barbier, Maxime; Berthault, Claire; Dulphy, Nicolas; Alberdi, Antonio José; Burlen-Defranoux, Odile; Socié, Gerard; Bories, Jean Christophe; Larghero, Jerôme; Vanneaux, Valérie; Verhoeyen, Els; Wirth, Thierry; Dalod, Marc; Gluckman, Jean Claude; Cumano, Ana; Canque, Bruno

2017-10-17

The classical model of hematopoiesis established in the mouse postulates that lymphoid cells originate from a founder population of common lymphoid progenitors. Here, using a modeling approach in humanized mice, we showed that human lymphoid development stemmed from distinct populations of CD127 - and CD127 + early lymphoid progenitors (ELPs). Combining molecular analyses with in vitro and in vivo functional assays, we demonstrated that CD127 - and CD127 + ELPs emerged independently from lympho-mono-dendritic progenitors, responded differently to Notch1 signals, underwent divergent modes of lineage restriction, and displayed both common and specific differentiation potentials. Whereas CD127 - ELPs comprised precursors of T cells, marginal zone B cells, and natural killer (NK) and innate lymphoid cells (ILCs), CD127 + ELPs supported production of all NK cell, ILC, and B cell populations but lacked T potential. On the basis of these results, we propose a "two-family" model of human lymphoid development that differs from the prevailing model of hematopoiesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Fluorescent CSC models evidence that targeted nanomedicines improve treatment sensitivity of breast and colon cancer stem cells.

PubMed

Gener, Petra; Gouveia, Luis Pleno; Sabat, Guillem Romero; de Sousa Rafael, Diana Fernandes; Fort, Núria Bergadà; Arranja, Alexandra; Fernández, Yolanda; Prieto, Rafael Miñana; Ortega, Joan Sayos; Arango, Diego; Abasolo, Ibane; Videira, Mafalda; Schwartz, Simo

2015-11-01

To be able to study the efficacy of targeted nanomedicines in marginal population of highly aggressive cancer stem cells (CSC), we have developed a novel in vitro fluorescent CSC model that allows us to visualize these cells in heterogeneous population and to monitor CSC biological performance after therapy. In this model tdTomato reporter gene is driven by CSC specific (ALDH1A1) promoter and contrary to other similar models, CSC differentiation and un-differentiation processes are not restrained and longitudinal studies are feasible. We used this model for preclinical validation of poly[(d,l-lactide-co-glycolide)-co-PEG] (PLGA-co-PEG) micelles loaded with paclitaxel. Further, active targeting against CD44 and EGFR receptors was validated in breast and colon cancer cell lines. Accordingly, specific active targeting toward surface receptors enhances the performance of nanomedicines and sensitizes CSC to paclitaxel based chemotherapy. Many current cancer therapies fail because of the failure to target cancer stem cells. This surviving population soon proliferates and differentiates into more cancer cells. In this interesting article, the authors designed an in vitro cancer stem cell model to study the effects of active targeting using antibody-labeled micelles containing chemotherapeutic agent. This new model should allow future testing of various drug/carrier platforms before the clinical phase. Copyright © 2015 Elsevier Inc. All rights reserved.

Population pharmacokinetics of busulfan in pediatric and young adult patients undergoing hematopoietic cell transplant: a model-based dosing algorithm for personalized therapy and implementation into routine clinical use.

PubMed

Long-Boyle, Janel R; Savic, Rada; Yan, Shirley; Bartelink, Imke; Musick, Lisa; French, Deborah; Law, Jason; Horn, Biljana; Cowan, Morton J; Dvorak, Christopher C

2015-04-01

Population pharmacokinetic (PK) studies of busulfan in children have shown that individualized model-based algorithms provide improved targeted busulfan therapy when compared with conventional dose guidelines. The adoption of population PK models into routine clinical practice has been hampered by the tendency of pharmacologists to develop complex models too impractical for clinicians to use. The authors aimed to develop a population PK model for busulfan in children that can reliably achieve therapeutic exposure (concentration at steady state) and implement a simple model-based tool for the initial dosing of busulfan in children undergoing hematopoietic cell transplantation. Model development was conducted using retrospective data available in 90 pediatric and young adult patients who had undergone hematopoietic cell transplantation with busulfan conditioning. Busulfan drug levels and potential covariates influencing drug exposure were analyzed using the nonlinear mixed effects modeling software, NONMEM. The final population PK model was implemented into a clinician-friendly Microsoft Excel-based tool and used to recommend initial doses of busulfan in a group of 21 pediatric patients prospectively dosed based on the population PK model. Modeling of busulfan time-concentration data indicates that busulfan clearance displays nonlinearity in children, decreasing up to approximately 20% between the concentrations of 250-2000 ng/mL. Important patient-specific covariates found to significantly impact busulfan clearance were actual body weight and age. The percentage of individuals achieving a therapeutic concentration at steady state was significantly higher in subjects receiving initial doses based on the population PK model (81%) than in historical controls dosed on conventional guidelines (52%) (P = 0.02). When compared with the conventional dosing guidelines, the model-based algorithm demonstrates significant improvement for providing targeted busulfan therapy in children and young adults.

Phasic Firing in Vasopressin Cells: Understanding Its Functional Significance through Computational Models

PubMed Central

MacGregor, Duncan J.; Leng, Gareth

2012-01-01

Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing. PMID:23093929

Programming strategy for efficient modeling of dynamics in a population of heterogeneous cells.

PubMed

Hald, Bjørn Olav; Garkier Hendriksen, Morten; Sørensen, Preben Graae

2013-05-15

Heterogeneity is a ubiquitous property of biological systems. Even in a genetically identical population of a single cell type, cell-to-cell differences are observed. Although the functional behavior of a given population is generally robust, the consequences of heterogeneity are fairly unpredictable. In heterogeneous populations, synchronization of events becomes a cardinal problem-particularly for phase coherence in oscillating systems. The present article presents a novel strategy for construction of large-scale simulation programs of heterogeneous biological entities. The strategy is designed to be tractable, to handle heterogeneity and to handle computational cost issues simultaneously, primarily by writing a generator of the 'model to be simulated'. We apply the strategy to model glycolytic oscillations among thousands of yeast cells coupled through the extracellular medium. The usefulness is illustrated through (i) benchmarking, showing an almost linear relationship between model size and run time, and (ii) analysis of the resulting simulations, showing that contrary to the experimental situation, synchronous oscillations are surprisingly hard to achieve, underpinning the need for tools to study heterogeneity. Thus, we present an efficient strategy to model the biological heterogeneity, neglected by ordinary mean-field models. This tool is well posed to facilitate the elucidation of the physiologically vital problem of synchronization. The complete python code is available as Supplementary Information. bjornhald@gmail.com or pgs@kiku.dk Supplementary data are available at Bioinformatics online.

A stochastic step model of replicative senescence explains ROS production rate in ageing cell populations.

PubMed

Lawless, Conor; Jurk, Diana; Gillespie, Colin S; Shanley, Daryl; Saretzki, Gabriele; von Zglinicki, Thomas; Passos, João F

2012-01-01

Increases in cellular Reactive Oxygen Species (ROS) concentration with age have been observed repeatedly in mammalian tissues. Concomitant increases in the proportion of replicatively senescent cells in ageing mammalian tissues have also been observed. Populations of mitotic human fibroblasts cultured in vitro, undergoing transition from proliferation competence to replicative senescence are useful models of ageing human tissues. Similar exponential increases in ROS with age have been observed in this model system. Tracking individual cells in dividing populations is difficult, and so the vast majority of observations have been cross-sectional, at the population level, rather than longitudinal observations of individual cells.One possible explanation for these observations is an exponential increase in ROS in individual fibroblasts with time (e.g. resulting from a vicious cycle between cellular ROS and damage). However, we demonstrate an alternative, simple hypothesis, equally consistent with these observations which does not depend on any gradual increase in ROS concentration: the Stochastic Step Model of Replicative Senescence (SSMRS). We also demonstrate that, consistent with the SSMRS, neither proliferation-competent human fibroblasts of any age, nor populations of hTERT overexpressing human fibroblasts passaged beyond the Hayflick limit, display high ROS concentrations. We conclude that longitudinal studies of single cells and their lineages are now required for testing hypotheses about roles and mechanisms of ROS increase during replicative senescence.

A Stochastic Step Model of Replicative Senescence Explains ROS Production Rate in Ageing Cell Populations

PubMed Central

Lawless, Conor; Jurk, Diana; Gillespie, Colin S.; Shanley, Daryl; Saretzki, Gabriele; von Zglinicki, Thomas; Passos, João F.

2012-01-01

Increases in cellular Reactive Oxygen Species (ROS) concentration with age have been observed repeatedly in mammalian tissues. Concomitant increases in the proportion of replicatively senescent cells in ageing mammalian tissues have also been observed. Populations of mitotic human fibroblasts cultured in vitro, undergoing transition from proliferation competence to replicative senescence are useful models of ageing human tissues. Similar exponential increases in ROS with age have been observed in this model system. Tracking individual cells in dividing populations is difficult, and so the vast majority of observations have been cross-sectional, at the population level, rather than longitudinal observations of individual cells. One possible explanation for these observations is an exponential increase in ROS in individual fibroblasts with time (e.g. resulting from a vicious cycle between cellular ROS and damage). However, we demonstrate an alternative, simple hypothesis, equally consistent with these observations which does not depend on any gradual increase in ROS concentration: the Stochastic Step Model of Replicative Senescence (SSMRS). We also demonstrate that, consistent with the SSMRS, neither proliferation-competent human fibroblasts of any age, nor populations of hTERT overexpressing human fibroblasts passaged beyond the Hayflick limit, display high ROS concentrations. We conclude that longitudinal studies of single cells and their lineages are now required for testing hypotheses about roles and mechanisms of ROS increase during replicative senescence. PMID:22359661

Mathematical Modelling as a Tool to Understand Cell Self-renewal and Differentiation.

PubMed

Getto, Philipp; Marciniak-Czochra, Anna

2015-01-01

Mathematical modeling is a powerful technique to address key questions and paradigms in a variety of complex biological systems and can provide quantitative insights into cell kinetics, fate determination and development of cell populations. The chapter is devoted to a review of modeling of the dynamics of stem cell-initiated systems using mathematical methods of ordinary differential equations. Some basic concepts and tools for cell population dynamics are summarized and presented as a gentle introduction to non-mathematicians. The models take into account different plausible mechanisms regulating homeostasis. Two mathematical frameworks are proposed reflecting, respectively, a discrete (punctuated by division events) and a continuous character of transitions between differentiation stages. Advantages and constraints of the mathematical approaches are presented on examples of models of blood systems and compared to patients data on healthy hematopoiesis.

Modeling Transformation and Conjugation in Bacteria Populations

NASA Astrophysics Data System (ADS)

Russo, John; Dong, J. J.

The rise of antibiotic resistance in bacteria populations is a growing threat to medical treatment of diseases. Transformation, where a cell absorbs a plasmid from its environment, and conjugation, direct transfer of a plasmid from one cell to another, are the two main mechanisms of emergence of antibiotic resistance. We model the processes using a combined approach of Kinetic Monte Carlo simulation and differential equations to describe the plasmid-carrying and plasmid-free populations. Through analysis of our results, we characterize the conditions that lead to dominance of the antibiotic resistant population. NSF-DMR #1248387.

A novel quantitative model of cell cycle progression based on cyclin-dependent kinases activity and population balances.

PubMed

Pisu, Massimo; Concas, Alessandro; Cao, Giacomo

2015-04-01

Cell cycle regulates proliferative cell capacity under normal or pathologic conditions, and in general it governs all in vivo/in vitro cell growth and proliferation processes. Mathematical simulation by means of reliable and predictive models represents an important tool to interpret experiment results, to facilitate the definition of the optimal operating conditions for in vitro cultivation, or to predict the effect of a specific drug in normal/pathologic mammalian cells. Along these lines, a novel model of cell cycle progression is proposed in this work. Specifically, it is based on a population balance (PB) approach that allows one to quantitatively describe cell cycle progression through the different phases experienced by each cell of the entire population during its own life. The transition between two consecutive cell cycle phases is simulated by taking advantage of the biochemical kinetic model developed by Gérard and Goldbeter (2009) which involves cyclin-dependent kinases (CDKs) whose regulation is achieved through a variety of mechanisms that include association with cyclins and protein inhibitors, phosphorylation-dephosphorylation, and cyclin synthesis or degradation. This biochemical model properly describes the entire cell cycle of mammalian cells by maintaining a sufficient level of detail useful to identify check point for transition and to estimate phase duration required by PB. Specific examples are discussed to illustrate the ability of the proposed model to simulate the effect of drugs for in vitro trials of interest in oncology, regenerative medicine and tissue engineering. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantifying the importance of pMHC valency, total pMHC dose and frequency on nanoparticle therapeutic efficacy.

PubMed

Sugarman, Jordan; Tsai, Sue; Santamaria, Pere; Khadra, Anmar

2013-05-01

Nanoparticles (NPs) coated with β-cell-specific peptide major histocompatibility complex (pMHC) class I molecules can effectively restore normoglycemia in spontaneously diabetic nonobese diabetic mice. They do so by expanding pools of cognate memory autoreactive regulatory CD8+ T cells that arise from naive low-avidity T-cell precursors to therapeutic levels. Here we develop our previously constructed mathematical model to explore the effects of compound design parameters (NP dose and pMHC valency) on therapeutic efficacy with the underlying hypothesis that the functional correlates of the therapeutic response (expansion of autoregulatory T cells and deletion of autoantigen-loaded antigen-presenting cells by these T cells) are biphasic. We show, using bifurcation analysis, that the model exhibits a 'resonance'-like behavior for a given range of NP dose in which bistability between the healthy state (possessing zero level of effector T-cell population) and autoimmune state (possessing elevated level of the same population) disappears. A heterogeneous population of model mice subjected to several treatment protocols under these new conditions is conducted to quantify both the average percentage of autoregulatory T cells in responsive and nonresponsive model mice, and the average valency-dependent minimal optimal dose needed for effective therapy. Our results reveal that a moderate increase (≥1.6-fold) in the NP-dependent expansion rate of autoregulatory T-cell population leads to a significant increase in the efficacy and the area corresponding to the effective treatment regimen, provided that NP dose ≥8 μg. We expect the model developed here to generalize to other autoimmune diseases and serve as a computational tool to understand and optimize pMHC-NP-based therapies.

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

PubMed

Kurhekar, Manish; Deshpande, Umesh

2016-01-01

Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model.

PubMed

Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di

2016-07-15

We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.

Identification of Metastatic Tumor Stem Cell

DTIC Science & Technology

2010-09-01

addition to a tumor stem cell , an existence of a metastatic stem cell is predicted. Despite the critical importance of the concept, this idea has not been...isolating stem cell population from a unique set of breast tumor cell lines and by examining their metastatic behavior in an animal model. The overall...will (i) isolate stem - cell population from non-metastatic and metastatic cells of a pair of syngenic breast tumor cell lines, and test their metastatic

Spatial self-organization in hybrid models of multicellular adhesion

NASA Astrophysics Data System (ADS)

Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

2016-10-01

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

Cell differentiation modeled via a coupled two-switch regulatory network

NASA Astrophysics Data System (ADS)

Schittler, D.; Hasenauer, J.; Allgöwer, F.; Waldherr, S.

2010-12-01

Mesenchymal stem cells can give rise to bone and other tissue cells, but their differentiation still escapes full control. In this paper we address this issue by mathematical modeling. We present a model for a genetic switch determining the cell fate of progenitor cells which can differentiate into osteoblasts (bone cells) or chondrocytes (cartilage cells). The model consists of two switch mechanisms and reproduces the experimentally observed three stable equilibrium states: a progenitor, an osteogenic, and a chondrogenic state. Conventionally, the loss of an intermediate (progenitor) state and the entailed attraction to one of two opposite (differentiated) states is modeled as a result of changing parameters. In our model in contrast, we achieve this by distributing the differentiation process to two functional switch parts acting in concert: one triggering differentiation and the other determining cell fate. Via stability and bifurcation analysis, we investigate the effects of biochemical stimuli associated with different system inputs. We employ our model to generate differentiation scenarios on the single cell as well as on the cell population level. The single cell scenarios allow to reconstruct the switching upon extrinsic signals, whereas the cell population scenarios provide a framework to identify the impact of intrinsic properties and the limiting factors for successful differentiation.

Adoptive cell therapy for lymphoma with CD4 T cells depleted of CD137-expressing regulatory T cells.

PubMed

Goldstein, Matthew J; Kohrt, Holbrook E; Houot, Roch; Varghese, Bindu; Lin, Jack T; Swanson, Erica; Levy, Ronald

2012-03-01

Adoptive immunotherapy with antitumor T cells is a promising novel approach for the treatment of cancer. However, T-cell therapy may be limited by the cotransfer of regulatory T cells (T(reg)). Here, we explored this hypothesis by using 2 cell surface markers, CD44 and CD137, to isolate antitumor CD4 T cells while excluding T(regs). In a murine model of B-cell lymphoma, only CD137(neg)CD44(hi) CD4 T cells infiltrated tumor sites and provided protection. Conversely, the population of CD137(pos)CD44hi CD4 T cells consisted primarily of activated T(regs). Notably, this CD137(pos) T(reg) population persisted following adoptive transfer and maintained expression of FoxP3 as well as CD137. Moreover, in vitro these CD137(pos) cells suppressed the proliferation of effector cells in a contact-dependent manner, and in vivo adding the CD137(pos)CD44(hi) CD4 cells to CD137(neg)CD44(hi) CD4 cells suppressed the antitumor immune response. Thus, CD137 expression on CD4 T cells defined a population of activated T(regs) that greatly limited antitumor immune responses. Consistent with observations in the murine model, human lymphoma biopsies also contained a population of CD137(pos) CD4 T cells that were predominantly CD25(pos)FoxP3(pos) T(regs). In conclusion, our findings identify 2 surface markers that can be used to facilitate the enrichment of antitumor CD4 T cells while depleting an inhibitory T(reg) population.

Numerically exploring habitat fragmentation effects on populations using cell-based coupled map lattices

Treesearch

Michael Bevers; Curtis H. Flather

1999-01-01

We examine habitat size, shape, and arrangement effects on populations using a discrete reaction-diffusion model. Diffusion is modeled passively and applied to a cellular grid of territories forming a coupled map lattice. Dispersal mortality is proportional to the amount of nonhabitat and fully occupied habitat surrounding a given cell, with distance decay. After...

Drug scheduling of cancer chemotherapy based on natural actor-critic approach.

PubMed

Ahn, Inkyung; Park, Jooyoung

2011-11-01

Recently, reinforcement learning methods have drawn significant interests in the area of artificial intelligence, and have been successfully applied to various decision-making problems. In this paper, we study the applicability of the NAC (natural actor-critic) approach, a state-of-the-art reinforcement learning method, to the drug scheduling of cancer chemotherapy for an ODE (ordinary differential equation)-based tumor growth model. ODE-based cancer dynamics modeling is an active research area, and many different mathematical models have been proposed. Among these, we use the model proposed by de Pillis and Radunskaya (2003), which considers the growth of tumor cells and their interaction with normal cells and immune cells. The NAC approach is applied to this ODE model with the goal of minimizing the tumor cell population and the drug amount while maintaining the adequate population levels of normal cells and immune cells. In the framework of the NAC approach, the drug dose is regarded as the control input, and the reward signal is defined as a function of the control input and the cell populations of tumor cells, normal cells, and immune cells. According to the control policy found by the NAC approach, effective drug scheduling in cancer chemotherapy for the considered scenarios has turned out to be close to the strategy of continuing drug injection from the beginning until an appropriate time. Also, simulation results showed that the NAC approach can yield better performance than conventional pulsed chemotherapy. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A dual near-infrared and dielectric spectroscopies strategy to monitor populations of Chinese hamster ovary cells in bioreactor.

PubMed

Courtès, Franck; Ebel, Bruno; Guédon, Emmanuel; Marc, Annie

2016-05-01

to develop a new strategy combining near-infrared (NIR) and dielectric spectroscopies for real-time monitoring and in-depth characterizing populations of Chinese hamster ovary cells throughout cultures performed in bioreactors. Spectral data processing was based on off-line analyses of the cells, including trypan blue exclusion method, and lactate dehydrogenase activity (LDH). Viable cell density showed a linear correlation with permittivity up to 6 × 10(6) cells ml(-1), while a logarithmic correlation was found between non-lysed dead cell density and conductivity up to 10(7) cells ml(-1). Additionally, partial least square technique was used to develop a calibration model of the supernatant LDH activity based on online NIR spectra with a RMSEC of 55 U l(-1). Considering the LDH content of viable cells measured to be 110 U per 10(9) cells, the lysed dead cell density could be then estimated. These calibration models provided real-time prediction accuracy (R(2) ≥ 0.95) for the three types of cell populations. The high potential of a dual spectroscopy strategy to enhance the online bioprocesses characterization is demonstrated since it allows the simultaneous determination of viable, dead and lysed cell populations in real time.

Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.

PubMed

Ferrer, Jordi; Prats, Clara; López, Daniel; Vives-Rego, Josep

2009-08-31

Predictive microbiology is the area of food microbiology that attempts to forecast the quantitative evolution of microbial populations over time. This is achieved to a great extent through models that include the mechanisms governing population dynamics. Traditionally, the models used in predictive microbiology are whole-system continuous models that describe population dynamics by means of equations applied to extensive or averaged variables of the whole system. Many existing models can be classified by specific criteria. We can distinguish between survival and growth models by seeing whether they tackle mortality or cell duplication. We can distinguish between empirical (phenomenological) models, which mathematically describe specific behaviour, and theoretical (mechanistic) models with a biological basis, which search for the underlying mechanisms driving already observed phenomena. We can also distinguish between primary, secondary and tertiary models, by examining their treatment of the effects of external factors and constraints on the microbial community. Recently, the use of spatially explicit Individual-based Models (IbMs) has spread through predictive microbiology, due to the current technological capacity of performing measurements on single individual cells and thanks to the consolidation of computational modelling. Spatially explicit IbMs are bottom-up approaches to microbial communities that build bridges between the description of micro-organisms at the cell level and macroscopic observations at the population level. They provide greater insight into the mesoscale phenomena that link unicellular and population levels. Every model is built in response to a particular question and with different aims. Even so, in this research we conducted a SWOT (Strength, Weaknesses, Opportunities and Threats) analysis of the different approaches (population continuous modelling and Individual-based Modelling), which we hope will be helpful for current and future researchers.

An Îto stochastic differential equations model for the dynamics of the MCF-7 breast cancer cell line treated by radiotherapy.

PubMed

Oroji, Amin; Omar, Mohd; Yarahmadian, Shantia

2016-10-21

In this paper, a new mathematical model is proposed for studying the population dynamics of breast cancer cells treated by radiotherapy by using a system of stochastic differential equations. The novelty of the model is essentially in capturing the concept of the cell cycle in the modeling to be able to evaluate the tumor lifespan. According to the cell cycle, each cell belongs to one of three subpopulations G, S, or M, representing gap, synthesis and mitosis subpopulations. Cells in the M subpopulation are highly radio-sensitive, whereas cells in the S subpopulation are highly radio-resistant. Therefore, in the process of radiotherapy, cell death rates of different subpopulations are not equal. In addition, since flow cytometry is unable to detect apoptotic cells accurately, the small changes in cell death rate in each subpopulation during treatment are considered. Subsequently, the proposed model is calibrated using experimental data from previous experiments involving the MCF-7 breast cancer cell line. Consequently, the proposed model is able to predict tumor lifespan based on the number of initial carcinoma cells. The results show the effectiveness of the radiation under the condition of stability, which describes the decreasing trend of the tumor cells population. Copyright © 2016 Elsevier Ltd. All rights reserved.

TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data

PubMed Central

Roth, Andrew; Khattra, Jaswinder; Ho, Julie; Yap, Damian; Prentice, Leah M.; Melnyk, Nataliya; McPherson, Andrew; Bashashati, Ali; Laks, Emma; Biele, Justina; Ding, Jiarui; Le, Alan; Rosner, Jamie; Shumansky, Karey; Marra, Marco A.; Gilks, C. Blake; Huntsman, David G.; McAlpine, Jessica N.; Aparicio, Samuel

2014-01-01

The evolution of cancer genomes within a single tumor creates mixed cell populations with divergent somatic mutational landscapes. Inference of tumor subpopulations has been disproportionately focused on the assessment of somatic point mutations, whereas computational methods targeting evolutionary dynamics of copy number alterations (CNA) and loss of heterozygosity (LOH) in whole-genome sequencing data remain underdeveloped. We present a novel probabilistic model, TITAN, to infer CNA and LOH events while accounting for mixtures of cell populations, thereby estimating the proportion of cells harboring each event. We evaluate TITAN on idealized mixtures, simulating clonal populations from whole-genome sequences taken from genomically heterogeneous ovarian tumor sites collected from the same patient. In addition, we show in 23 whole genomes of breast tumors that the inference of CNA and LOH using TITAN critically informs population structure and the nature of the evolving cancer genome. Finally, we experimentally validated subclonal predictions using fluorescence in situ hybridization (FISH) and single-cell sequencing from an ovarian cancer patient sample, thereby recapitulating the key modeling assumptions of TITAN. PMID:25060187

Traveling waves in a coupled reaction-diffusion and difference model of hematopoiesis

NASA Astrophysics Data System (ADS)

Adimy, M.; Chekroun, A.; Kazmierczak, B.

2017-04-01

The formation and development of blood cells is a very complex process, called hematopoiesis. This process involves a small population of cells called hematopoietic stem cells (HSCs). The HSCs are undifferentiated cells, located in the bone marrow before they become mature blood cells and enter the blood stream. They have a unique ability to produce either similar cells (self-renewal), or cells engaged in one of different lineages of blood cells: red blood cells, white cells and platelets (differentiation). The HSCs can be either in a proliferating or in a quiescent phase. In this paper, we distinguish between dividing cells that enter directly to the quiescent phase and dividing cells that return to the proliferating phase to divide again. We propose a mathematical model describing the dynamics of HSC population, taking into account their spatial distribution. The resulting model is a coupled reaction-diffusion equation and difference equation with delay. We study the existence of monotone traveling wave fronts and the asymptotic speed of spread.

Characterizing human stem cell-derived sensory neurons at the single-cell level reveals their ion channel expression and utility in pain research.

PubMed

Young, Gareth T; Gutteridge, Alex; Fox, Heather DE; Wilbrey, Anna L; Cao, Lishuang; Cho, Lily T; Brown, Adam R; Benn, Caroline L; Kammonen, Laura R; Friedman, Julia H; Bictash, Magda; Whiting, Paul; Bilsland, James G; Stevens, Edward B

2014-08-01

The generation of human sensory neurons by directed differentiation of pluripotent stem cells opens new opportunities for investigating the biology of pain. The inability to generate this cell type has meant that up until now their study has been reliant on the use of rodent models. Here, we use a combination of population and single-cell techniques to perform a detailed molecular, electrophysiological, and pharmacological phenotyping of sensory neurons derived from human embryonic stem cells. We describe the evolution of cell populations over 6 weeks of directed differentiation; a process that results in the generation of a largely homogeneous population of neurons that are both molecularly and functionally comparable to human sensory neurons derived from mature dorsal root ganglia. This work opens the prospect of using pluripotent stem-cell-derived sensory neurons to study human neuronal physiology and as in vitro models for drug discovery in pain and sensory disorders.

Dynamic equilibrium of heterogeneous and interconvertible multipotent hematopoietic cell subsets

PubMed Central

Weston, Wendy; Zayas, Jennifer; Perez, Ruben; George, John; Jurecic, Roland

2014-01-01

Populations of hematopoietic stem cells and progenitors are quite heterogeneous and consist of multiple cell subsets with distinct phenotypic and functional characteristics. Some of these subsets also appear to be interconvertible and oscillate between functionally distinct states. The multipotent hematopoietic cell line EML has emerged as a unique model to study the heterogeneity and interconvertibility of multipotent hematopoietic cells. Here we describe extensive phenotypic and functional heterogeneity of EML cells which stems from the coexistence of multiple cell subsets. Each of these subsets is phenotypically and functionally heterogeneous, and displays distinct multilineage differentiation potential, cell cycle profile, proliferation kinetics, and expression pattern of HSC markers and some of the key lineage-associated transcription factors. Analysis of their maintenance revealed that on a population level all EML cell subsets exhibit cell-autonomous interconvertible properties, with the capacity to generate all other subsets and re-establish complete parental EML cell population. Moreover, all EML cell subsets generated during multiple cell generations maintain their distinct phenotypic and functional signatures and interconvertible properties. The model of EML cell line suggests that interconvertible multipotent hematopoietic cell subsets coexist in a homeostatically maintained dynamic equilibrium which is regulated by currently unknown cell-intrinsic mechanisms. PMID:24903657

Dynamic equilibrium of heterogeneous and interconvertible multipotent hematopoietic cell subsets.

PubMed

Weston, Wendy; Zayas, Jennifer; Perez, Ruben; George, John; Jurecic, Roland

2014-06-06

Populations of hematopoietic stem cells and progenitors are quite heterogeneous and consist of multiple cell subsets with distinct phenotypic and functional characteristics. Some of these subsets also appear to be interconvertible and oscillate between functionally distinct states. The multipotent hematopoietic cell line EML has emerged as a unique model to study the heterogeneity and interconvertibility of multipotent hematopoietic cells. Here we describe extensive phenotypic and functional heterogeneity of EML cells which stems from the coexistence of multiple cell subsets. Each of these subsets is phenotypically and functionally heterogeneous, and displays distinct multilineage differentiation potential, cell cycle profile, proliferation kinetics, and expression pattern of HSC markers and some of the key lineage-associated transcription factors. Analysis of their maintenance revealed that on a population level all EML cell subsets exhibit cell-autonomous interconvertible properties, with the capacity to generate all other subsets and re-establish complete parental EML cell population. Moreover, all EML cell subsets generated during multiple cell generations maintain their distinct phenotypic and functional signatures and interconvertible properties. The model of EML cell line suggests that interconvertible multipotent hematopoietic cell subsets coexist in a homeostatically maintained dynamic equilibrium which is regulated by currently unknown cell-intrinsic mechanisms.

Endometrial Stromal Cells and Immune Cell Populations Within Lymph Nodes in a Nonhuman Primate Model of Endometriosis

PubMed Central

Fazleabas, A. T.; Braundmeier, A. G.; Markham, R.; Fraser, I. S.; Berbic, M.

2011-01-01

Mounting evidence suggests that immunological responses may be altered in endometriosis. The baboon (Papio anubis) is generally considered the best model of endometriosis pathogenesis. The objective of the current study was to investigate for the first time immunological changes within uterine and peritoneal draining lymph nodes in a nonhuman primate baboon model of endometriosis. Paraffin-embedded femoral lymph nodes were obtained from 22 normally cycling female baboons (induced endometriosis n = 11; control n = 11). Immunohistochemical staining was performed with antibodies for endometrial stromal cells, T cells, immature and mature dendritic cells, and B cells. Lymph nodes were evaluated using an automated cellular imaging system. Endometrial stromal cells were significantly increased in lymph nodes from animals with induced endometriosis, compared to control animals (P = .033). In animals with induced endometriosis, some lymph node immune cell populations including T cells, dendritic cells and B cells were increased, suggesting an efficient early response or peritoneal drainage. PMID:21617251

A comparison between the stability properties in a DDE model for leukemia and the modified fractional counterpart

NASA Astrophysics Data System (ADS)

Rǎdulescu, I. R.; Cândea, D.; Kaslik, E.

2017-01-01

In this paper, a delay differential equations (DDEs) model of leukemia is introduced and its dynamical properties are investigated in comparison with the modified fractional-order system where the Caputo's derivative is used. The model takes into account three types of division that a stem-like cell can undergo and cell competition between healthy and leukemia cell populations. The action of the immune system on the leukemic cell populations is also considered. The stability properties of the equilibrium points are established through numerical results and the differences between the two types of approaches are discussed. Medical conclusions are drawn in view of the obtained numerical simulations.

CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets

PubMed Central

Nowicka, Malgorzata; Krieg, Carsten; Weber, Lukas M.; Hartmann, Felix J.; Guglietta, Silvia; Becher, Burkhard; Levesque, Mitchell P.; Robinson, Mark D.

2017-01-01

High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals). PMID:28663787

Luminance, Colour, Viewpoint and Border Enhanced Disparity Energy Model

PubMed Central

Martins, Jaime A.; Rodrigues, João M. F.; du Buf, Hans

2015-01-01

The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas. PMID:26107954

Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors.

PubMed

Lorz, Alexander; Lorenzi, Tommaso; Clairambault, Jean; Escargueil, Alexandre; Perthame, Benoît

2015-01-01

Histopathological evidence supports the idea that the emergence of phenotypic heterogeneity and resistance to cytotoxic drugs can be considered as a process of selection in tumor cell populations. In this framework, can we explain intra-tumor heterogeneity in terms of selection driven by the local cell environment? Can we overcome the emergence of resistance and favor the eradication of cancer cells by using combination therapies? Bearing these questions in mind, we develop a model describing cell dynamics inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs. Cancer cells are assumed to be structured as a population by two real variables standing for space position and the expression level of a phenotype of resistance to cytotoxic drugs. The model takes explicitly into account the dynamics of resources and anticancer drugs as well as their interactions with the cell population under treatment. We analyze the effects of space structure and combination therapies on phenotypic heterogeneity and chemotherapeutic resistance. Furthermore, we study the efficacy of combined therapy protocols based on constant infusion and bang-bang delivery of cytotoxic and cytostatic drugs.

Ranitidine modifies myeloid cell populations and inhibits breast tumor development and spread in mice

PubMed Central

Vila-Leahey, Ava; Oldford, Sharon A.; Marignani, Paola A.; Wang, Jun; Haidl, Ian D.; Marshall, Jean S.

2016-01-01

ABSTRACT Histamine receptor 2 (H2) antagonists are widely used clinically for the control of gastrointestinal symptoms, but also impact immune function. They have been reported to reduce tumor growth in established colon and lung cancer models. Histamine has also been reported to modify populations of myeloid-derived suppressor cells (MDSCs). We have examined the impact of the widely used H2 antagonist ranitidine, on both myeloid cell populations and tumor development and spread, in three distinct models of breast cancer that highlight different stages of cancer progression. Oral ranitidine treatment significantly decreased the monocytic MDSC population in the spleen and bone marrow both alone and in the context of an orthotopic breast tumor model. H2 antagonists ranitidine and famotidine, but not H1 or H4 antagonists, significantly inhibited lung metastasis in the 4T1 model. In the E0771 model, ranitidine decreased primary tumor growth while omeprazole treatment had no impact on tumor development. Gemcitabine treatment prevented the tumor growth inhibition associated with ranitidine treatment. In keeping with ranitidine-induced changes in myeloid cell populations in non-tumor-bearing mice, ranitidine also delayed the onset of spontaneous tumor development, and decreased the number of tumors that developed in LKB1−/−/NIC mice. These results indicate that ranitidine alters monocyte populations associated with MDSC activity, and subsequently impacts breast tumor development and outcome. Ranitidine has potential as an adjuvant therapy or preventative agent in breast cancer and provides a novel and safe approach to the long-term reduction of tumor-associated immune suppression. PMID:27622015

Increasing accuracy of dispersal kernels in grid-based population models

USGS Publications Warehouse

Slone, D.H.

2011-01-01

Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels (σ > 10 cells), the total kernel error was <10 &sup-11; compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10-11 and invasion time error to <5%.

Mesenchymal stem cells support neuronal fiber growth in an organotypic brain slice co-culture model.

PubMed

Sygnecka, Katja; Heider, Andreas; Scherf, Nico; Alt, Rüdiger; Franke, Heike; Heine, Claudia

2015-04-01

Mesenchymal stem cells (MSCs) have been identified as promising candidates for neuroregenerative cell therapies. However, the impact of different isolation procedures on the functional and regenerative characteristics of MSC populations has not been studied thoroughly. To quantify these differences, we directly compared classically isolated bulk bone marrow-derived MSCs (bulk BM-MSCs) to the subpopulation Sca-1(+)Lin(-)CD45(-)-derived MSCs(-) (SL45-MSCs), isolated by fluorescence-activated cell sorting from bulk BM-cell suspensions. Both populations were analyzed with respect to functional readouts, that are, frequency of fibroblast colony forming units (CFU-f), general morphology, and expression of stem cell markers. The SL45-MSC population is characterized by greater morphological homogeneity, higher CFU-f frequency, and significantly increased nestin expression compared with bulk BM-MSCs. We further quantified the potential of both cell populations to enhance neuronal fiber growth, using an ex vivo model of organotypic brain slice co-cultures of the mesocortical dopaminergic projection system. The MSC populations were cultivated underneath the slice co-cultures without direct contact using a transwell system. After cultivation, the fiber density in the border region between the two brain slices was quantified. While both populations significantly enhanced fiber outgrowth as compared with controls, purified SL45-MSCs stimulated fiber growth to a larger degree. Subsequently, we analyzed the expression of different growth factors in both cell populations. The results show a significantly higher expression of brain-derived neurotrophic factor (BDNF) and basic fibroblast growth factor in the SL45-MSCs population. Altogether, we conclude that MSC preparations enriched for primary MSCs promote neuronal regeneration and axonal regrowth, more effectively than bulk BM-MSCs, an effect that may be mediated by a higher BDNF secretion.

The developing cancer stem-cell model: clinical challenges and opportunities.

PubMed

Vermeulen, Louis; de Sousa e Melo, Felipe; Richel, Dick J; Medema, Jan Paul

2012-02-01

During the past decade, a stem-cell-like subset of cancer cells has been identified in many malignancies. These cells, referred to as cancer stem cells (CSCs), are of particular interest because they are believed to be the clonogenic core of the tumour and therefore represent the cell population that drives growth and progression. Many efforts have been made to design therapies that specifically target the CSC population, since this was predicted to be the crucial population to eliminate. However, recent insights have complicated the initial elegant model, by showing a dominant role for the tumour microenvironment in determining CSC characteristics within a malignancy. This is particularly important since dedifferentiation of non-tumorigenic tumour cells towards CSCs can occur, and therefore the CSC population in a neoplasm is expected to vary over time. Moreover, evidence suggests that not all tumours are driven by rare CSCs, but might instead contain a large population of tumorigenic cells. Even though these results suggest that specific targeting of the CSC population might not be a useful therapeutic strategy, research into the hierarchical cellular organisation of malignancies has provided many important new insights in the biology of tumours. In this Personal View, we highlight how the CSC concept is developing and influences our thinking on future treatment for solid tumours, and recommend ways to design clinical trials to assess drugs that target malignant disease in a rational fashion. Copyright © 2012 Elsevier Ltd. All rights reserved.

Stochasticity in the signalling network of a model microbe

NASA Astrophysics Data System (ADS)

Bischofs, Ilka; Foley, Jonathan; Battenberg, Eric; Fontaine-Bodin, Lisa; Price, Gavin; Wolf, Denise; Arkin, Adam

2007-03-01

The soil dwelling bacterium Bacillus subtilis is an excellent model organism for studying stochastic stress response induction in an isoclonal population. Subjected to the same stressor cells undergo different cell fates, including sporulation, competence, degradative enzyme synthesis and motility. For example, under conditions of nutrient deprivation and high cell density only a portion of the cell population forms an endospore. Here we use a combined experimental and theoretical approach to study stochastic sporulation induction in Bacillus subtilis. Using several fluorescent reporter strains we apply time lapse fluorescent microscopy in combination with quantitative image analysis to study cell fate progression on a single cell basis and elucidate key noise generators in the underlying cellular network.

Modeling and Analysis of a Nonlinear Age-Structured Model for Tumor Cell Populations with Quiescence

NASA Astrophysics Data System (ADS)

Liu, Zijian; Chen, Jing; Pang, Jianhua; Bi, Ping; Ruan, Shigui

2018-05-01

We present a nonlinear first-order hyperbolic partial differential equation model to describe age-structured tumor cell populations with proliferating and quiescent phases at the avascular stage in vitro. The division rate of the proliferating cells is assumed to be nonlinear due to the limitation of the nutrient and space. The model includes a proportion of newborn cells that enter directly the quiescent phase with age zero. This proportion can reflect the effect of treatment by drugs such as erlotinib. The existence and uniqueness of solutions are established. The local and global stabilities of the trivial steady state are investigated. The existence and local stability of the positive steady state are also analyzed. Numerical simulations are performed to verify the results and to examine the impacts of parameters on the nonlinear dynamics of the model.

SU-E-T-565: RAdiation Resistance of Cancer CElls Using GEANT4 DNA: RACE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perrot, Y; Payno, H; Delage, E

2014-06-01

Purpose: The objective of the RACE project is to develop a comparison between Monte Carlo simulation using the Geant4-DNA toolkit and measurements of radiation damage on 3D melanoma and chondrosarcoma culture cells coupled with gadolinium nanoparticles. We currently expose the status of the developments regarding simulations. Methods: Monte Carlo studies are driven using the Geant4 toolkit and the Geant4-DNA extension. In order to model the geometry of a cell population, the opensource CPOP++ program is being developed for the geometrical representation of 3D cell populations including a specific cell mesh coupled with a multi-agent system. Each cell includes cytoplasm andmore » nucleus. The correct modeling of the cell population has been validated with confocal microscopy images of spheroids. The Geant4 Livermore physics models are used to simulate the interactions of a 250 keV X-ray beam and the production of secondaries from gadolinium nanoparticles supposed to be fixed on the cell membranes. Geant4-DNA processes are used to simulate the interactions of charged particles with the cells. An atomistic description of the DNA molecule, from PDB (Protein Data Bank) files, is provided by the so-called PDB4DNA Geant4 user application we developed to score energy depositions in DNA base pairs and sugar-phosphate groups. Results: At the microscopic level, our simulations enable assessing microscopic energy distribution in each cell compartment of a realistic 3D cell population. Dose enhancement factors due to the presence of gadolinium nanoparticles can be estimated. At the nanometer scale, direct damages on nuclear DNA are also estimated. Conclusion: We successfully simulated the impact of direct radiations on a realistic 3D cell population model compatible with microdosimetry calculations using the Geant4-DNA toolkit. Upcoming validation and the future integration of the radiochemistry module of Geant4-DNA will propose to correlate clusters of ionizations with in vitro experiments. All those developments will be released publicly. This work was supported by grants from Plan Cancer 2009-2013 French national initiative managed by INSERM (Institut National de la Sante et de la Recherche Medicale)« less

Stochasticity and Spatial Interaction Govern Stem Cell Differentiation Dynamics

NASA Astrophysics Data System (ADS)

Smith, Quinton; Stukalin, Evgeny; Kusuma, Sravanti; Gerecht, Sharon; Sun, Sean X.

2015-07-01

Stem cell differentiation underlies many fundamental processes such as development, tissue growth and regeneration, as well as disease progression. Understanding how stem cell differentiation is controlled in mixed cell populations is an important step in developing quantitative models of cell population dynamics. Here we focus on quantifying the role of cell-cell interactions in determining stem cell fate. Toward this, we monitor stem cell differentiation in adherent cultures on micropatterns and collect statistical cell fate data. Results show high cell fate variability and a bimodal probability distribution of stem cell fraction on small (80-140 μm diameter) micropatterns. On larger (225-500 μm diameter) micropatterns, the variability is also high but the distribution of the stem cell fraction becomes unimodal. Using a stochastic model, we analyze the differentiation dynamics and quantitatively determine the differentiation probability as a function of stem cell fraction. Results indicate that stem cells can interact and sense cellular composition in their immediate neighborhood and adjust their differentiation probability accordingly. Blocking epithelial cadherin (E-cadherin) can diminish this cell-cell contact mediated sensing. For larger micropatterns, cell motility adds a spatial dimension to the picture. Taken together, we find stochasticity and cell-cell interactions are important factors in determining cell fate in mixed cell populations.

Modeling mechanical inhomogeneities in small populations of proliferating monolayers and spheroids.

PubMed

Lejeune, Emma; Linder, Christian

2018-06-01

Understanding the mechanical behavior of multicellular monolayers and spheroids is fundamental to tissue culture, organism development, and the early stages of tumor growth. Proliferating cells in monolayers and spheroids experience mechanical forces as they grow and divide and local inhomogeneities in the mechanical microenvironment can cause individual cells within the multicellular system to grow and divide at different rates. This differential growth, combined with cell division and reorganization, leads to residual stress. Multiple different modeling approaches have been taken to understand and predict the residual stresses that arise in growing multicellular systems, particularly tumor spheroids. Here, we show that by using a mechanically robust agent-based model constructed with the peridynamic framework, we gain a better understanding of residual stresses in multicellular systems as they grow from a single cell. In particular, we focus on small populations of cells (1-100 s) where population behavior is highly stochastic and prior investigation has been limited. We compare the average strain energy density of cells in monolayers and spheroids using different growth and division rules and find that, on average, cells in spheroids have a higher strain energy density than cells in monolayers. We also find that cells in the interior of a growing spheroid are, on average, in compression. Finally, we demonstrate the importance of accounting for stochastic fluctuations in the mechanical environment, particularly when the cellular response to mechanical cues is nonlinear. The results presented here serve as a starting point for both further investigation with agent-based models, and for the incorporation of major findings from agent-based models into continuum scale models when explicit representation of individual cells is not computationally feasible.

Neuronal differentiation and long-term culture of the human neuroblastoma line SH-SY5Y.

PubMed

Constantinescu, R; Constantinescu, A T; Reichmann, H; Janetzky, B

2007-01-01

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder in industrialized countries. Present cell culture models for PD rely on either primary cells or immortal cell lines, neither of which allow for long-term experiments on a constant population, a crucial requisite for a realistic model of slowly progressing neurodegenerative diseases. We differentiated SH-SY5Y human dopaminergic neuroblastoma cells to a neuronal-like state in a perfusion culture system using a combination of retinoic acid and mitotic inhibitors. The cells could be cultivated for two months without the need for passage. We show, by various means, that the differentiated cells exhibit, at the molecular level, many neuronal properties not characteristic to the starting line. This approach opens the possibility to develop chronic models, in which the effect of perturbations and putative counteracting strategies can be monitored over long periods of time in a quasi-stable cell population.

Modeling mechanical interactions in growing populations of rod-shaped bacteria

NASA Astrophysics Data System (ADS)

Winkle, James J.; Igoshin, Oleg A.; Bennett, Matthew R.; Josić, Krešimir; Ott, William

2017-10-01

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell’s environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

Clonal analysis of synovial fluid stem cells to characterize and identify stable mesenchymal stromal cell/mesenchymal progenitor cell phenotypes in a porcine model: a cell source with enhanced commitment to the chondrogenic lineage.

PubMed

Ando, Wataru; Kutcher, Josh J; Krawetz, Roman; Sen, Arindom; Nakamura, Norimasa; Frank, Cyril B; Hart, David A

2014-06-01

Previous studies have demonstrated that porcine synovial membrane stem cells can adhere to a cartilage defect in vivo through the use of a tissue-engineered construct approach. To optimize this model, we wanted to compare effectiveness of tissue sources to determine whether porcine synovial fluid, synovial membrane, bone marrow and skin sources replicate our understanding of synovial fluid mesenchymal stromal cells or mesenchymal progenitor cells from humans both at the population level and the single-cell level. Synovial fluid clones were subsequently isolated and characterized to identify cells with a highly characterized optimal phenotype. The chondrogenic, osteogenic and adipogenic potentials were assessed in vitro for skin, bone marrow, adipose, synovial fluid and synovial membrane-derived stem cells. Synovial fluid cells then underwent limiting dilution analysis to isolate single clonal populations. These clonal populations were assessed for proliferative and differentiation potential by use of standardized protocols. Porcine-derived cells demonstrated the same relationship between cell sources as that demonstrated previously for humans, suggesting that the pig may be an ideal preclinical animal model. Synovial fluid cells demonstrated the highest chondrogenic potential that was further characterized, demonstrating the existence of a unique clonal phenotype with enhanced chondrogenic potential. Porcine stem cells demonstrate characteristics similar to those in human-derived mesenchymal stromal cells from the same sources. Synovial fluid-derived stem cells contain an inherent phenotype that may be optimal for cartilage repair. This must be more fully investigated for future use in the in vivo tissue-engineered construct approach in this physiologically relevant preclinical porcine model. Copyright © 2014 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Population transcriptomics with single-cell resolution: a new field made possible by microfluidics: a technology for high throughput transcript counting and data-driven definition of cell types.

PubMed

Plessy, Charles; Desbois, Linda; Fujii, Teruo; Carninci, Piero

2013-02-01

Tissues contain complex populations of cells. Like countries, which are comprised of mixed populations of people, tissues are not homogeneous. Gene expression studies that analyze entire populations of cells from tissues as a mixture are blind to this diversity. Thus, critical information is lost when studying samples rich in specialized but diverse cells such as tumors, iPS colonies, or brain tissue. High throughput methods are needed to address, model and understand the constitutive and stochastic differences between individual cells. Here, we describe microfluidics technologies that utilize a combination of molecular biology and miniaturized labs on chips to study gene expression at the single cell level. We discuss how the characterization of the transcriptome of each cell in a sample will open a new field in gene expression analysis, population transcriptomics, that will change the academic and biomedical analysis of complex samples by defining them as quantified populations of single cells. Copyright © 2013 WILEY Periodicals, Inc.

Effects of developmental variability on the dynamics and self-organization of cell populations

NASA Astrophysics Data System (ADS)

Prabhakara, Kaumudi H.; Gholami, Azam; Zykov, Vladimir S.; Bodenschatz, Eberhard

2017-11-01

We report experimental and theoretical results for spatiotemporal pattern formation in cell populations, where the parameters vary in space and time due to mechanisms intrinsic to the system, namely Dictyostelium discoideum (D.d.) in the starvation phase. We find that different patterns are formed when the populations are initialized at different developmental stages, or when populations at different initial developmental stages are mixed. The experimentally observed patterns can be understood with a modified Kessler-Levine model that takes into account the initial spatial heterogeneity of the cell populations and a developmental path introduced by us, i.e. the time dependence of the various biochemical parameters. The dynamics of the parameters agree with known biochemical studies. Most importantly, the modified model reproduces not only our results, but also the observations of an independent experiment published earlier. This shows that pattern formation can be used to understand and quantify the temporal evolution of the system parameters.

An "age"-structured model of hematopoietic stem cell organization with application to chronic myeloid leukemia.

PubMed

Roeder, Ingo; Herberg, Maria; Horn, Matthias

2009-04-01

Previously, we have modeled hematopoietic stem cell organization by a stochastic, single cell-based approach. Applications to different experimental systems demonstrated that this model consistently explains a broad variety of in vivo and in vitro data. A major advantage of the agent-based model (ABM) is the representation of heterogeneity within the hematopoietic stem cell population. However, this advantage comes at the price of time-consuming simulations if the systems become large. One example in this respect is the modeling of disease and treatment dynamics in patients with chronic myeloid leukemia (CML), where the realistic number of individual cells to be considered exceeds 10(6). To overcome this deficiency, without losing the representation of the inherent heterogeneity of the stem cell population, we here propose to approximate the ABM by a system of partial differential equations (PDEs). The major benefit of such an approach is its independence from the size of the system. Although this mean field approach includes a number of simplifying assumptions compared to the ABM, it retains the key structure of the model including the "age"-structure of stem cells. We show that the PDE model qualitatively and quantitatively reproduces the results of the agent-based approach.

The prisoner's dilemma as a cancer model.

PubMed

West, Jeffrey; Hasnain, Zaki; Mason, Jeremy; Newton, Paul K

2016-09-01

Tumor development is an evolutionary process in which a heterogeneous population of cells with different growth capabilities compete for resources in order to gain a proliferative advantage. What are the minimal ingredients needed to recreate some of the emergent features of such a developing complex ecosystem? What is a tumor doing before we can detect it? We outline a mathematical model, driven by a stochastic Moran process, in which cancer cells and healthy cells compete for dominance in the population. Each are assigned payoffs according to a Prisoner's Dilemma evolutionary game where the healthy cells are the cooperators and the cancer cells are the defectors. With point mutational dynamics, heredity, and a fitness landscape controlling birth and death rates, natural selection acts on the cell population and simulated 'cancer-like' features emerge, such as Gompertzian tumor growth driven by heterogeneity, the log-kill law which (linearly) relates therapeutic dose density to the (log) probability of cancer cell survival, and the Norton-Simon hypothesis which (linearly) relates tumor regression rates to tumor growth rates. We highlight the utility, clarity, and power that such models provide, despite (and because of) their simplicity and built-in assumptions.

Changes in tumor cell heterogeneity after chemotherapy treatment in a xenograft model of glioblastoma.

PubMed

Welker, Alessandra M; Jaros, Brian D; An, Min; Beattie, Christine E

2017-07-25

Glioblastoma (GBM) is a highly aggressive brain cancer with limited treatments and poor patient survival. GBM tumors are heterogeneous containing a complex mixture of dividing cells, differentiated cells, and cancer stem cells. It is unclear, however, how these different cell populations contribute to tumor growth or whether they exhibit differential responses to chemotherapy. Here we set out to address these questions using a zebrafish xenograft transplant model (Welker et al., 2016). We found that a small population of differentiated vimentin-positive tumor cells, but a majority of Sox2-positive putative cancer stem cells, were dividing during tumor growth. We also observed co-expression of Sox2 and GFAP, another suggested marker of glioma cancer stem cells, indicating that the putative cancer stem cells in GBM9 tumors expressed both of these markers. To determine how these different tumor cell populations responded to chemotherapy, we treated animals with temozolomide (TMZ) and assessed these cell populations immediately after treatment and 5 and 10days after treatment cessation. As expected we found a significant decrease in dividing cells after treatment. We also found a significant decrease in vimentin-positive cells, but not in Sox2 or GFAP-positive cells. However, the Sox2-positive cells significantly increased 5days after TMZ treatment. These data support that putative glioma cancer stem cells are more resistant to TMZ treatment and may contribute to tumor regrowth after chemotherapy. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data.

PubMed

Vallejos, Catalina A; Marioni, John C; Richardson, Sylvia

2015-06-01

Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of unexplained technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model where: (i) cell-specific normalisation constants are estimated as part of the model parameters, (ii) technical variability is quantified based on spike-in genes that are artificially introduced to each analysed cell's lysate and (iii) the total variability of the expression counts is decomposed into technical and biological components. BASiCS also provides an intuitive detection criterion for highly (or lowly) variable genes within the population of cells under study. This is formalised by means of tail posterior probabilities associated to high (or low) biological cell-to-cell variance contributions, quantities that can be easily interpreted by users. We demonstrate our method using gene expression measurements from mouse Embryonic Stem Cells. Cross-validation and meaningful enrichment of gene ontology categories within genes classified as highly (or lowly) variable supports the efficacy of our approach.

In vitro ovine articular chondrocyte proliferation: experiments and modelling.

PubMed

Mancuso, L; Liuzzo, M I; Fadda, S; Pisu, M; Cincotti, A; Arras, M; La Nasa, G; Concas, A; Cao, G

2010-06-01

This study focuses on analysis of in vitro cultures of chondrocytes from ovine articular cartilage. Isolated cells were seeded in Petri dishes, then expanded to confluence and phenotypically characterized by flow cytometry. The sigmoidal temporal profile of total counts was obtained by classic haemocytometry and corresponding cell size distributions were measured electronically using a Coulter Counter. A mathematical model recently proposed (1) was adopted for quantitative interpretation of these experimental data. The model is based on a 1-D (that is, mass-structured), single-staged population balance approach capable of taking into account contact inhibition at confluence. The model's parameters were determined by fitting measured total cell counts and size distributions. Model reliability was verified by predicting cell proliferation counts and corresponding size distributions at culture times longer than those used when tuning the model's parameters. It was found that adoption of cell mass as the intrinsic characteristic of a growing chondrocyte population enables sigmoidal temporal profiles of total counts in the Petri dish, as well as cell size distributions at 'balanced growth', to be adequately predicted.

Cancer growth and its inhibition in terms of coherence.

PubMed

Popp, Fritz-Albert

2009-01-01

It is shown that a molecular origin for growth inhibition is rather unlikely because the cross-sectional area of inhibitory forces in a cell population cannot exceed more than about 10(-8) Dalton. A model of the time dependence of cell number N(t), where t is the time, is based on biophotons and explains without any contradiction to known experimental results growth regulation in terms of the factor a = 1/T, which stimulates the cell division rate dN/dt and the factor b = dT/dN(1/T(2)), which inhibits cell division. It accounts for the total cell division rate dN/dt = aN(t) - bN(2)(t). For adults, T is the coherence time of about 10(6) s, corresponding to the longest lifetime of cell organelles in men, while dT/dN = 10(-7) s corresponds to the resolution time of the cell population which is always the average time interval between two cell loss events. Our model follows a stringently holistic approach to describing a cell population as an entity, regulated by a fully coherent (biophoton) field.

Accounting for Space—Quantification of Cell-To-Cell Transmission Kinetics Using Virus Dynamics Models.

PubMed

Kumberger, Peter; Durso-Cain, Karina; Uprichard, Susan L; Dahari, Harel; Graw, Frederik

2018-04-17

Mathematical models based on ordinary differential equations (ODE) that describe the population dynamics of viruses and infected cells have been an essential tool to characterize and quantify viral infection dynamics. Although an important aspect of viral infection is the dynamics of viral spread, which includes transmission by cell-free virions and direct cell-to-cell transmission, models used so far ignored cell-to-cell transmission completely, or accounted for this process by simple mass-action kinetics between infected and uninfected cells. In this study, we show that the simple mass-action approach falls short when describing viral spread in a spatially-defined environment. Using simulated data, we present a model extension that allows correct quantification of cell-to-cell transmission dynamics within a monolayer of cells. By considering the decreasing proportion of cells that can contribute to cell-to-cell spread with progressing infection, our extension accounts for the transmission dynamics on a single cell level while still remaining applicable to standard population-based experimental measurements. While the ability to infer the proportion of cells infected by either of the transmission modes depends on the viral diffusion rate, the improved estimates obtained using our novel approach emphasize the need to correctly account for spatial aspects when analyzing viral spread.

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

PubMed Central

Vallejos, Catalina A.; Marioni, John C.; Richardson, Sylvia

2015-01-01

Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of unexplained technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model where: (i) cell-specific normalisation constants are estimated as part of the model parameters, (ii) technical variability is quantified based on spike-in genes that are artificially introduced to each analysed cell’s lysate and (iii) the total variability of the expression counts is decomposed into technical and biological components. BASiCS also provides an intuitive detection criterion for highly (or lowly) variable genes within the population of cells under study. This is formalised by means of tail posterior probabilities associated to high (or low) biological cell-to-cell variance contributions, quantities that can be easily interpreted by users. We demonstrate our method using gene expression measurements from mouse Embryonic Stem Cells. Cross-validation and meaningful enrichment of gene ontology categories within genes classified as highly (or lowly) variable supports the efficacy of our approach. PMID:26107944

Bet-hedging in bacteriocin producing Escherichia coli populations: the single cell perspective

NASA Astrophysics Data System (ADS)

Bayramoglu, Bihter; Toubiana, David; van Vliet, Simon; Inglis, R. Fredrik; Shnerb, Nadav; Gillor, Osnat

2017-02-01

Production of public goods in biological systems is often a collaborative effort that may be detrimental to the producers. It is therefore sustainable only if a small fraction of the population shoulders the cost while the majority reap the benefits. We modelled this scenario using Escherichia coli populations producing colicins, an antibiotic that kills producer cells’ close relatives. Colicin expression is a costly trait, and it has been proposed that only a small fraction of the population actively expresses the antibiotic. Colicinogenic populations were followed at the single-cell level using time-lapse microscopy, and showed two distinct, albeit dynamic, subpopulations: the majority silenced colicin expression, while a small fraction of elongated, slow-growing cells formed colicin-expressing hotspots, placing a significant burden on expressers. Moreover, monitoring lineages of individual colicinogenic cells showed stochastic switching between expressers and non-expressers. Hence, colicin expressers may be engaged in risk-reducing strategies—or bet-hedging—as they balance the cost of colicin production with the need to repel competitors. To test the bet-hedging strategy in colicin-mediated interactions, competitions between colicin-sensitive and producer cells were simulated using a numerical model, demonstrating a finely balanced expression range that is essential to sustaining the colicinogenic population.

Population mixture model for nonlinear telomere dynamics

NASA Astrophysics Data System (ADS)

Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl

2008-12-01

Telomeres are DNA repeats protecting chromosomal ends which shorten with each cell division, eventually leading to cessation of cell growth. We present a population mixture model that predicts an exponential decrease in telomere length with time. We analytically solve the dynamics of the telomere length distribution. The model provides an excellent fit to available telomere data and accounts for the previously unexplained observation of telomere elongation following stress and bone marrow transplantation, thereby providing insight into the nature of the telomere clock.

TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data.

PubMed

Ha, Gavin; Roth, Andrew; Khattra, Jaswinder; Ho, Julie; Yap, Damian; Prentice, Leah M; Melnyk, Nataliya; McPherson, Andrew; Bashashati, Ali; Laks, Emma; Biele, Justina; Ding, Jiarui; Le, Alan; Rosner, Jamie; Shumansky, Karey; Marra, Marco A; Gilks, C Blake; Huntsman, David G; McAlpine, Jessica N; Aparicio, Samuel; Shah, Sohrab P

2014-11-01

The evolution of cancer genomes within a single tumor creates mixed cell populations with divergent somatic mutational landscapes. Inference of tumor subpopulations has been disproportionately focused on the assessment of somatic point mutations, whereas computational methods targeting evolutionary dynamics of copy number alterations (CNA) and loss of heterozygosity (LOH) in whole-genome sequencing data remain underdeveloped. We present a novel probabilistic model, TITAN, to infer CNA and LOH events while accounting for mixtures of cell populations, thereby estimating the proportion of cells harboring each event. We evaluate TITAN on idealized mixtures, simulating clonal populations from whole-genome sequences taken from genomically heterogeneous ovarian tumor sites collected from the same patient. In addition, we show in 23 whole genomes of breast tumors that the inference of CNA and LOH using TITAN critically informs population structure and the nature of the evolving cancer genome. Finally, we experimentally validated subclonal predictions using fluorescence in situ hybridization (FISH) and single-cell sequencing from an ovarian cancer patient sample, thereby recapitulating the key modeling assumptions of TITAN. © 2014 Ha et al.; Published by Cold Spring Harbor Laboratory Press.

Characterization of human skeletal stem and bone cell populations using dielectrophoresis.

PubMed

Ismail, A; Hughes, M P; Mulhall, H J; Oreffo, R O C; Labeed, F H

2015-02-01

Dielectrophoresis (DEP) is a non-invasive cell analysis method that uses differences in electrical properties between particles and surrounding medium to determine a unique set of cellular properties that can be used as a basis for cell separation. Cell-based therapies using skeletal stem cells are currently one of the most promising areas for treating a variety of skeletal and muscular disorders. However, identifying and sorting these cells remains a challenge in the absence of unique skeletal stem cell markers. DEP provides an ideal method for identifying subsets of cells without the need for markers by using their dielectric properties. This study used a 3D dielectrophoretic well chip device to determine the dielectric characteristics of two osteosarcoma cell lines (MG-63 and SAOS-2) and an immunoselected enriched skeletal stem cell fraction (STRO-1 positive cell) of human bone marrow. Skeletal cells were exposed to a series of different frequencies to induce dielectrophoretic cell movement, and a model was developed to generate the membrane and cytoplasmic properties of the cell populations. Differences were observed in the dielectric properties of MG-63, SAOS-2 and STRO-1 enriched skeletal populations, which could potentially be used to sort cells in mixed populations. This study provide evidence of the ability to characterize different human skeletal stem and mature cell populations, and acts as a proof-of-concept that dielectrophoresis can be exploited to detect, isolate and separate skeletal cell populations from heterogeneous bone marrow cell populations. Copyright © 2012 John Wiley & Sons, Ltd.

A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach

DOE PAGES

De Pillis, L. G.; Radunskaya, A.

2001-01-01

We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore » regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less

A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Pillis, L. G.; Radunskaya, A.

We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore » regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less

Podocytes populate cellular crescents in a murine model of inflammatory glomerulonephritis.

PubMed

Moeller, Marcus J; Soofi, Abdulsalaam; Hartmann, Inge; Le Hir, Michel; Wiggins, Roger; Kriz, Wilhelm; Holzman, Lawrence B

2004-01-01

Cellular crescents are a defining histologic finding in many forms of inflammatory glomerulonephritis. Despite numerous studies, the origin of glomerular crescents remains unresolved. A genetic cell lineage-mapping study with a novel transgenic mouse model was performed to investigate whether visceral glomerular epithelial cells, termed podocytes, are precursors of cells that populate cellular crescents. The podocyte-specific 2.5P-Cre mouse line was crossed with the ROSA26 reporter line, resulting in irreversible constitutive expression of beta-galactosidase in doubly transgenic 2.5P-Cre/ROSA26 mice. In these mice, crescentic glomerulonephritis was induced with a previously described rabbit anti-glomerular basement membrane antiserum nephritis approach. Interestingly, beta-galactosidase-positive cells derived from podocytes adhered to the parietal basement membrane and populated glomerular crescents during the early phases of cellular crescent formation, accounting for at least one-fourth of the total cell mass. In cellular crescents, the proliferation marker Ki-67 was expressed in beta-galactosidase-positive and beta-galactosidase-negative cells, indicating that both cell types contributed to the formation of cellular crescents through proliferation in situ. Podocyte-specific antigens, including WT-1, synaptopodin, nephrin, and podocin, were not expressed by any cells in glomerular crescents, suggesting that podocytes underwent profound phenotypic changes in this nephritis model.

Stability and bifurcation in a model for the dynamics of stem-like cells in leukemia under treatment

NASA Astrophysics Data System (ADS)

Rǎdulescu, I. R.; Cândea, D.; Halanay, A.

2012-11-01

A mathematical model for the dynamics of leukemic cells during treatment is introduced. Delay differential equations are used to model cells' evolution and are based on the Mackey-Glass approach, incorporating Goldie-Coldman law. Since resistance is propagated by cells that have the capacity of self-renewal, a population of stem-like cells is studied. Equilibrium points are calculated and their stability properties are investigated.

Computational Model of Population Dynamics Based on the Cell Cycle and Local Interactions

NASA Astrophysics Data System (ADS)

Oprisan, Sorinel Adrian; Oprisan, Ana

2005-03-01

Our study bridges cellular (mesoscopic) level interactions and global population (macroscopic) dynamics of carcinoma. The morphological differences and transitions between well and smooth defined benign tumors and tentacular malignat tumors suggest a theoretical analysis of tumor invasion based on the development of mathematical models exhibiting bifurcations of spatial patterns in the density of tumor cells. Our computational model views the most representative and clinically relevant features of oncogenesis as a fight between two distinct sub-systems: the immune system of the host and the neoplastic system. We implemented the neoplastic sub-system using a three-stage cell cycle: active, dormant, and necrosis. The second considered sub-system consists of cytotoxic active (effector) cells — EC, with a very broad phenotype ranging from NK cells to CTL cells, macrophages, etc. Based on extensive numerical simulations, we correlated the fractal dimensions for carcinoma, which could be obtained from tumor imaging, with the malignat stage. Our computational model was able to also simulate the effects of surgical, chemotherapeutical, and radiotherapeutical treatments.

Maintenance of algal endosymbionts in Paramecium bursaria: a simple model based on population dynamics.

PubMed

Iwai, Sosuke; Fujiwara, Kenji; Tamura, Takuro

2016-09-01

Algal endosymbiosis is widely distributed in eukaryotes including many protists and metazoans, and plays important roles in aquatic ecosystems, combining phagotrophy and phototrophy. To maintain a stable symbiotic relationship, endosymbiont population size in the host must be properly regulated and maintained at a constant level; however, the mechanisms underlying the maintenance of algal endosymbionts are still largely unknown. Here we investigate the population dynamics of the unicellular ciliate Paramecium bursaria and its Chlorella-like algal endosymbiont under various experimental conditions in a simple culture system. Our results suggest that endosymbiont population size in P. bursaria was not regulated by active processes such as cell division coupling between the two organisms, or partitioning of the endosymbionts at host cell division. Regardless, endosymbiont population size was eventually adjusted to a nearly constant level once cells were grown with light and nutrients. To explain this apparent regulation of population size, we propose a simple mechanism based on the different growth properties (specifically the nutrient requirements) of the two organisms, and based from this develop a mathematical model to describe the population dynamics of host and endosymbiont. The proposed mechanism and model may provide a basis for understanding the maintenance of algal endosymbionts. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

[The reentrant binomial model of nuclear anomalies growth in rhabdomyosarcoma RA-23 cell populations under increasing doze of rare ionizing radiation].

PubMed

Alekseeva, N P; Alekseev, A O; Vakhtin, Iu B; Kravtsov, V Iu; Kuzovatov, S N; Skorikova, T I

2008-01-01

Distributions of nuclear morphology anomalies in transplantable rabdomiosarcoma RA-23 cell populations were investigated under effect of ionizing radiation from 0 to 45 Gy. Internuclear bridges, nuclear protrusions and dumbbell-shaped nuclei were accepted for morphological anomalies. Empirical distributions of the number of anomalies per 100 nuclei were used. The adequate model of reentrant binomial distribution has been found. The sum of binomial random variables with binomial number of summands has such distribution. Averages of these random variables were named, accordingly, internal and external average reentrant components. Their maximum likelihood estimations were received. Statistical properties of these estimations were investigated by means of statistical modeling. It has been received that at equally significant correlation between the radiation dose and the average of nuclear anomalies in cell populations after two-three cellular cycles from the moment of irradiation in vivo the irradiation doze significantly correlates with internal average reentrant component, and in remote descendants of cell transplants irradiated in vitro - with external one.

Linking macroscopic with microscopic neuroanatomy using synthetic neuronal populations.

PubMed

Schneider, Calvin J; Cuntz, Hermann; Soltesz, Ivan

2014-10-01

Dendritic morphology has been shown to have a dramatic impact on neuronal function. However, population features such as the inherent variability in dendritic morphology between cells belonging to the same neuronal type are often overlooked when studying computation in neural networks. While detailed models for morphology and electrophysiology exist for many types of single neurons, the role of detailed single cell morphology in the population has not been studied quantitatively or computationally. Here we use the structural context of the neural tissue in which dendritic trees exist to drive their generation in silico. We synthesize the entire population of dentate gyrus granule cells, the most numerous cell type in the hippocampus, by growing their dendritic trees within their characteristic dendritic fields bounded by the realistic structural context of (1) the granule cell layer that contains all somata and (2) the molecular layer that contains the dendritic forest. This process enables branching statistics to be linked to larger scale neuroanatomical features. We find large differences in dendritic total length and individual path length measures as a function of location in the dentate gyrus and of somatic depth in the granule cell layer. We also predict the number of unique granule cell dendrites invading a given volume in the molecular layer. This work enables the complete population-level study of morphological properties and provides a framework to develop complex and realistic neural network models.

Linking Macroscopic with Microscopic Neuroanatomy Using Synthetic Neuronal Populations

PubMed Central

Schneider, Calvin J.; Cuntz, Hermann; Soltesz, Ivan

2014-01-01

Dendritic morphology has been shown to have a dramatic impact on neuronal function. However, population features such as the inherent variability in dendritic morphology between cells belonging to the same neuronal type are often overlooked when studying computation in neural networks. While detailed models for morphology and electrophysiology exist for many types of single neurons, the role of detailed single cell morphology in the population has not been studied quantitatively or computationally. Here we use the structural context of the neural tissue in which dendritic trees exist to drive their generation in silico. We synthesize the entire population of dentate gyrus granule cells, the most numerous cell type in the hippocampus, by growing their dendritic trees within their characteristic dendritic fields bounded by the realistic structural context of (1) the granule cell layer that contains all somata and (2) the molecular layer that contains the dendritic forest. This process enables branching statistics to be linked to larger scale neuroanatomical features. We find large differences in dendritic total length and individual path length measures as a function of location in the dentate gyrus and of somatic depth in the granule cell layer. We also predict the number of unique granule cell dendrites invading a given volume in the molecular layer. This work enables the complete population-level study of morphological properties and provides a framework to develop complex and realistic neural network models. PMID:25340814

Cell adhesion heterogeneity reinforces tumour cell dissemination: novel insights from a mathematical model.

PubMed

Reher, David; Klink, Barbara; Deutsch, Andreas; Voss-Böhme, Anja

2017-08-11

Cancer cell invasion, dissemination, and metastasis have been linked to an epithelial-mesenchymal transition (EMT) of individual tumour cells. During EMT, adhesion molecules like E-cadherin are downregulated and the decrease of cell-cell adhesion allows tumour cells to dissociate from the primary tumour mass. This complex process depends on intracellular cues that are subject to genetic and epigenetic variability, as well as extrinsic cues from the local environment resulting in a spatial heterogeneity in the adhesive phenotype of individual tumour cells. Here, we use a novel mathematical model to study how adhesion heterogeneity, influenced by intrinsic and extrinsic factors, affects the dissemination of tumour cells from an epithelial cell population. The model is a multiscale cellular automaton that couples intracellular adhesion receptor regulation with cell-cell adhesion. Simulations of our mathematical model indicate profound effects of adhesion heterogeneity on tumour cell dissemination. In particular, we show that a large variation of intracellular adhesion receptor concentrations in a cell population reinforces cell dissemination, regardless of extrinsic cues mediated through the local cell density. However, additional control of adhesion receptor concentration through the local cell density, which can be assumed in healthy cells, weakens the effect. Furthermore, we provide evidence that adhesion heterogeneity can explain the remarkable differences in adhesion receptor concentrations of epithelial and mesenchymal phenotypes observed during EMT and might drive early dissemination of tumour cells. Our results suggest that adhesion heterogeneity may be a universal trigger to reinforce cell dissemination in epithelial cell populations. This effect can be at least partially compensated by a control of adhesion receptor regulation through neighbouring cells. Accordingly, our findings explain how both an increase in intra-tumour adhesion heterogeneity and the loss of control through the local environment can promote tumour cell dissemination. This article was reviewed by Hanspeter Herzel, Thomas Dandekar and Marek Kimmel.

Characterizing Human Stem Cell–derived Sensory Neurons at the Single-cell Level Reveals Their Ion Channel Expression and Utility in Pain Research

PubMed Central

Young, Gareth T; Gutteridge, Alex; Fox, Heather DE; Wilbrey, Anna L; Cao, Lishuang; Cho, Lily T; Brown, Adam R; Benn, Caroline L; Kammonen, Laura R; Friedman, Julia H; Bictash, Magda; Whiting, Paul; Bilsland, James G; Stevens, Edward B

2014-01-01

The generation of human sensory neurons by directed differentiation of pluripotent stem cells opens new opportunities for investigating the biology of pain. The inability to generate this cell type has meant that up until now their study has been reliant on the use of rodent models. Here, we use a combination of population and single-cell techniques to perform a detailed molecular, electrophysiological, and pharmacological phenotyping of sensory neurons derived from human embryonic stem cells. We describe the evolution of cell populations over 6 weeks of directed differentiation; a process that results in the generation of a largely homogeneous population of neurons that are both molecularly and functionally comparable to human sensory neurons derived from mature dorsal root ganglia. This work opens the prospect of using pluripotent stem-cell–derived sensory neurons to study human neuronal physiology and as in vitro models for drug discovery in pain and sensory disorders. PMID:24832007

Complexities and sequence similarities of mRNA populations of cholinergic (NS20-Y) and adrenergic (N1E-115) murine neuroblastoma cell lines.

PubMed

Strauss, W L

1990-07-01

The clonal murine neuroblastoma cell lines NS20-Y and N1E-115 have been proposed as models for examining the commitment of neural crest cells to either the cholinergic or adrenergic phenotype, respectively. The validity of this model depends in part on the extent to which these two cell lines have diverged as a result of their transformed, rather than neuronal properties. In order to quantitate differences in gene expression between NS20-Y and N1E-115 cells, the mRNA complexity of each cell type was determined. An analysis of the kinetics of hybridization of NS20-Y cell mRNA with cDNA prepared from NS20-Y cell mRNA demonstrated the presence of approximately 11,700 mRNA species assuming an average length of 1900 nucleotides. A similar analysis using mRNA isolated from N1E-115 cells and cDNA prepared from N1E-115 cell mRNA demonstrated that the adrenergic cell line expressed approximately 11,600 mRNA species. The species of mRNA expressed by each cell line were resolved into high, intermediate, and low abundance populations. In order to determine whether mRNAs were expressed by the cholinergic, but not by the adrenergic cell line, NS20-Y cDNA was hybridized to an excess of N1E-115 cell mRNA. An analysis of the solution hybridization kinetics from this procedure demonstrated that the two cell lines do not differ significantly in the nucleotide complexity of their mRNA populations. The extensive similarity between the two mRNA populations suggests that only a small number of genes are expressed differentially between the two cell lines and supports their use as models for the differentiation of cholinergic and adrenergic neurons.

Modelling the collective response of heterogeneous cell populations to stationary gradients and chemical signal relay

NASA Astrophysics Data System (ADS)

Pineda, M.; Eftimie, R.

2017-12-01

The directed motion of cell aggregates toward a chemical source occurs in many relevant biological processes. Understanding the mechanisms that control this complex behavior is of great relevance for our understanding of developmental biological processes and many diseases. In this paper, we consider a self-propelled particle model for the movement of heterogeneous subpopulations of chemically interacting cells towards an imposed stable chemical gradient. Our simulations show explicitly how self-organisation of cell populations (which could lead to engulfment or complete cell segregation) can arise from the heterogeneity of chemotactic responses alone. This new result complements current theoretical and experimental studies that emphasise the role of differential cell-cell adhesion on self-organisation and spatial structure of cellular aggregates. We also investigate how the speed of individual cell aggregations increases with the chemotactic sensitivity of the cells, and decreases with the number of cells inside the aggregates

Multi-scale modeling of the CD8 immune response

NASA Astrophysics Data System (ADS)

Barbarroux, Loic; Michel, Philippe; Adimy, Mostafa; Crauste, Fabien

2016-06-01

During the primary CD8 T-Cell immune response to an intracellular pathogen, CD8 T-Cells undergo exponential proliferation and continuous differentiation, acquiring cytotoxic capabilities to address the infection and memorize the corresponding antigen. After cleaning the organism, the only CD8 T-Cells left are antigen-specific memory cells whose role is to respond stronger and faster in case they are presented this very same antigen again. That is how vaccines work: a small quantity of a weakened pathogen is introduced in the organism to trigger the primary response, generating corresponding memory cells in the process, giving the organism a way to defend himself in case it encounters the same pathogen again. To investigate this process, we propose a non linear, multi-scale mathematical model of the CD8 T-Cells immune response due to vaccination using a maturity structured partial differential equation. At the intracellular scale, the level of expression of key proteins is modeled by a delay differential equation system, which gives the speeds of maturation for each cell. The population of cells is modeled by a maturity structured equation whose speeds are given by the intracellular model. We focus here on building the model, as well as its asymptotic study. Finally, we display numerical simulations showing the model can reproduce the biological dynamics of the cell population for both the primary response and the secondary responses.

Multi-scale modeling of the CD8 immune response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barbarroux, Loic, E-mail: loic.barbarroux@doctorant.ec-lyon.fr; Ecole Centrale de Lyon, 36 avenue Guy de Collongue, 69134 Ecully; Michel, Philippe, E-mail: philippe.michel@ec-lyon.fr

During the primary CD8 T-Cell immune response to an intracellular pathogen, CD8 T-Cells undergo exponential proliferation and continuous differentiation, acquiring cytotoxic capabilities to address the infection and memorize the corresponding antigen. After cleaning the organism, the only CD8 T-Cells left are antigen-specific memory cells whose role is to respond stronger and faster in case they are presented this very same antigen again. That is how vaccines work: a small quantity of a weakened pathogen is introduced in the organism to trigger the primary response, generating corresponding memory cells in the process, giving the organism a way to defend himself inmore » case it encounters the same pathogen again. To investigate this process, we propose a non linear, multi-scale mathematical model of the CD8 T-Cells immune response due to vaccination using a maturity structured partial differential equation. At the intracellular scale, the level of expression of key proteins is modeled by a delay differential equation system, which gives the speeds of maturation for each cell. The population of cells is modeled by a maturity structured equation whose speeds are given by the intracellular model. We focus here on building the model, as well as its asymptotic study. Finally, we display numerical simulations showing the model can reproduce the biological dynamics of the cell population for both the primary response and the secondary responses.« less

Agent-Based Phytoplankton Models of Cellular and Population Processes: Fostering Individual-Based Learning in Undergraduate Research

NASA Astrophysics Data System (ADS)

Berges, J. A.; Raphael, T.; Rafa Todd, C. S.; Bate, T. C.; Hellweger, F. L.

2016-02-01

Engaging undergraduate students in research projects that require expertise in multiple disciplines (e.g. cell biology, population ecology, and mathematical modeling) can be challenging because they have often not developed the expertise that allows them to participate at a satisfying level. Use of agent-based modeling can allow exploration of concepts at more intuitive levels, and encourage experimentation that emphasizes processes over computational skills. Over the past several years, we have involved undergraduate students in projects examining both ecological and cell biological aspects of aquatic microbial biology, using the freely-downloadable, agent-based modeling environment NetLogo (https://ccl.northwestern.edu/netlogo/). In Netlogo, actions of large numbers of individuals can be simulated, leading to complex systems with emergent behavior. The interface features appealing graphics, monitors, and control structures. In one example, a group of sophomores in a BioMathematics program developed an agent-based model of phytoplankton population dynamics in a pond ecosystem, motivated by observed macroscopic changes in cell numbers (due to growth and death), and driven by responses to irradiance, temperature and a limiting nutrient. In a second example, junior and senior undergraduates conducting Independent Studies created a model of the intracellular processes governing stress and cell death for individual phytoplankton cells (based on parameters derived from experiments using single-cell culturing and flow cytometry), and then this model was embedded in the agents in the pond ecosystem model. In our experience, students with a range of mathematical abilities learned to code quickly and could use the software with varying degrees of sophistication, for example, creation of spatially-explicit two and three-dimensional models. Skills developed quickly and transferred readily to other platforms (e.g. Matlab).

Population balance modeling: current status and future prospects.

PubMed

Ramkrishna, Doraiswami; Singh, Meenesh R

2014-01-01

Population balance modeling is undergoing phenomenal growth in its applications, and this growth is accompanied by multifarious reviews. This review aims to fortify the model's fundamental base, as well as point to a variety of new applications, including modeling of crystal morphology, cell growth and differentiation, gene regulatory processes, and transfer of drug resistance. This is accomplished by presenting the many faces of population balance equations that arise in the foregoing applications.

Exploring bacterial infections: theoretical and experimental studies of the bacterial population dynamics and antibiotic treatment

NASA Astrophysics Data System (ADS)

Shao, Xinxian

Bacterial infections are very common in human society. Thus extensive research has been conducted to reveal the molecular mechanisms of the pathogenesis and to evaluate the antibiotics' efficacy against bacteria. Little is known, however, about the population dynamics of bacterial populations and their interactions with the host's immune system. In this dissertation, a stochatic model is developed featuring stochastic phenotypic switching of bacterial individuals to explain the single-variant bottleneck discovered in multi strain bacterial infections. I explored early events in a bacterial infection establishment using classical experiments of Moxon and Murphy on neonatal rats. I showed that the minimal model and its simple variants do not work. I proposed modifications to the model that could explain the data quantitatively. The bacterial infections are also commonly established in physical structures, as biofilms or 3-d colonies. In contrast, most research on antibiotic treatment of bacterial infections has been conducted in well-mixed liquid cultures. I explored the efficacy of antibiotics to treat such bacterial colonies, a broadly applicable method is designed and evaluated where discrete bacterial colonies on 2-d surfaces were exposed to antibiotics. I discuss possible explanations and hypotheses for the experimental results. To verify these hypotheses, we investigated the dynamics of bacterial population as 3-d colonies. We showed that a minimal mathematical model of bacterial colony growth in 3-d was able to account for the experimentally observed presence of a diffusion-limited regime. The model further revealed highly loose packing of the cells in 3-d colonies and smaller cell sizes in colonies than plancktonic cells in corresponding liquid culture. Further experimental tests of the model predictions have revealed that the ratio of the cell size in liquid culture to that in colony cultures was consistent with the model prediction, that the dead cells emerged randomly in a colony, and that the cells packed heterogeneously in the outer part of a colony, possibly explaining the loose packing.

Toward understanding of the role of reversibility of phenotypic switching in the evolution of resistance to therapy

NASA Astrophysics Data System (ADS)

Horvath, D.; Brutovsky, B.

2018-06-01

Reversibility of state transitions is intensively studied topic in many scientific disciplines over many years. In cell biology, it plays an important role in epigenetic variation of phenotypes, known as phenotypic plasticity. More interestingly, the cell state reversibility is probably crucial in the adaptation of population phenotypic heterogeneity to environmental fluctuations by evolving bet-hedging strategy, which might confer to cancer cells resistance to therapy. In this article, we propose a formalization of the evolution of highly reversible states in the environments of periodic variability. Two interrelated models of heterogeneous cell populations are proposed and their behavior is studied. The first model captures selection dynamics of the cell clones for the respective levels of phenotypic reversibility. The second model focuses on the interplay between reversibility and drug resistance in the particular case of cancer. Overall, our results show that the threshold dependencies are emergent features of the investigated model with eventual therapeutic relevance. Presented examples demonstrate importance of taking into account cell to cell heterogeneity within a system of clones with different reversibility quantified by appropriately chosen genetic and epigenetic entropy measures.

CD133+ tumor initiating cells in a syngenic murine model of pancreatic cancer respond to Minnelide.

PubMed

Banerjee, Sulagna; Nomura, Alice; Sangwan, Veena; Chugh, Rohit; Dudeja, Vikas; Vickers, Selwyn M; Saluja, Ashok

2014-05-01

Pancreatic adenocarcinoma is the fourth leading cause for cancer-related mortality with a survival rate of less than 5%. Late diagnosis and lack of effective chemotherapeutic regimen contribute to these grim survival statistics. Relapse of any tumor is largely attributed to the presence of tumor-initiating cells (TIC) or cancer stem cells (CSC). These cells are considered as hurdles to cancer therapy as no known chemotherapeutic compound is reported to target them. Thus, there is an urgent need to develop a TIC-targeted therapy for pancreatic cancer. We isolated CD133(+) cells from a spontaneous pancreatic ductal adenocarcinoma mouse model and studied both surface expression, molecular markers of pancreatic TICs. We also studied tumor initiation properties by implanting low numbers of CD133(+) cells in immune competent mice. Effect of Minnelide, a drug currently under phase I clinical trial, was studied on the tumors derived from the CD133(+) cells. Our study showed for the first time that CD133(+) population demonstrated all the molecular markers for pancreatic TIC. These cells initiated tumors in immunocompetent mouse models and showed increased expression of prosurvival and proinvasive proteins compared to the CD133(-) non-TIC population. Our study further showed that Minnelide was very efficient in downregulating both CD133(-) and CD133(+) population in the tumors, resulting in a 60% decrease in tumor volume compared with the untreated ones. As Minnelide is currently under phase I clinical trial, its evaluation in reducing tumor burden by decreasing TIC as well as non-TIC population suggests its potential as an effective therapy. ©2014 AACR.

Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry.

PubMed

García, Míriam R; Vázquez, José A; Teixeira, Isabel G; Alonso, Antonio A

2017-01-01

A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modeling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behavior of bacteria inside populations. In this work, we overcome this problem by estimating the individual behavior of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modeling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modeling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modeling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that P. acidilactici divide into two successive parallel planes.

Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data.

PubMed

Pyne, Saumyadipta; Lee, Sharon X; Wang, Kui; Irish, Jonathan; Tamayo, Pablo; Nazaire, Marc-Danie; Duong, Tarn; Ng, Shu-Kay; Hafler, David; Levy, Ronald; Nolan, Garry P; Mesirov, Jill; McLachlan, Geoffrey J

2014-01-01

In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template--used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts. Software for fitting the JCM models have been implemented in an R package EMMIX-JCM, available from http://www.maths.uq.edu.au/~gjm/mix_soft/EMMIX-JCM/.

An Empirically Calibrated Model of Cell Fate Decision Following Viral Infection

NASA Astrophysics Data System (ADS)

Coleman, Seth; Igoshin, Oleg; Golding, Ido

The life cycle of the virus (phage) lambda is an established paradigm for the way genetic networks drive cell fate decisions. But despite decades of interrogation, we are still unable to theoretically predict whether the infection of a given cell will result in cell death or viral dormancy. The poor predictive power of current models reflects the absence of quantitative experimental data describing the regulatory interactions between different lambda genes. To address this gap, we are constructing a theoretical model that captures the known interactions in the lambda network. Model assumptions and parameters are calibrated using new single-cell data from our lab, describing the activity of lambda genes at single-molecule resolution. We began with a mean-field model, aimed at exploring the population averaged gene-expression trajectories under different initial conditions. Next, we will develop a stochastic formulation, to capture the differences between individual cells within the population. The eventual goal is to identify how the post-infection decision is driven by the interplay between network topology, initial conditions, and stochastic effects. The insights gained here will inform our understanding of cell fate choices in more complex cellular systems.

Development of a population of cancer cells: Observation and modeling by a Mixed Spatial Evolutionary Games approach.

PubMed

Świerniak, Andrzej; Krześlak, Michał; Student, Sebastian; Rzeszowska-Wolny, Joanna

2016-09-21

Living cells, like whole living organisms during evolution, communicate with their neighbors, interact with the environment, divide, change their phenotypes, and eventually die. The development of specific ways of communication (through signaling molecules and receptors) allows some cellular subpopulations to survive better, to coordinate their physiological status, and during embryonal development to create tissues and organs or in some conditions to become tumors. Populations of cells cultured in vitro interact similarly, also competing for space and nutrients and stimulating each other to better survive or to die. The results of these intercellular interactions of different types seem to be good examples of biological evolutionary games, and have been the subjects of simulations by the methods of evolutionary game theory where individual cells are treated as players. Here we present examples of intercellular contacts in a population of living human cancer HeLa cells cultured in vitro and propose an evolutionary game theory approach to model the development of such populations. We propose a new technique termed Mixed Spatial Evolutionary Games (MSEG) which are played on multiple lattices corresponding to the possible cellular phenotypes which gives the possibility of simulating and investigating the effects of heterogeneity at the cellular level in addition to the population level. Analyses performed with MSEG suggested different ways in which cellular populations develop in the case of cells communicating directly and through factors released to the environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Incorporating pushing in exclusion-process models of cell migration.

PubMed

Yates, Christian A; Parker, Andrew; Baker, Ruth E

2015-05-01

The macroscale movement behavior of a wide range of isolated migrating cells has been well characterized experimentally. Recently, attention has turned to understanding the behavior of cells in crowded environments. In such scenarios it is possible for cells to interact, inducing neighboring cells to move in order to make room for their own movements or progeny. Although the behavior of interacting cells has been modeled extensively through volume-exclusion processes, few models, thus far, have explicitly accounted for the ability of cells to actively displace each other in order to create space for themselves. In this work we consider both on- and off-lattice volume-exclusion position-jump processes in which cells are explicitly allowed to induce movements in their near neighbors in order to create space for themselves to move or proliferate into. We refer to this behavior as pushing. From these simple individual-level representations we derive continuum partial differential equations for the average occupancy of the domain. We find that, for limited amounts of pushing, comparison between the averaged individual-level simulations and the population-level model is nearly as good as in the scenario without pushing. Interestingly, we find that, in the on-lattice case, the diffusion coefficient of the population-level model is increased by pushing, whereas, for the particular off-lattice model that we investigate, the diffusion coefficient is reduced. We conclude, therefore, that it is important to consider carefully the appropriate individual-level model to use when representing complex cell-cell interactions such as pushing.

Independent components of neural activity carry information on individual populations.

PubMed

Głąbska, Helena; Potworowski, Jan; Łęski, Szymon; Wójcik, Daniel K

2014-01-01

Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges.

Independent Components of Neural Activity Carry Information on Individual Populations

PubMed Central

Głąbska, Helena; Potworowski, Jan; Łęski, Szymon; Wójcik, Daniel K.

2014-01-01

Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges. PMID:25153730

Entropy, Ergodicity, and Stem Cell Multipotency

NASA Astrophysics Data System (ADS)

Ridden, Sonya J.; Chang, Hannah H.; Zygalakis, Konstantinos C.; MacArthur, Ben D.

2015-11-01

Populations of mammalian stem cells commonly exhibit considerable cell-cell variability. However, the functional role of this diversity is unclear. Here, we analyze expression fluctuations of the stem cell surface marker Sca1 in mouse hematopoietic progenitor cells using a simple stochastic model and find that the observed dynamics naturally lie close to a critical state, thereby producing a diverse population that is able to respond rapidly to environmental changes. We propose an information-theoretic interpretation of these results that views cellular multipotency as an instance of maximum entropy statistical inference.

Digital Image Analysis of Yeast Single Cells Growing in Two Different Oxygen Concentrations to Analyze the Population Growth and to Assist Individual-Based Modeling.

PubMed

Ginovart, Marta; Carbó, Rosa; Blanco, Mónica; Portell, Xavier

2017-01-01

Nowadays control of the growth of Saccharomyces to obtain biomass or cellular wall components is crucial for specific industrial applications. The general aim of this contribution is to deal with experimental data obtained from yeast cells and from yeast cultures to attempt the integration of the two levels of information, individual and population, to progress in the control of yeast biotechnological processes by means of the overall analysis of this set of experimental data, and to assist in the improvement of an individual-based model, namely, INDISIM- Saccha . Populations of S. cerevisiae growing in liquid batch culture, in aerobic and microaerophilic conditions, were studied. A set of digital images was taken during the population growth, and a protocol for the treatment and analyses of the images obtained was established. The piecewise linear model of Buchanan was adjusted to the temporal evolutions of the yeast populations to determine the kinetic parameters and changes of growth phases. In parallel, for all the yeast cells analyzed, values of direct morphological parameters, such as area, perimeter, major diameter, minor diameter, and derived ones, such as circularity and elongation, were obtained. Graphical and numerical methods from descriptive statistics were applied to these data to characterize the growth phases and the budding state of the yeast cells in both experimental conditions, and inferential statistical methods were used to compare the diverse groups of data achieved. Oxidative metabolism of yeast in a medium with oxygen available and low initial sugar concentration can be taken into account in order to obtain a greater number of cells or larger cells. Morphological parameters were analyzed statistically to identify which were the most useful for the discrimination of the different states, according to budding and/or growth phase, in aerobic and microaerophilic conditions. The use of the experimental data for subsequent modeling work was then discussed and compared to simulation results generated with INDISIM- Saccha , which allowed us to advance in the development of this yeast model, and illustrated the utility of data at different levels of observation and the needs and logic behind the development of a microbial individual-based model.

Distribution of chaos and periodic spikes in a three-cell population model of cancer. Auto-organization of oscillatory phases in parameter planes

NASA Astrophysics Data System (ADS)

Gallas, Michelle R.; Gallas, Marcia R.; Gallas, Jason A. C.

2014-10-01

We study complex oscillations generated by the de Pillis-Radunskaya model of cancer growth, a model including interactions between tumor cells, healthy cells, and activated immune system cells. We report a wide-ranging systematic numerical classification of the oscillatory states and of their relative abundance. The dynamical states of the cell populations are characterized here by two independent and complementary types of stability diagrams: Lyapunov and isospike diagrams. The model is found to display stability phases organized regularly in old and new ways: Apart from the familiar spirals of stability, it displays exceptionally long zig-zag networks and intermixed cascades of two- and three-doubling flanked stability islands previously detected only in feedback systems with delay. In addition, we also characterize the interplay between continuous spike-adding and spike-doubling mechanisms responsible for the unbounded complexification of periodic wave patterns. This article is dedicated to Prof. Hans Jürgen Herrmann on the occasion of his 60th birthday.

Generators of the brainstem auditory evoked potential in cat. III: Identified cell populations.

PubMed

Melcher, J R; Kiang, N Y

1996-04-01

This paper examines the relationship between different brainstem cell populations and the brainstem auditory evoked potential (BAEP). First, we present a mathematical model relating the BAEP to underlying cellular activity. Then, we identify specific cellular generators of the click-evoked BAEP in cats by combining model-derived insights with key experimental data. These data include (a) a correspondence between particular brainstem regions and specific extrema in the BAEP waveform, determined from lesion experiments, and (b) values for model parameters derived from published physiological and anatomical information. Ultimately, we conclude (with varying degrees of confidence) that: (1) the earliest extrema in the BAEP are generated by spiral ganglion cells, (2) P2 is mainly generated by cochlear nucleus (CN) globular cells, (3) P3 is partly generated by CN spherical cells and partly by cells receiving inputs from globular cells, (4) P4 is predominantly generated by medial superior olive (MSO) principal cells, which are driven by spherical cells, (5) the generators of P5 are driven by MSO principal cells, and (6) the BAEP, as a whole, is generated mainly by cells with characteristic frequencies above 2 kHz. Thus, the BAEP in cats mainly reflects cellular activity in two parallel pathways, one originating with globular cells and the other with spherical cells. Since the globular cell pathway is poorly represented in humans, we suggest that the human BAEP is largely generated by brainstem cells in the spherical cell pathway. Given our conclusions, it should now be possible to relate activity in specific cell populations to psychophysical performance since the BAEP can be recorded in behaving humans and animals.

Computational and experimental single cell biology techniques for the definition of cell type heterogeneity, interplay and intracellular dynamics.

PubMed

de Vargas Roditi, Laura; Claassen, Manfred

2015-08-01

Novel technological developments enable single cell population profiling with respect to their spatial and molecular setup. These include single cell sequencing, flow cytometry and multiparametric imaging approaches and open unprecedented possibilities to learn about the heterogeneity, dynamics and interplay of the different cell types which constitute tissues and multicellular organisms. Statistical and dynamic systems theory approaches have been applied to quantitatively describe a variety of cellular processes, such as transcription and cell signaling. Machine learning approaches have been developed to define cell types, their mutual relationships, and differentiation hierarchies shaping heterogeneous cell populations, yielding insights into topics such as, for example, immune cell differentiation and tumor cell type composition. This combination of experimental and computational advances has opened perspectives towards learning predictive multi-scale models of heterogeneous cell populations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cancer stem cell-like population is preferentially suppressed by EGFR-TKIs in EGFR-mutated PC-9 tumor models.

PubMed

Yang, Fan; Li, Yang; Liu, Bin; You, Jiacong; Zhou, Qinghua

2018-01-01

Although the epidermal growth factor receptor (EGFR) and Wnt/β-catenin signaling systems synergistically regulate many essential developmental and regenerative processes in lung cancer, the mechanisms of their crosstalk remain poorly defined. Our study aimed to investigate an interaction between EGFR and the β-catenin signal. In this study, we described a potent activation of β-catenin by EGFR, which is dependent of the PtdIns3K/AKT pathway. We found EGF activated β-catenin signaling via phosphorylation of EGFR and AKT in EGFR-mutated PC-9 lung cancer cells. Meanwhile, EGFR tyrosine kinase inhibitors (EGFR-TKIs) regulated cancer stem-like cells (CSCs) by inhibiting autophosphorylation of EGFR and downstream signaling proteins, as well as β-catenin. Further, β-catenin depletion by RNA interference virtually eliminated cancer stem cell-like population in PC-9 cells in vitro. The nude mice transplantation model was also performed to confirm EGFR-TKIs strongly inhibited the β-catenin signal and decreased CSCs. Importantly, the reduction of CSCs that sorted out by side population (SP) cells significantly reduced the migration capability. Thus, our results improved the understanding of this process to provide insights into mechanisms of responding to EGFR-TKIs. Our discoveries raise an intriguing question of the role of β-catenin in EGFR-TKIs-treated cancer stem cell-like population(s) and its potential as a new therapeutic target for NSCLC in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

Retention of Ag-specific memory CD4+ T cells in the draining lymph node indicates lymphoid tissue resident memory populations.

PubMed

Marriott, Clare L; Dutton, Emma E; Tomura, Michio; Withers, David R

2017-05-01

Several different memory T-cell populations have now been described based upon surface receptor expression and migratory capabilities. Here we have assessed murine endogenous memory CD4 + T cells generated within a draining lymph node and their subsequent migration to other secondary lymphoid tissues. Having established a model response targeting a specific peripheral lymph node, we temporally labelled all the cells within draining lymph node using photoconversion. Tracking of photoconverted and non-photoconverted Ag-specific CD4 + T cells revealed the rapid establishment of a circulating memory population in all lymph nodes within days of immunisation. Strikingly, a resident memory CD4 + T cell population became established in the draining lymph node and persisted for several months in the absence of detectable migration to other lymphoid tissue. These cells most closely resembled effector memory T cells, usually associated with circulation through non-lymphoid tissue, but here, these cells were retained in the draining lymph node. These data indicate that lymphoid tissue resident memory CD4 + T-cell populations are generated in peripheral lymph nodes following immunisation. © 2017 The Authors. European Journal of Immunology published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large scale spontaneous synchronization of cell cycles in amoebae

NASA Astrophysics Data System (ADS)

Segota, Igor; Boulet, Laurent; Franck, Carl

2014-03-01

Unicellular eukaryotic amoebae Dictyostelium discoideum are generally believed to grow in their vegetative state as single cells until starvation, when their collective aspect emerges and they differentiate to form a multicellular slime mold. While major efforts continue to be aimed at their starvation-induced social aspect, our understanding of population dynamics and cell cycle in the vegetative growth phase has remained incomplete. We show that substrate-growtn cell populations spontaneously synchronize their cell cycles within several hours. These collective population-wide cell cycle oscillations span millimeter length scales and can be completely suppressed by washing away putative cell-secreted signals, implying signaling by means of a diffusible growth factor or mitogen. These observations give strong evidence for collective proliferation behavior in the vegetative state and provide opportunities for synchronization theories beyond classic Kuramoto models.

What to Do about Zero Frequency Cells when Estimating Polychoric Correlations

ERIC Educational Resources Information Center

Savalei, Victoria

2011-01-01

Categorical structural equation modeling (SEM) methods that fit the model to estimated polychoric correlations have become popular in the social sciences. When population thresholds are high in absolute value, contingency tables in small samples are likely to contain zero frequency cells. Such cells make the estimation of the polychoric…

Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations

PubMed Central

Schreiber, Frank; Dal Co, Alma; Kiviet, Daniel J.; Littmann, Sten

2017-01-01

While we have good understanding of bacterial metabolism at the population level, we know little about the metabolic behavior of individual cells: do single cells in clonal populations sometimes specialize on different metabolic pathways? Such metabolic specialization could be driven by stochastic gene expression and could provide individual cells with growth benefits of specialization. We measured the degree of phenotypic specialization in two parallel metabolic pathways, the assimilation of glucose and arabinose. We grew Escherichia coli in chemostats, and used isotope-labeled sugars in combination with nanometer-scale secondary ion mass spectrometry and mathematical modeling to quantify sugar assimilation at the single-cell level. We found large variation in metabolic activities between single cells, both in absolute assimilation and in the degree to which individual cells specialize in the assimilation of different sugars. Analysis of transcriptional reporters indicated that this variation was at least partially based on cell-to-cell variation in gene expression. Metabolic differences between cells in clonal populations could potentially reduce metabolic incompatibilities between different pathways, and increase the rate at which parallel reactions can be performed. PMID:29253903

Assessing the role of spatial correlations during collective cell spreading

PubMed Central

Treloar, Katrina K.; Simpson, Matthew J.; Binder, Benjamin J.; McElwain, D. L. Sean; Baker, Ruth E.

2014-01-01

Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher's equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations. PMID:25026987

Population genetics inside a cell: Mutations and mitochondrial genome maintenance

NASA Astrophysics Data System (ADS)

Goyal, Sidhartha; Shraiman, Boris; Gottschling, Dan

2012-02-01

In realistic ecological and evolutionary systems natural selection acts on multiple levels, i.e. it acts on individuals as well as on collection of individuals. An understanding of evolutionary dynamics of such systems is limited in large part due to the lack of experimental systems that can challenge theoretical models. Mitochondrial genomes (mtDNA) are subjected to selection acting on cellular as well as organelle levels. It is well accepted that mtDNA in yeast Saccharomyces cerevisiae is unstable and can degrade over time scales comparable to yeast cell division time. We utilize a recent technology designed in Gottschling lab to extract DNA from populations of aged yeast cells and deep sequencing to characterize mtDNA variation in a population of young and old cells. In tandem, we developed a stochastic model that includes the essential features of mitochondrial biology that provides a null model for expected mtDNA variation. Overall, we find approximately 2% of the polymorphic loci that show significant increase in frequency as cells age providing direct evidence for organelle level selection. Such quantitative study of mtDNA dynamics is absolutely essential to understand the propagation of mtDNA mutations linked to a spectrum of age-related diseases in humans.

Using state variables to model the response of tumour cells to radiation and heat: a novel multi-hit-repair approach.

PubMed

Scheidegger, Stephan; Fuchs, Hans U; Zaugg, Kathrin; Bodis, Stephan; Füchslin, Rudolf M

2013-01-01

In order to overcome the limitations of the linear-quadratic model and include synergistic effects of heat and radiation, a novel radiobiological model is proposed. The model is based on a chain of cell populations which are characterized by the number of radiation induced damages (hits). Cells can shift downward along the chain by collecting hits and upward by a repair process. The repair process is governed by a repair probability which depends upon state variables used for a simplistic description of the impact of heat and radiation upon repair proteins. Based on the parameters used, populations up to 4-5 hits are relevant for the calculation of the survival. The model describes intuitively the mathematical behaviour of apoptotic and nonapoptotic cell death. Linear-quadratic-linear behaviour of the logarithmic cell survival, fractionation, and (with one exception) the dose rate dependencies are described correctly. The model covers the time gap dependence of the synergistic cell killing due to combined application of heat and radiation, but further validation of the proposed approach based on experimental data is needed. However, the model offers a work bench for testing different biological concepts of damage induction, repair, and statistical approaches for calculating the variables of state.

A mathematical model for late term cancer chemotherapy

NASA Astrophysics Data System (ADS)

Izard, Zac; Hirschbeck, Sarah; Volk, Christian; Shojania Feizabadi, Mitra

2006-03-01

A mathematical model for cancer treated with the ``on-off'' type where the drug is either active or inactive and when the chemotherapeutic treatment only affects the cycling cells is presented. This model is considered for late term chemotherapy when the total population of cells doesn't show a significant change. The size of the cycling cells as a function of time has been investigated.

A mechanistic model for bromodeoxyuridine dilution naturally explains labelling data of self-renewing T cell populations

PubMed Central

Ganusov, Vitaly V.; De Boer, Rob J.

2013-01-01

Bromodeoxyuridine (BrdU) is widely used in immunology to detect cell division, and several mathematical models have been proposed to estimate proliferation and death rates of lymphocytes from BrdU labelling and de-labelling curves. One problem in interpreting BrdU data is explaining the de-labelling curves. Because shortly after label withdrawal, BrdU+ cells are expected to divide into BrdU+ daughter cells, one would expect a flat down-slope. As for many cell types, the fraction of BrdU+ cells decreases during de-labelling, previous mathematical models had to make debatable assumptions to be able to account for the data. We develop a mechanistic model tracking the number of divisions that each cell has undergone in the presence and absence of BrdU, and allow cells to accumulate and dilute their BrdU content. From the same mechanistic model, one can naturally derive expressions for the mean BrdU content (MBC) of all cells, or the MBC of the BrdU+ subset, which is related to the mean fluorescence intensity of BrdU that can be measured in experiments. The model is extended to include subpopulations with different rates of division and death (i.e. kinetic heterogeneity). We fit the extended model to previously published BrdU data from memory T lymphocytes in simian immunodeficiency virus-infected and uninfected macaques, and find that the model describes the data with at least the same quality as previous models. Because the same model predicts a modest decline in the MBC of BrdU+ cells, which is consistent with experimental observations, BrdU dilution seems a natural explanation for the observed down-slopes in self-renewing populations. PMID:23034350

On the probability of cure for heavy-ion radiotherapy

NASA Astrophysics Data System (ADS)

Hanin, Leonid; Zaider, Marco

2014-07-01

The probability of a cure in radiation therapy (RT)—viewed as the probability of eventual extinction of all cancer cells—is unobservable, and the only way to compute it is through modeling the dynamics of cancer cell population during and post-treatment. The conundrum at the heart of biophysical models aimed at such prospective calculations is the absence of information on the initial size of the subpopulation of clonogenic cancer cells (also called stem-like cancer cells), that largely determines the outcome of RT, both in an individual and population settings. Other relevant parameters (e.g. potential doubling time, cell loss factor and survival probability as a function of dose) are, at least in principle, amenable to empirical determination. In this article we demonstrate that, for heavy-ion RT, microdosimetric considerations (justifiably ignored in conventional RT) combined with an expression for the clone extinction probability obtained from a mechanistic model of radiation cell survival lead to useful upper bounds on the size of the pre-treatment population of clonogenic cancer cells as well as upper and lower bounds on the cure probability. The main practical impact of these limiting values is the ability to make predictions about the probability of a cure for a given population of patients treated to newer, still unexplored treatment modalities from the empirically determined probability of a cure for the same or similar population resulting from conventional low linear energy transfer (typically photon/electron) RT. We also propose that the current trend to deliver a lower total dose in a smaller number of fractions with larger-than-conventional doses per fraction has physical limits that must be understood before embarking on a particular treatment schedule.

Dispersal leads to spatial autocorrelation in species distributions: A simulation model

USGS Publications Warehouse

Bahn, V.; Krohn, W.B.; O'Connor, R.J.

2008-01-01

Compared to population growth regulated by local conditions, dispersal has been underappreciated as a central process shaping the spatial distribution of populations. This paper asks: (a) which conditions increase the importance of dispersers relative to local recruits in determining population sizes? and (b) how does dispersal influence the spatial distribution patterns of abundances among connected populations? We approached these questions with a simulation model of populations on a coupled lattice with cells of continuously varying habitat quality expressed as carrying capacities. Each cell contained a population with the basic dynamics of density-regulated growth, and was connected to other populations by immigration and emigration. The degree to which dispersal influenced the distribution of population sizes depended most strongly on the absolute amount of dispersal, and then on the potential population growth rate. Dispersal decaying in intensity with distance left close neighbours more alike in population size than distant populations, leading to an increase in spatial autocorrelation. The spatial distribution of species with low potential growth rates is more dependent on dispersal than that of species with high growth rates; therefore, distribution modelling for species with low growth rates requires particular attention to autocorrelation, and conservation management of these species requires attention to factors curtailing dispersal, such as fragmentation and dispersal barriers. ?? 2007 Elsevier B.V. All rights reserved.

Fluctuations of cell population in a colonic crypt

NASA Astrophysics Data System (ADS)

Pei, Qi-ming; Zhan, Xuan; Yang, Li-jian; Bao, Chun; Cao, Wei; Li, An-bang; Rozi, Anvar; Jia, Ya

2014-03-01

The number of stem cells in a colonic crypt is often very small, which leads to large intrinsic fluctuations in the cell population. Based on the model of cell population dynamics with linear feedback in a colonic crypt, we present a stochastic dynamics of the cell population [including stem cells (SCs), transit amplifying cells (TACs), and fully differentiated cells (FDCs)]. The Fano factor, covariance, and susceptibility formulas of the cell population around the steady state are derived by using the Langevin theory. In the range of physiologically reasonable parameter values, it is found that the stationary populations of TACs and FDCs exhibit an approximately threshold behavior as a function of the net growth rate of TACs, and the reproductions of TACs and FDCs can be classified into three regimens: controlled, crossover, and uncontrolled. With the increasing of the net growth rate of TACs, there is a maximum of the relative intrinsic fluctuations (i.e., the Fano factors) of TACs and FDCs in the crossover region. For a fixed differentiation rate and the net growth rate of SCs, the covariance of fluctuations between SCs and TACs has a maximum in the crossover region. However, the susceptibilities of both TACs and FDCs to the net growth rate of TACs have a minimum in the crossover region.

Examples of Mathematical Modeling

PubMed Central

Johnston, Matthew D.; Edwards, Carina M.; Bodmer, Walter F.; Maini, Philip K.; Chapman, S. Jonathan

2008-01-01

Mathematical modeling is being increasingly recognized within the biomedical sciences as an important tool that can aid the understanding of biological systems. The heavily regulated cell renewal cycle in the colonic crypt provides a good example of how modeling can be used to find out key features of the system kinetics, and help to explain both the breakdown of homeostasis and the initiation of tumorigenesis. We use the cell population model by Johnston et al.5 to illustrate the power of mathematical modeling by considering two key questions about the cell population dynamics in the colonic crypt. We ask: how can a model describe both homeostasis and unregulated growth in tumorigenesis; and to which parameters in the system is the model most sensitive? In order to address these questions, we discuss what type of modeling approach is most appropriate in the crypt. We use the model to argue why tumorigenesis is observed to occur in stages with long lag phases between periods of rapid growth, and we identify the key parameters. PMID:17873520

Cancer dormancy and criticality from a game theory perspective.

PubMed

Wu, Amy; Liao, David; Kirilin, Vlamimir; Lin, Ke-Chih; Torga, Gonzalo; Qu, Junle; Liu, Liyu; Sturm, James C; Pienta, Kenneth; Austin, Robert

2018-01-01

The physics of cancer dormancy, the time between initial cancer treatment and re-emergence after a protracted period, is a puzzle. Cancer cells interact with host cells via complex, non-linear population dynamics, which can lead to very non-intuitive but perhaps deterministic and understandable progression dynamics of cancer and dormancy. We explore here the dynamics of host-cancer cell populations in the presence of (1) payoffs gradients and (2) perturbations due to cell migration. We determine to what extent the time-dependence of the populations can be quantitively understood in spite of the underlying complexity of the individual agents and model the phenomena of dormancy.

Growth of bacteria in 3-d colonies

PubMed Central

Mugler, Andrew; Kim, Justin

2017-01-01

The dynamics of growth of bacterial populations has been extensively studied for planktonic cells in well-agitated liquid culture, in which all cells have equal access to nutrients. In the real world, bacteria are more likely to live in physically structured habitats as colonies, within which individual cells vary in their access to nutrients. The dynamics of bacterial growth in such conditions is poorly understood, and, unlike that for liquid culture, there is not a standard broadly used mathematical model for bacterial populations growing in colonies in three dimensions (3-d). By extending the classic Monod model of resource-limited population growth to allow for spatial heterogeneity in the bacterial access to nutrients, we develop a 3-d model of colonies, in which bacteria consume diffusing nutrients in their vicinity. By following the changes in density of E. coli in liquid and embedded in glucose-limited soft agar, we evaluate the fit of this model to experimental data. The model accounts for the experimentally observed presence of a sub-exponential, diffusion-limited growth regime in colonies, which is absent in liquid cultures. The model predicts and our experiments confirm that, as a consequence of inter-colony competition for the diffusing nutrients and of cell death, there is a non-monotonic relationship between total number of colonies within the habitat and the total number of individual cells in all of these colonies. This combined theoretical-experimental study reveals that, within 3-d colonies, E. coli cells are loosely packed, and colonies produce about 2.5 times as many cells as the liquid culture from the same amount of nutrients. We verify that this is because cells in liquid culture are larger than in colonies. Our model provides a baseline description of bacterial growth in 3-d, deviations from which can be used to identify phenotypic heterogeneities and inter-cellular interactions that further contribute to the structure of bacterial communities. PMID:28749935

Dynamics of morphological evolution in experimental Escherichia coli populations.

PubMed

Cui, F; Yuan, B

2016-08-30

Here, we applied a two-stage clonal expansion model of morphological (cell-size) evolution to a long-term evolution experiment with Escherichia coli. Using this model, we derived the incidence function of the appearance of cell-size stability, the waiting time until this morphological stability, and the conditional and unconditional probabilities of morphological stability. After assessing the parameter values, we verified that the calculated waiting time was consistent with the experimental results, demonstrating the effectiveness of the two-stage model. According to the relative contributions of parameters to the incidence function and the waiting time, cell-size evolution is largely determined by the promotion rate, i.e., the clonal expansion rate of selectively advantageous organisms. This rate plays a prominent role in the evolution of cell size in experimental populations, whereas all other evolutionary forces were found to be less influential.

Synchronization of glycolytic oscillations in a yeast cell population.

PubMed

Danø, S; Hynne, F; De Monte, S; d'Ovidio, F; Sørensen, P G; Westerhoff, H

2001-01-01

The mechanism of active phase synchronization in a suspension of oscillatory yeast cells has remained a puzzle for almost half a century. The difficulty of the problem stems from the fact that the synchronization phenomenon involves the entire metabolic network of glycolysis and fermentation, and consequently it cannot be addressed at the level of a single enzyme or a single chemical species. In this paper it is shown how this system in a CSTR (continuous flow stirred tank reactor) can be modelled quantitatively as a population of Stuart-Landau oscillators interacting by exchange of metabolites through the extracellular medium, thus reducing the complexity of the problem without sacrificing the biochemical realism. The parameters of the model can be derived by a systematic expansion from any full-scale model of the yeast cell kinetics with a supercritical Hopf bifurcation. Some parameter values can also be obtained directly from analysis of perturbation experiments. In the mean-field limit, equations for the study of populations having a distribution of frequencies are used to simulate the effect of the inherent variations between cells.

Efficient coarse simulation of a growing avascular tumor

PubMed Central

Kavousanakis, Michail E.; Liu, Ping; Boudouvis, Andreas G.; Lowengrub, John; Kevrekidis, Ioannis G.

2013-01-01

The subject of this work is the development and implementation of algorithms which accelerate the simulation of early stage tumor growth models. Among the different computational approaches used for the simulation of tumor progression, discrete stochastic models (e.g., cellular automata) have been widely used to describe processes occurring at the cell and subcell scales (e.g., cell-cell interactions and signaling processes). To describe macroscopic characteristics (e.g., morphology) of growing tumors, large numbers of interacting cells must be simulated. However, the high computational demands of stochastic models make the simulation of large-scale systems impractical. Alternatively, continuum models, which can describe behavior at the tumor scale, often rely on phenomenological assumptions in place of rigorous upscaling of microscopic models. This limits their predictive power. In this work, we circumvent the derivation of closed macroscopic equations for the growing cancer cell populations; instead, we construct, based on the so-called “equation-free” framework, a computational superstructure, which wraps around the individual-based cell-level simulator and accelerates the computations required for the study of the long-time behavior of systems involving many interacting cells. The microscopic model, e.g., a cellular automaton, which simulates the evolution of cancer cell populations, is executed for relatively short time intervals, at the end of which coarse-scale information is obtained. These coarse variables evolve on slower time scales than each individual cell in the population, enabling the application of forward projection schemes, which extrapolate their values at later times. This technique is referred to as coarse projective integration. Increasing the ratio of projection times to microscopic simulator execution times enhances the computational savings. Crucial accuracy issues arising for growing tumors with radial symmetry are addressed by applying the coarse projective integration scheme in a cotraveling (cogrowing) frame. As a proof of principle, we demonstrate that the application of this scheme yields highly accurate solutions, while preserving the computational savings of coarse projective integration. PMID:22587128

Population Density Modeling for Diverse Land Use Classes: Creating a National Dasymetric Worker Population Model

NASA Astrophysics Data System (ADS)

Trombley, N.; Weber, E.; Moehl, J.

2017-12-01

Many studies invoke dasymetric mapping to make more accurate depictions of population distribution by spatially restricting populations to inhabited/inhabitable portions of observational units (e.g., census blocks) and/or by varying population density among different land classes. LandScan USA uses this approach by restricting particular population components (such as residents or workers) to building area detected from remotely sensed imagery, but also goes a step further by classifying each cell of building area in accordance with ancillary land use information from national parcel data (CoreLogic, Inc.'s ParcelPoint database). Modeling population density according to land use is critical. For instance, office buildings would have a higher density of workers than warehouses even though the latter would likely have more cells of detection. This paper presents a modeling approach by which different land uses are assigned different densities to more accurately distribute populations within them. For parts of the country where the parcel data is insufficient, an alternate methodology is developed that uses National Land Cover Database (NLCD) data to define the land use type of building detection. Furthermore, LiDAR data is incorporated for many of the largest cities across the US, allowing the independent variables to be updated from two-dimensional building detection area to total building floor space. In the end, four different regression models are created to explain the effect of different land uses on worker distribution: A two-dimensional model using land use types from the parcel data A three-dimensional model using land use types from the parcel data A two-dimensional model using land use types from the NLCD data, and A three-dimensional model using land use types from the NLCD data. By and large, the resultant coefficients followed intuition, but importantly allow the relationships between different land uses to be quantified. For instance, in the model using two-dimensional building area, commercial building area had a density 2.5 times greater than public building area and 4 times greater than industrial building area. These coefficients can be applied to define the ratios at which population is distributed to building cells. Finally, possible avenues for refining the methodology are presented.

Primitive Sca-1 Positive Bone Marrow HSC in Mouse Model of Aplastic Anemia: A Comparative Study through Flowcytometric Analysis and Scanning Electron Microscopy

PubMed Central

Chatterjee, Sumanta; Basak, Pratima; Das, Prosun; Das, Madhurima; Pereira, Jacintha Archana; Dutta, Ranjan Kumar; Chaklader, Malay; Chaudhuri, Samaresh; Law, Sujata

2010-01-01

Self-renewing Hematopoietic Stem Cells (HSCs) are responsible for reconstitution of all blood cell lineages. Sca-1 is the “stem cell antigen” marker used to identify the primitive murine HSC population, the expression of which decreases upon differentiation to other mature cell types. Sca-1+ HSCs maintain the bone marrow stem cell pool throughout the life. Aplastic anemia is a disease considered to involve primary stem cell deficiency and is characterized by severe pancytopenia and a decline in healthy blood cell generation system. Studies conducted in our laboratory revealed that the primitive Sca-1+ BM-HSCs (bone marrow hematopoietic stem cell) are significantly affected in experimental Aplastic animals pretreated with chemotherapeutic drugs (Busulfan and Cyclophosphamide) and there is increased Caspase-3 activity with consecutive high Annexin-V positivity leading to premature apoptosis in the bone marrow hematopoietic stem cell population in Aplastic condition. The Sca-1bright, that is, “more primitive” BM-HSC population was more affected than the “less primitive” BM-HSC Sca-1dim  population. The decreased cell population and the receptor expression were directly associated with an empty and deranged marrow microenvironment, which is evident from scanning electron microscopy (SEM). The above experimental evidences hint toward the manipulation of receptor expression for the benefit of cytotherapy by primitive stem cell population in Aplastic anemia cases. PMID:21048851

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth.

PubMed

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

NASA Astrophysics Data System (ADS)

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.

Two-population model for medial temporal lobe neurons: The vast majority are almost silent

NASA Astrophysics Data System (ADS)

Magyar, Andrew; Collins, John

2015-07-01

Recordings in the human medial temporal lobe have found many neurons that respond to pictures (and related stimuli) of just one particular person of those presented. It has been proposed that these are concept cells, responding to just a single concept. However, a direct experimental test of the concept cell idea appears impossible, because it would need the measurement of the response of each cell to enormous numbers of other stimuli. Here we propose a new statistical method for analysis of the data that gives a more powerful way to analyze how close data are to the concept-cell idea. Central to the model is the neuronal sparsity, defined as the total fraction of stimuli that elicit an above-threshold response in the neuron. The model exploits the large number of sampled neurons to give sensitivity to situations where the average response sparsity is much less than one response for the number of presented stimuli. We show that a conventional model where a single sparsity is postulated for all neurons gives an extremely poor fit to the data. In contrast, a model with two dramatically different populations gives an excellent fit to data from the hippocampus and entorhinal cortex. In the hippocampus, one population has 7% of the cells with a 2.6% sparsity. But a much larger fraction (93%) respond to only 0.1% of the stimuli. This can result in an extreme bias in the responsiveness of reported neurons compared with a typical neuron. Finally, we show how to allow for the fact that some identified units correspond to multiple neurons and find that our conclusions at the neural level are quantitatively changed but strengthened, with an even stronger difference between the two populations.

Binding of fluoresceinated epidermal growth factor to A431 cell sub-populations studied using a model-independent analysis of flow cytometric fluorescence data.

PubMed Central

Chatelier, R C; Ashcroft, R G; Lloyd, C J; Nice, E C; Whitehead, R H; Sawyer, W H; Burgess, A W

1986-01-01

A method is developed for determining ligand-cell association parameters from a model-free analysis of data obtained with a flow cytometer. The method requires measurement of the average fluorescence per cell as a function of ligand and cell concentration. The analysis is applied to data obtained for the binding of fluoresceinated epidermal growth factor to a human epidermoid carcinoma cell line, A431. The results indicate that the growth factor binds to two classes of sites on A431 cells: 4 X 10(4) sites with a dissociation constant (KD) of less than or equal to 20 pM, and 1.5 X 10(6) sites with a KD of 3.7 nM. A derived plot of the average fluorescence per cell versus the average number of bound ligands per cell is used to construct binding isotherms for four sub-populations of A431 cells fractionated on the basis of low-angle light scatter. The four sub-populations bind the ligand with equal affinity but differ substantially in terms of the number of binding sites per cell. We also use this new analysis to critically evaluate the use of 'Fluorotrol' as a calibration standard in flow cytometry. PMID:3015587

Genetically distinct leukemic stem cells in human CD34− acute myeloid leukemia are arrested at a hemopoietic precursor-like stage

PubMed Central

Quek, Lynn; Garnett, Catherine; Karamitros, Dimitris; Stoilova, Bilyana; Doondeea, Jessica; Kennedy, Alison; Metzner, Marlen; Ivey, Adam; Sternberg, Alexander; Hunter, Hannah; Price, Andrew; Virgo, Paul; Grimwade, David; Freeman, Sylvie; Russell, Nigel; Mead, Adam

2016-01-01

Our understanding of the perturbation of normal cellular differentiation hierarchies to create tumor-propagating stem cell populations is incomplete. In human acute myeloid leukemia (AML), current models suggest transformation creates leukemic stem cell (LSC) populations arrested at a progenitor-like stage expressing cell surface CD34. We show that in ∼25% of AML, with a distinct genetic mutation pattern where >98% of cells are CD34−, there are multiple, nonhierarchically arranged CD34+ and CD34− LSC populations. Within CD34− and CD34+ LSC–containing populations, LSC frequencies are similar; there are shared clonal structures and near-identical transcriptional signatures. CD34− LSCs have disordered global transcription profiles, but these profiles are enriched for transcriptional signatures of normal CD34− mature granulocyte–macrophage precursors, downstream of progenitors. But unlike mature precursors, LSCs express multiple normal stem cell transcriptional regulators previously implicated in LSC function. This suggests a new refined model of the relationship between LSCs and normal hemopoiesis in which the nature of genetic/epigenetic changes determines the disordered transcriptional program, resulting in LSC differentiation arrest at stages that are most like either progenitor or precursor stages of hemopoiesis. PMID:27377587

Characterization and functional analysis of a slow-cycling subpopulation in colorectal cancer enriched by cell cycle inducer combined chemotherapy.

PubMed

Wu, Feng-Hua; Mu, Lei; Li, Xiao-Lan; Hu, Yi-Bing; Liu, Hui; Han, Lin-Tao; Gong, Jian-Ping

2017-10-03

The concept of cancer stem cells has been proposed in various malignancies including colorectal cancer. Recent studies show direct evidence for quiescence slow-cycling cells playing a role in cancer stem cells. There exists an urgent need to isolate and better characterize these slow-cycling cells. In this study, we developed a new model to enrich slow-cycling tumor cells using cell-cycle inducer combined with cell cycle-dependent chemotherapy in vitro and in vivo . Our results show that Short-term exposure of colorectal cancer cells to chemotherapy combined with cell-cycle inducer enriches for a cell-cycle quiescent tumor cell population. Specifically, these slow-cycling tumor cells exhibit increased chemotherapy resistance in vitro and tumorigenicity in vivo . Notably, these cells are stem-cell like and participate in metastatic dormancy. Further exploration indicates that slow-cycling colorectal cancer cells in our model are less sensitive to cytokine-induced-killer cell mediated cytotoxic killing in vivo and in vitro . Collectively, our cell cycle inducer combined chemotherapy exposure model enriches for a slow-cycling, dormant, chemo-resistant tumor cell sub-population that are resistant to cytokine induced killer cell based immunotherapy. Studying unique signaling pathways in dormant tumor cells enriched by cell cycle inducer combined chemotherapy treatment is expected to identify novel therapeutic targets for preventing tumor recurrence.

Characterization and functional analysis of a slow-cycling subpopulation in colorectal cancer enriched by cell cycle inducer combined chemotherapy

PubMed Central

Wu, Feng-Hua; Mu, Lei; Li, Xiao-Lan; Hu, Yi-Bing; Liu, Hui; Han, Lin-Tao; Gong, Jian-Ping

2017-01-01

The concept of cancer stem cells has been proposed in various malignancies including colorectal cancer. Recent studies show direct evidence for quiescence slow-cycling cells playing a role in cancer stem cells. There exists an urgent need to isolate and better characterize these slow-cycling cells. In this study, we developed a new model to enrich slow-cycling tumor cells using cell-cycle inducer combined with cell cycle-dependent chemotherapy in vitro and in vivo. Our results show that Short-term exposure of colorectal cancer cells to chemotherapy combined with cell-cycle inducer enriches for a cell-cycle quiescent tumor cell population. Specifically, these slow-cycling tumor cells exhibit increased chemotherapy resistance in vitro and tumorigenicity in vivo. Notably, these cells are stem-cell like and participate in metastatic dormancy. Further exploration indicates that slow-cycling colorectal cancer cells in our model are less sensitive to cytokine-induced-killer cell mediated cytotoxic killing in vivo and in vitro. Collectively, our cell cycle inducer combined chemotherapy exposure model enriches for a slow-cycling, dormant, chemo-resistant tumor cell sub-population that are resistant to cytokine induced killer cell based immunotherapy. Studying unique signaling pathways in dormant tumor cells enriched by cell cycle inducer combined chemotherapy treatment is expected to identify novel therapeutic targets for preventing tumor recurrence. PMID:29108242

Phenotype heterogeneity in cancer cell populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Almeida, Luis; Chisholm, Rebecca; Clairambault, Jean

2016-06-08

Phenotype heterogeneity in cancer cell populations, be it of genetic, epigenetic or stochastic origin, has been identified as a main source of resistance to drug treatments and a major source of therapeutic failures in cancers. The molecular mechanisms of drug resistance are partly understood at the single cell level (e.g., overexpression of ABC transporters or of detoxication enzymes), but poorly predictable in tumours, where they are hypothesised to rely on heterogeneity at the cell population scale, which is thus the right level to describe cancer growth and optimise its control by therapeutic strategies in the clinic. We review a fewmore » results from the biological literature on the subject, and from mathematical models that have been published to predict and control evolution towards drug resistance in cancer cell populations. We propose, based on the latter, optimisation strategies of combined treatments to limit emergence of drug resistance to cytotoxic drugs in cancer cell populations, in the monoclonal situation, which limited as it is still retains consistent features of cell population heterogeneity. The polyclonal situation, that may be understood as “bet hedging” of the tumour, thus protecting itself from different sources of drug insults, may lie beyond such strategies and will need further developments. In the monoclonal situation, we have designed an optimised therapeutic strategy relying on a scheduled combination of cytotoxic and cytostatic treatments that can be adapted to different situations of cancer treatments. Finally, we review arguments for biological theoretical frameworks proposed at different time and development scales, the so-called atavistic model (diachronic view relying on Darwinian genotype selection in the coursof billions of years) and the Waddington-like epigenetic landscape endowed with evolutionary quasi-potential (synchronic view relying on Lamarckian phenotype instruction of a given genome by reversible mechanisms), to represent evolution towards heterogeneity, possibly polyclonal, in cancer cell populations and propose innovative directions for therapeutic strategies based on such frameworks.« less

Phenotype heterogeneity in cancer cell populations

NASA Astrophysics Data System (ADS)

Almeida, Luis; Chisholm, Rebecca; Clairambault, Jean; Escargueil, Alexandre; Lorenzi, Tommaso; Lorz, Alexander; Trélat, Emmanuel

2016-06-01

Phenotype heterogeneity in cancer cell populations, be it of genetic, epigenetic or stochastic origin, has been identified as a main source of resistance to drug treatments and a major source of therapeutic failures in cancers. The molecular mechanisms of drug resistance are partly understood at the single cell level (e.g., overexpression of ABC transporters or of detoxication enzymes), but poorly predictable in tumours, where they are hypothesised to rely on heterogeneity at the cell population scale, which is thus the right level to describe cancer growth and optimise its control by therapeutic strategies in the clinic. We review a few results from the biological literature on the subject, and from mathematical models that have been published to predict and control evolution towards drug resistance in cancer cell populations. We propose, based on the latter, optimisation strategies of combined treatments to limit emergence of drug resistance to cytotoxic drugs in cancer cell populations, in the monoclonal situation, which limited as it is still retains consistent features of cell population heterogeneity. The polyclonal situation, that may be understood as "bet hedging" of the tumour, thus protecting itself from different sources of drug insults, may lie beyond such strategies and will need further developments. In the monoclonal situation, we have designed an optimised therapeutic strategy relying on a scheduled combination of cytotoxic and cytostatic treatments that can be adapted to different situations of cancer treatments. Finally, we review arguments for biological theoretical frameworks proposed at different time and development scales, the so-called atavistic model (diachronic view relying on Darwinian genotype selection in the coursof billions of years) and the Waddington-like epigenetic landscape endowed with evolutionary quasi-potential (synchronic view relying on Lamarckian phenotype instruction of a given genome by reversible mechanisms), to represent evolution towards heterogeneity, possibly polyclonal, in cancer cell populations and propose innovative directions for therapeutic strategies based on such frameworks.

Density-Dependent Recycling Promotes the Long-Term Survival of Bacterial Populations during Periods of Starvation.

PubMed

Takano, Sotaro; Pawlowska, Bogna J; Gudelj, Ivana; Yomo, Tetsuya; Tsuru, Saburo

2017-02-07

The amount of natural resources in the Earth's environment is in flux, which can trigger catastrophic collapses of ecosystems. How populations survive under nutrient-poor conditions is a central question in ecology. Curiously, some bacteria persist for a long time in nutrient-poor environments. Although this survival may be accomplished through cell death and the recycling of dead cells, the importance of these processes and the mechanisms underlying the survival of the populations have not been quantitated. Here, we use microbial laboratory experiments and mathematical models to demonstrate that death and recycling are essential activities for the maintenance of cell survival. We also show that the behavior of the survivors is governed by population density feedback, wherein growth is limited not only by the available resources but also by the population density. The numerical simulations suggest that population density-dependent recycling could be an advantageous behavior under starvation conditions. How organisms survive after exhaustion of resources is a central question in ecology. Starving Escherichia coli constitute a model system to understand survival mechanisms during long-term starvation. Although death and the recycling of dead cells might play a key role in the maintenance of long-term survival, their mechanisms and importance have not been quantitated. Here, we verified the significance of social recycling of dead cells for long-term survival. We also show that the survivors restrained their recycling and did not use all available nutrients released from dead cells, which may be advantageous under starvation conditions. These results indicate that not only the utilization of dead cells but also restrained recycling coordinate the effective utilization of limited resources for long-term survival under starvation. Copyright © 2017 Takano et al.

Stimulation of angiogenesis, neurogenesis and regeneration by side population cells from dental pulp.

PubMed

Ishizaka, Ryo; Hayashi, Yuki; Iohara, Koichiro; Sugiyama, Masahiko; Murakami, Masashi; Yamamoto, Tsubasa; Fukuta, Osamu; Nakashima, Misako

2013-03-01

Mesenchymal stem cells (MSCs) have been used for cell therapy in various experimental disease models. However, the regenerative potential of MSCs from different tissue sources and the influence of the tissue niche have not been investigated. In this study, we compared the regenerative potential of dental pulp, bone marrow and adipose tissue-derived CD31(-) side population (SP) cells isolated from an individual porcine source. Pulp CD31(-) SP cells expressed the highest levels of angiogenic/neurotrophic factors and had the highest migration activity. Conditioned medium from pulp CD31(-) SP cells produced potent anti-apoptotic activity and neurite outgrowth, compared to those from bone marrow and adipose CD31(-) SP cells. Transplantation of pulp CD31(-) SP cells in a mouse hindlimb ischemia model produced higher blood flow and capillary density than transplantation of bone marrow and adipose CD31(-) SP cells. Motor function recovery and infarct size reduction were greater with pulp CD31(-) SP cells. Pulp CD31(-) SP cells induced maximal angiogenesis, neurogenesis and pulp regeneration in ectopic transplantation models compared to other tissue sources. These results demonstrate that pulp stem cells have higher angiogenic, neurogenic and regenerative potential and may therefore be superior to bone marrow and adipose stem cells for cell therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

Regeneration of dental pulp by stem cells.

PubMed

Nakashima, M; Iohara, K

2011-07-01

Angiogenesis/vasculogenesis and neurogenesis are essential for pulp regeneration. Two subfractions of side-population (SP) cells, CD31(-)/CD146(-) SP cells and CD105(+) cells with angiogenic and neurogenic potential, were isolated by flow cytometry from canine dental pulp. In an experimental model of mouse hindlimb ischemia, transplantation of these cell populations resulted in an increase in blood flow, including high-density capillary formation. In a model of rat cerebral ischemia, stem cell transplantations enhanced neuronal regeneration and recovery from motor disability. Autologous transplantation of the CD31(-)/CD146(-) SP cells into an in vivo model of amputated pulp resulted in complete regeneration of pulp tissue with vascular and neuronal processes within 14 days. The transplanted cells expressed pro-angiogenic factors, implying trophic action on endothelial cells. Autologous transplantation of CD31(-)/CD146(-) SP cells or CD105(+) cells with stromal-cell-derived factor-1 (SDF-1) into root canals after whole pulp removal of mature teeth resulted in complete regeneration of pulp replete with nerves and vasculature by day 14, followed by dentin formation along the dentinal wall by day 35. Therefore, the potential utility of fractionated SP cells and CD105(+) cells in angiogenesis and neurogenesis was demonstrated by treatment of limb and cerebral ischemia following pulpotomy and pulpectomy.

ODE, RDE and SDE models of cell cycle dynamics and clustering in yeast.

PubMed

Boczko, Erik M; Gedeon, Tomas; Stowers, Chris C; Young, Todd R

2010-07-01

Biologists have long observed periodic-like oxygen consumption oscillations in yeast populations under certain conditions, and several unsatisfactory explanations for this phenomenon have been proposed. These ‘autonomous oscillations’ have often appeared with periods that are nearly integer divisors of the calculated doubling time of the culture. We hypothesize that these oscillations could be caused by a form of cell cycle synchronization that we call clustering. We develop some novel ordinary differential equation models of the cell cycle. For these models, and for random and stochastic perturbations, we give both rigorous proofs and simulations showing that both positive and negative growth rate feedback within the cell cycle are possible agents that can cause clustering of populations within the cell cycle. It occurs for a variety of models and for a broad selection of parameter values. These results suggest that the clustering phenomenon is robust and is likely to be observed in nature. Since there are necessarily an integer number of clusters, clustering would lead to periodic-like behaviour with periods that are nearly integer divisors of the period of the cell cycle. Related experiments have shown conclusively that cell cycle clustering occurs in some oscillating yeast cultures.

Computational model, method, and system for kinetically-tailoring multi-drug chemotherapy for individuals

DOEpatents

Gardner, Shea Nicole

2007-10-23

A method and system for tailoring treatment regimens to individual patients with diseased cells exhibiting evolution of resistance to such treatments. A mathematical model is provided which models rates of population change of proliferating and quiescent diseased cells using cell kinetics and evolution of resistance of the diseased cells, and pharmacokinetic and pharmacodynamic models. Cell kinetic parameters are obtained from an individual patient and applied to the mathematical model to solve for a plurality of treatment regimens, each having a quantitative efficacy value associated therewith. A treatment regimen may then be selected from the plurlaity of treatment options based on the efficacy value.

Mathematical model for HIV dynamics in HIV-specific helper cells

NASA Astrophysics Data System (ADS)

Pinto, Carla M. A.; Carvalho, Ana

2014-03-01

In this paper we study a delay mathematical model for the dynamics of HIV in HIV-specific CD4 + T helper cells. We modify the model presented by Roy and Wodarz in 2012, where the HIV dynamics is studied, considering a single CD4 + T cell population. Non-specific helper cells are included as alternative target cell population, to account for macrophages and dendritic cells. In this paper, we include two types of delay: (1) a latent period between the time target cells are contacted by the virus particles and the time the virions enter the cells and; (2) virus production period for new virions to be produced within and released from the infected cells. We compute the reproduction number of the model, R0, and the local stability of the disease free equilibrium and of the endemic equilibrium. We find that for values of R0<1, the model approaches asymptotically the disease free equilibrium. For values of R0>1, the model approximates asymptotically the endemic equilibrium. We observe numerically the phenomenon of backward bifurcation for values of R0⪅1. This statement will be proved in future work. We also vary the values of the latent period and the production period of infected cells and free virus. We conclude that increasing these values translates in a decrease of the reproduction number. Thus, a good strategy to control the HIV virus should focus on drugs to prolong the latent period and/or slow down the virus production. These results suggest that the model is mathematically and epidemiologically well-posed.

A biologically based model of growth and senescence of Syrian hamster embryo (SHE) cells after exposure to arsenic.

PubMed Central

Liao, K H; Gustafson, D L; Fox, M H; Chubb, L S; Reardon, K F; Yang, R S

2001-01-01

We modified the two-stage Moolgavkar-Venzon-Knudson (MVK) model for use with Syrian hamster embryo (SHE) cell neoplastic progression. Five phenotypic stages are proposed in this model: Normal cells can either become senescent or mutate into immortal cells followed by anchorage-independent growth and tumorigenic stages. The growth of normal SHE cells was controlled by their division, death, and senescence rates, and all senescent cells were converted from normal cells. In this report, we tested the modeling of cell kinetics of the first two phenotypic stages against experimental data evaluating the effects of arsenic on SHE cells. We assessed cell division and death rates using flow cytometry and correlated cell division rates to the degree of confluence of cell cultures. The mean cell death rate was approximately equal to 1% of the average division rate. Arsenic did not induce immortalization or further mutations of SHE cells at concentrations of 2 microM and below, and chromium (3.6 microM) and lead (100 microM) had similar negative results. However, the growth of SHE cells was inhibited by 5.4 microM arsenic after a 2-day exposure, with cells becoming senescent after only 16 population doublings. In contrast, normal cells and cells exposed to lower arsenic concentrations grew normally for at least 30 population doublings. The biologically based model successfully predicted the growth of normal and arsenic-treated cells, as well as the senescence rates. Mechanisms responsible for inducing cellular senescence in SHE cells exposed to arsenic may help explain the apparent inability of arsenic to induce neoplasia in experimental animals. PMID:11748027

Generational distribution of a Candida glabrata population: Resilient old cells prevail, while younger cells dominate in the vulnerable host.

PubMed

Bouklas, Tejas; Alonso-Crisóstomo, Luz; Székely, Tamás; Diago-Navarro, Elizabeth; Orner, Erika P; Smith, Kalie; Munshi, Mansa A; Del Poeta, Maurizio; Balázsi, Gábor; Fries, Bettina C

2017-05-01

Similar to other yeasts, the human pathogen Candida glabrata ages when it undergoes asymmetric, finite cell divisions, which determines its replicative lifespan. We sought to investigate if and how aging changes resilience of C. glabrata populations in the host environment. Our data demonstrate that old C. glabrata are more resistant to hydrogen peroxide and neutrophil killing, whereas young cells adhere better to epithelial cell layers. Consequently, virulence of old compared to younger C. glabrata cells is enhanced in the Galleria mellonella infection model. Electron microscopy images of old C. glabrata cells indicate a marked increase in cell wall thickness. Comparison of transcriptomes of old and young C. glabrata cells reveals differential regulation of ergosterol and Hog pathway associated genes as well as adhesion proteins, and suggests that aging is accompanied by remodeling of the fungal cell wall. Biochemical analysis supports this conclusion as older cells exhibit a qualitatively different lipid composition, leading to the observed increased emergence of fluconazole resistance when grown in the presence of fluconazole selection pressure. Older C. glabrata cells accumulate during murine and human infection, which is statistically unlikely without very strong selection. Therefore, we tested the hypothesis that neutrophils constitute the predominant selection pressure in vivo. When we altered experimentally the selection pressure by antibody-mediated removal of neutrophils, we observed a significantly younger pathogen population in mice. Mathematical modeling confirmed that differential selection of older cells is sufficient to cause the observed demographic shift in the fungal population. Hence our data support the concept that pathogenesis is affected by the generational age distribution of the infecting C. glabrata population in a host. We conclude that replicative aging constitutes an emerging trait, which is selected by the host and may even play an unanticipated role in the transition from a commensal to a pathogen state.

A parallel implementation of an off-lattice individual-based model of multicellular populations

NASA Astrophysics Data System (ADS)

Harvey, Daniel G.; Fletcher, Alexander G.; Osborne, James M.; Pitt-Francis, Joe

2015-07-01

As computational models of multicellular populations include ever more detailed descriptions of biophysical and biochemical processes, the computational cost of simulating such models limits their ability to generate novel scientific hypotheses and testable predictions. While developments in microchip technology continue to increase the power of individual processors, parallel computing offers an immediate increase in available processing power. To make full use of parallel computing technology, it is necessary to develop specialised algorithms. To this end, we present a parallel algorithm for a class of off-lattice individual-based models of multicellular populations. The algorithm divides the spatial domain between computing processes and comprises communication routines that ensure the model is correctly simulated on multiple processors. The parallel algorithm is shown to accurately reproduce the results of a deterministic simulation performed using a pre-existing serial implementation. We test the scaling of computation time, memory use and load balancing as more processes are used to simulate a cell population of fixed size. We find approximate linear scaling of both speed-up and memory consumption on up to 32 processor cores. Dynamic load balancing is shown to provide speed-up for non-regular spatial distributions of cells in the case of a growing population.

Density-based clustering analyses to identify heterogeneous cellular sub-populations

NASA Astrophysics Data System (ADS)

Heaster, Tiffany M.; Walsh, Alex J.; Landman, Bennett A.; Skala, Melissa C.

2017-02-01

Autofluorescence microscopy of NAD(P)H and FAD provides functional metabolic measurements at the single-cell level. Here, density-based clustering algorithms were applied to metabolic autofluorescence measurements to identify cell-level heterogeneity in tumor cell cultures. The performance of the density-based clustering algorithm, DENCLUE, was tested in samples with known heterogeneity (co-cultures of breast carcinoma lines). DENCLUE was found to better represent the distribution of cell clusters compared to Gaussian mixture modeling. Overall, DENCLUE is a promising approach to quantify cell-level heterogeneity, and could be used to understand single cell population dynamics in cancer progression and treatment.

Point process models for localization and interdependence of punctate cellular structures.

PubMed

Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F

2016-07-01

Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Emergent multicellular life cycles in filamentous bacteria owing to density-dependent population dynamics.

PubMed

Rossetti, Valentina; Filippini, Manuela; Svercel, Miroslav; Barbour, A D; Bagheri, Homayoun C

2011-12-07

Filamentous bacteria are the oldest and simplest known multicellular life forms. By using computer simulations and experiments that address cell division in a filamentous context, we investigate some of the ecological factors that can lead to the emergence of a multicellular life cycle in filamentous life forms. The model predicts that if cell division and death rates are dependent on the density of cells in a population, a predictable cycle between short and long filament lengths is produced. During exponential growth, there will be a predominance of multicellular filaments, while at carrying capacity, the population converges to a predominance of short filaments and single cells. Model predictions are experimentally tested and confirmed in cultures of heterotrophic and phototrophic bacterial species. Furthermore, by developing a formulation of generation time in bacterial populations, it is shown that changes in generation time can alter length distributions. The theory predicts that given the same population growth curve and fitness, species with longer generation times have longer filaments during comparable population growth phases. Characterization of the environmental dependence of morphological properties such as length, and the number of cells per filament, helps in understanding the pre-existing conditions for the evolution of developmental cycles in simple multicellular organisms. Moreover, the theoretical prediction that strains with the same fitness can exhibit different lengths at comparable growth phases has important implications. It demonstrates that differences in fitness attributed to morphology are not the sole explanation for the evolution of life cycles dominated by multicellularity.

Tumor-Initiating Cells and Methods of Use

NASA Technical Reports Server (NTRS)

Hlatky, Lynn (Inventor)

2014-01-01

Provided herein are an isolated or enriched population of tumor initiating cells derived from normal cells, cells susceptible to neoplasia, or neoplastic cells. Methods of use of the cells for screening for anti-hyperproliferative agents, and use of the cells for animal models of hyperproliferative disorders including metastatic cancer, diagnostic methods, and therapeutic methods are provided.

Protein Biomarkers Associated With Growth And Synaptogenesis In a cell culture model of neuronal development

EPA Science Inventory

Cerebellar granule cells (CGC) provide a homogenous population of cells which can be used as an in vitro model for studying the cellular processes involved in the normal development of the CNS. They may also be useful for hazard identification as in vitro screens fo...

Study of muscle cell dedifferentiation after skeletal muscle injury of mice with a Cre-Lox system.

PubMed

Mu, Xiaodong; Peng, Hairong; Pan, Haiying; Huard, Johnny; Li, Yong

2011-02-03

Dedifferentiation of muscle cells in the tissue of mammals has yet to be observed. One of the challenges facing the study of skeletal muscle cell dedifferentiation is the availability of a reliable model that can confidentially distinguish differentiated cell populations of myotubes and non-fused mononuclear cells, including stem cells that can coexist within the population of cells being studied. In the current study, we created a Cre/Lox-β-galactosidase system, which can specifically tag differentiated multinuclear myotubes and myotube-generated mononuclear cells based on the activation of the marker gene, β-galactosidase. By using this system in an adult mouse model, we found that β-galactosidase positive mononuclear cells were generated from β-galactosidase positive multinuclear myofibers upon muscle injury. We also demonstrated that these mononuclear cells can develop into a variety of different muscle cell lineages, i.e., myoblasts, satellite cells, and muscle derived stem cells. These novel findings demonstrated, for the first time, that cellular dedifferentiation of skeletal muscle cells actually occurs in mammalian skeletal muscle following traumatic injury in vivo.

The stability of colorectal cancer mathematical models

NASA Astrophysics Data System (ADS)

Khairudin, Nur Izzati; Abdullah, Farah Aini

2013-04-01

Colorectal cancer is one of the most common types of cancer. To better understand about the kinetics of cancer growth, mathematical models are used to provide insight into the progression of this natural process which enables physicians and oncologists to determine optimal radiation and chemotherapy schedules and develop a prognosis, both of which are indispensable for treating cancer. This thesis investigates the stability of colorectal cancer mathematical models. We found that continuous saturating feedback is the best available model of colorectal cancer growth. We also performed stability analysis. The result shows that cancer progress in sequence of genetic mutations or epigenetic which lead to a very large number of cells population until become unbounded. The cell population growth initiate and its saturating feedback is overcome when mutation changes causing the net per-capita growth rate of stem or transit cells exceed critical threshold.

Continuum-level modelling of cellular adhesion and matrix production in aggregates.

PubMed

Geris, Liesbet; Ashbourn, Joanna M A; Clarke, Tim

2011-05-01

Key regulators in tissue-engineering processes such as cell culture and cellular organisation are the cell-cell and cell-matrix interactions. As mathematical models are increasingly applied to investigate biological phenomena in the biomedical field, it is important, for some applications, that these models incorporate an adequate description of cell adhesion. This study describes the development of a continuum model that represents a cell-in-gel culture system used in bone-tissue engineering, namely that of a cell aggregate embedded in a hydrogel. Cell adhesion is modelled through the use of non-local (integral) terms in the partial differential equations. The simulation results demonstrate that the effects of cell-cell and cell-matrix adhesion are particularly important for the survival and growth of the cell population and the production of extracellular matrix by the cells, concurring with experimental observations in the literature.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

NASA Astrophysics Data System (ADS)

Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

2009-12-01

Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

Acute B lymphoblastic leukaemia-propagating cells are present at high frequency in diverse lymphoblast populations

PubMed Central

Rehe, Klaus; Wilson, Kerrie; Bomken, Simon; Williamson, Daniel; Irving, Julie; den Boer, Monique L; Stanulla, Martin; Schrappe, Martin; Hall, Andrew G; Heidenreich, Olaf; Vormoor, Josef

2013-01-01

Leukaemia-propagating cells are more frequent in high-risk acute B lymphoblastic leukaemia than in many malignancies that follow a hierarchical cancer stem cell model. It is unclear whether this characteristic can be more universally applied to patients from non-‘high-risk’ sub-groups and across a broad range of cellular immunophenotypes. Here, we demonstrate in a wide range of primary patient samples and patient samples previously passaged through mice that leukaemia-propagating cells are found in all populations defined by high or low expression of the lymphoid differentiation markers CD10, CD20 or CD34. The frequency of leukaemia-propagating cells and their engraftment kinetics do not differ between these populations. Transcriptomic analysis of CD34high and CD34low blasts establishes their difference and their similarity to comparable normal progenitors at different stages of B-cell development. However, consistent with the functional similarity of these populations, expression signatures characteristic of leukaemia propagating cells in acute myeloid leukaemia fail to distinguish between the different populations. Together, these findings suggest that there is no stem cell hierarchy in acute B lymphoblastic leukaemia. PMID:23229821

The re-incarnation, re-interpretation and re-demise of the transition probability model.

PubMed

Koch, A L

1999-05-28

There are two classes of models for the cell cycle that have both a deterministic and a stochastic part; they are the transition probability (TP) models and sloppy size control (SSC) models. The hallmark of the basic TP model are two graphs: the alpha and beta plots. The former is the semi-logarithmic plot of the percentage of cell divisions yet to occur, this results in a horizontal line segment at 100% corresponding to the deterministic phase and a straight line sloping tail corresponding to the stochastic part. The beta plot concerns the differences of the age-at-division of sisters (the beta curve) and gives a straight line parallel to the tail of the alpha curve. For the SC models the deterministic part is the time needed for the cell to accumulate a critical amount of some substance(s). The variable part differs in the various variants of the general model, but they do not give alpha and beta curves with linear tails as postulated by the TP model. This paper argues against TP and for an elaboration of SSC type of model. The main argument against TP is that it assumes that the probability of the transition from the stochastic phase is time invariant even though it is certain that the cells are growing and metabolizing throughout the cell cycle; a fact that should make the transition probability be variable. The SSC models presume that cell division is triggered by the cell's success in growing and not simply the result of elapsed time. The extended model proposed here to accommodate the predictions of the SSC to the straight tailed parts of the alpha and beta plots depends on the existence of a few percent of the cell in a growing culture that are not growing normally, these are growing much slower or are temporarily quiescent. The bulk of the cells, however, grow nearly exponentially. Evidence for a slow growing component comes from experimental analyses of population size distributions for a variety of cell types by the Collins-Richmond technique. These subpopulations existence is consistent with the new concept that there are a large class of rapidly reversible mutations occurring in many organisms and at many loci serving a large range of purposes to enable the cell to survive environmental challenges. These mutations yield special subpopulations of cells within a population. The reversible mutational changes, relevant to the elaboration of SSC models, produce slow-growing cells that are either very large or very small in size; these later revert to normal growth and division. The subpopulations, however, distort the population distribution in such a way as to fit better the exponential tails of the alpha and beta curves of the TP model.

The model of fungal population dynamics affected by nystatin

NASA Astrophysics Data System (ADS)

Voychuk, Sergei I.; Gromozova, Elena N.; Sadovskiy, Mikhail G.

Fungal diseases are acute problems of the up-to-day medicine. Significant increase of resistance of microorganisms to the medically used antibiotics and a lack of new effective drugs follows in a growth of dosage of existing chemicals to solve the problem. Quite often such approach results in side effects on humans. Detailed study of fungi-antibiotic dynamics can identify new mechanisms and bring new ideas to overcome the microbial resistance with a lower dosage of antibiotics. In this study, the dynamics of the microbial population under antibiotic treatment was investigated. The effects of nystatin on the population of Saccharomyces cerevisiae yeasts were used as a model system. Nystatin effects were investigated both in liquid and solid media by viability tests. Dependence of nystatin action on osmotic gradient was evaluated in NaCl solutions. Influences of glucose and yeast extract were additionally analyzed. A "stepwise" pattern of the cell death caused by nystatin was the most intriguing. This pattern manifested in periodical changes of the stages of cell death against stages of resistance to the antibiotic. The mathematical model was proposed to describe cell-antibiotic interactions and nystatin viability effects in the liquid medium. The model implies that antibiotic ability to cause a cells death is significantly affected by the intracellular compounds, which came out of cells after their osmotic barriers were damaged

A Special Population of Regulatory T Cells Potentiates Muscle Repair

PubMed Central

Burzyn, Dalia; Kuswanto, Wilson; Kolodin, Dmitriy; Shadrach, Jennifer L.; Cerletti, Massimiliano; Jang, Young; Sefik, Esen; Tan, Tze Guan; Wagers, Amy J.; Benoist, Christophe; Mathis, Diane

2014-01-01

SUMMARY Long recognized to be potent suppressors of immune responses, Foxp3+CD4+ regulatory T (Treg) cells are being rediscovered as regulators of nonimmunological processes. We describe a phenotypically and functionally distinct population of Treg cells that rapidly accumulated in the acutely injured skeletal muscle of mice, just as invading myeloidlineage cells switched from a proinflammatory to a proregenerative state. A Treg population of similar phenotype accumulated in muscles of genetically dystrophic mice. Punctual depletion of Treg cells during the repair process prolonged the proinflammatory infiltrate and impaired muscle repair, while treatments that increased or decreased Treg activities diminished or enhanced (respectively) muscle damage in a dystrophy model. Muscle Treg cells expressed the growth factor Amphiregulin, which acted directly on muscle satellite cells in vitro and improved muscle repair in vivo. Thus, Treg cells and their products may provide new therapeutic opportunities for wound repair and muscular dystrophies. PMID:24315098

Inference of cell-cell interactions from population density characteristics and cell trajectories on static and growing domains.

PubMed

Ross, Robert J H; Yates, C A; Baker, R E

2015-06-01

A key feature of cell migration is how cell movement is affected by cell-cell interactions. Furthermore, many cell migratory processes such as neural crest stem cell migration [Thomas and Erickson, 2008; McLennan et al., 2012] occur on growing domains or in the presence of a chemoattractant. Therefore, it is important to study interactions between migrating cells in the context of domain growth and directed motility. Here we compare discrete and continuum models describing the spatial and temporal evolution of a cell population for different types of cell-cell interactions on static and growing domains. We suggest that cell-cell interactions can be inferred from population density characteristics in the presence of motility bias, and these population density characteristics for different cell-cell interactions are conserved on both static and growing domains. We also study the expected displacement of a tagged cell, and show that different types of cell-cell interactions can give rise to cell trajectories with different characteristics. These characteristics are conserved in the presence of domain growth, however, they are diminished in the presence of motility bias. Our results are relevant for researchers who study the existence and role of cell-cell interactions in biological systems, so far as we suggest that different types of cell-cell interactions could be identified from cell density and trajectory data. Copyright © 2015 Elsevier Inc. All rights reserved.

A simple theoretical framework for understanding heterogeneous differentiation of CD4+ T cells

PubMed Central

2012-01-01

Background CD4+ T cells have several subsets of functional phenotypes, which play critical yet diverse roles in the immune system. Pathogen-driven differentiation of these subsets of cells is often heterogeneous in terms of the induced phenotypic diversity. In vitro recapitulation of heterogeneous differentiation under homogeneous experimental conditions indicates some highly regulated mechanisms by which multiple phenotypes of CD4+ T cells can be generated from a single population of naïve CD4+ T cells. Therefore, conceptual understanding of induced heterogeneous differentiation will shed light on the mechanisms controlling the response of populations of CD4+ T cells under physiological conditions. Results We present a simple theoretical framework to show how heterogeneous differentiation in a two-master-regulator paradigm can be governed by a signaling network motif common to all subsets of CD4+ T cells. With this motif, a population of naïve CD4+ T cells can integrate the signals from their environment to generate a functionally diverse population with robust commitment of individual cells. Notably, two positive feedback loops in this network motif govern three bistable switches, which in turn, give rise to three types of heterogeneous differentiated states, depending upon particular combinations of input signals. We provide three prototype models illustrating how to use this framework to explain experimental observations and make specific testable predictions. Conclusions The process in which several types of T helper cells are generated simultaneously to mount complex immune responses upon pathogenic challenges can be highly regulated, and a simple signaling network motif can be responsible for generating all possible types of heterogeneous populations with respect to a pair of master regulators controlling CD4+ T cell differentiation. The framework provides a mathematical basis for understanding the decision-making mechanisms of CD4+ T cells, and it can be helpful for interpreting experimental results. Mathematical models based on the framework make specific testable predictions that may improve our understanding of this differentiation system. PMID:22697466

Synchronized mammalian cell culture: part I--a physical strategy for synchronized cultivation under physiological conditions.

PubMed

Barradas, Oscar Platas; Jandt, Uwe; Becker, Max; Bahnemann, Janina; Pörtner, Ralf; Zeng, An-Ping

2015-01-01

Conventional analysis and optimization procedures of mammalian cell culture processes mostly treat the culture as a homogeneous population. Hence, the focus is on cell physiology and metabolism, cell line development, and process control strategy. Impact on cultivations caused by potential variations in cellular properties between different subpopulations, however, has not yet been evaluated systematically. One main cause for the formation of such subpopulations is the progress of all cells through the cell cycle. The interaction of potential cell cycle specific variations in the cell behavior with large-scale process conditions can be optimally determined by means of (partially) synchronized cultivations, with subsequent population resolved model analysis. Therefore, it is desirable to synchronize a culture with minimal perturbation, which is possible with different yield and quality using physical selection methods, but not with frequently used chemical or whole-culture methods. Conventional nonsynchronizing methods with subsequent cell-specific, for example, flow cytometric analysis, can only resolve cell-limited effects of the cell cycle. In this work, we demonstrate countercurrent-flow centrifugal elutriation as a useful physical method to enrich mammalian cell populations within different phases of a cell cycle, which can be further cultivated for synchronized growth in bioreactors under physiological conditions. The presented combined approach contrasts with other physical selection methods especially with respect to the achievable yield, which makes it suitable for bioreactor scale cultivations. As shown with two industrial cell lines (CHO-K1 and human AGE1.HN), synchronous inocula can be obtained with overall synchrony degrees of up to 82% in the G1 phase, 53% in the S phase and 60% in the G2/M phase, with enrichment factors (Ysync) of 1.71, 1.79, and 4.24 respectively. Cells are able to grow with synchrony in bioreactors over several cell cycles. This strategy, combined with population-resolved model analysis and parameter extraction as described in the accompanying paper, offers new possibilities for studies of cell lines and processes at levels of cell cycle and population under physiological conditions. © 2014 American Institute of Chemical Engineers.

Mathematical Model of Naive T Cell Division and Survival IL-7 Thresholds.

PubMed

Reynolds, Joseph; Coles, Mark; Lythe, Grant; Molina-París, Carmen

2013-01-01

We develop a mathematical model of the peripheral naive T cell population to study the change in human naive T cell numbers from birth to adulthood, incorporating thymic output and the availability of interleukin-7 (IL-7). The model is formulated as three ordinary differential equations: two describe T cell numbers, in a resting state and progressing through the cell cycle. The third is introduced to describe changes in IL-7 availability. Thymic output is a decreasing function of time, representative of the thymic atrophy observed in aging humans. Each T cell is assumed to possess two interleukin-7 receptor (IL-7R) signaling thresholds: a survival threshold and a second, higher, proliferation threshold. If the IL-7R signaling strength is below its survival threshold, a cell may undergo apoptosis. When the signaling strength is above the survival threshold, but below the proliferation threshold, the cell survives but does not divide. Signaling strength above the proliferation threshold enables entry into cell cycle. Assuming that individual cell thresholds are log-normally distributed, we derive population-average rates for apoptosis and entry into cell cycle. We have analyzed the adiabatic change in homeostasis as thymic output decreases. With a parameter set representative of a healthy individual, the model predicts a unique equilibrium number of T cells. In a parameter range representative of persistent viral or bacterial infection, where naive T cell cycle progression is impaired, a decrease in thymic output may result in the collapse of the naive T cell repertoire.

CD4+ Foxp3+ T cells promote aberrant immunoglobulin G production and maintain CD8+ T-cell suppression during chronic liver disease.

PubMed

Tedesco, Dana; Thapa, Manoj; Gumber, Sanjeev; Elrod, Elizabeth J; Rahman, Khalidur; Ibegbu, Chris C; Magliocca, Joseph F; Adams, Andrew B; Anania, Frank; Grakoui, Arash

2017-02-01

Persistent hepatotropic viral infections are a common etiologic agent of chronic liver disease. Unresolved infection can be attributed to nonfunctional intrahepatic CD8+ T-cell responses. In light of dampened CD8 + T-cell responses, liver disease often manifests systemically as immunoglobulin (Ig)-related syndromes due to aberrant B-cell functions. These two opposing yet coexisting phenomena implicate the potential of altered CD4 + T-cell help. Elevated CD4 + forkhead box P3-positive (Foxp3+) T cells were evident in both human liver disease and a mouse model of chemically induced liver injury despite marked activation and spontaneous IgG production by intrahepatic B cells. While this population suppressed CD8 + T-cell responses, aberrant B-cell activities were maintained due to expression of CD40 ligand on a subset of CD4 + Foxp3+ T cells. In vivo blockade of CD40 ligand attenuated B-cell abnormalities in a mouse model of liver injury. A phenotypically similar population of CD4 + Foxp3+, CD40 ligand-positive T cells was found in diseased livers explanted from patients with chronic hepatitis C infection. This population was absent in nondiseased liver tissues and peripheral blood. Liver disease elicits alterations in the intrahepatic CD4 + T-cell compartment that suppress T-cell immunity while concomitantly promoting aberrant IgG mediated manifestations. (Hepatology 2017;65:661-677). © 2016 by the American Association for the Study of Liver Diseases.

Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

PubMed Central

Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

2013-01-01

In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients.

PubMed

Ribeiro, Ilda Patrícia; Caramelo, Francisco; Esteves, Luísa; Menoita, Joana; Marques, Francisco; Barroso, Leonor; Miguéis, Jorge; Melo, Joana Barbosa; Carreira, Isabel Marques

2017-10-24

The head and neck squamous cell carcinoma (HNSCC) population consists mainly of high-risk for recurrence and locally advanced stage patients. Increased knowledge of the HNSCC genomic profile can improve early diagnosis and treatment outcomes. The development of models to identify consistent genomic patterns that distinguish HNSCC patients that will recur and/or develop metastasis after treatment is of utmost importance to decrease mortality and improve survival rates. In this study, we used array comparative genomic hybridization data from HNSCC patients to implement a robust model to predict HNSCC recurrence/metastasis. This predictive model showed a good accuracy (>80%) and was validated in an independent population from TCGA data portal. This predictive genomic model comprises chromosomal regions from 5p, 6p, 8p, 9p, 11q, 12q, 15q and 17p, where several upstream and downstream members of signaling pathways that lead to an increase in cell proliferation and invasion are mapped. The introduction of genomic predictive models in clinical practice might contribute to a more individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The power of this genomic model to predict the recurrence and metastases development should be evaluated in other HNSCC populations.

A generalized model for multi-marker analysis of cell cycle progression in synchrony experiments.

PubMed

Mayhew, Michael B; Robinson, Joshua W; Jung, Boyoun; Haase, Steven B; Hartemink, Alexander J

2011-07-01

To advance understanding of eukaryotic cell division, it is important to observe the process precisely. To this end, researchers monitor changes in dividing cells as they traverse the cell cycle, with the presence or absence of morphological or genetic markers indicating a cell's position in a particular interval of the cell cycle. A wide variety of marker data is available, including information-rich cellular imaging data. However, few formal statistical methods have been developed to use these valuable data sources in estimating how a population of cells progresses through the cell cycle. Furthermore, existing methods are designed to handle only a single binary marker of cell cycle progression at a time. Consequently, they cannot facilitate comparison of experiments involving different sets of markers. Here, we develop a new sampling model to accommodate an arbitrary number of different binary markers that characterize the progression of a population of dividing cells along a branching process. We engineer a strain of Saccharomyces cerevisiae with fluorescently labeled markers of cell cycle progression, and apply our new model to two image datasets we collected from the strain, as well as an independent dataset of different markers. We use our model to estimate the duration of post-cytokinetic attachment between a S.cerevisiae mother and daughter cell. The Java implementation is fast and extensible, and includes a graphical user interface. Our model provides a powerful and flexible cell cycle analysis tool, suitable to any type or combination of binary markers. The software is available from: http://www.cs.duke.edu/~amink/software/cloccs/. michael.mayhew@duke.edu; amink@cs.duke.edu.

The penny pusher: a cellular model of lens growth.

PubMed

Shi, Yanrong; De Maria, Alicia; Lubura, Snježana; Šikić, Hrvoje; Bassnett, Steven

2014-12-16

The mechanisms that regulate the number of cells in the lens and, therefore, its size and shape are unknown. We examined the dynamic relationship between proliferative behavior in the epithelial layer and macroscopic lens growth. The distribution of S-phase cells across the epithelium was visualized by confocal microscopy and cell populations were determined from orthographic projections of the lens surface. The number of S-phase cells in the mouse lens epithelium fell exponentially, to an asymptotic value of approximately 200 cells by 6 months. Mitosis became increasingly restricted to a 300-μm-wide swath of equatorial epithelium, the germinative zone (GZ), within which two peaks in labeling index were detected. Postnatally, the cell population increased to approximately 50,000 cells at 4 weeks of age. Thereafter, the number of cells declined, despite continued growth in lens dimensions. This apparently paradoxical observation was explained by a time-dependent increase in the surface area of cells at all locations. The cell biological measurements were incorporated into a physical model, the Penny Pusher. In this simple model, cells were considered to be of a single type, the proliferative behavior of which depended solely on latitude. Simulations using the Penny Pusher predicted the emergence of cell clones and were in good agreement with data obtained from earlier lineage-tracing studies. The Penny Pusher, a simple stochastic model, offers a useful conceptual framework for the investigation of lens growth mechanisms and provides a plausible alternative to growth models that postulate the existence of lens stem cells. Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.

A new interpretation of the Keller-Segel model based on multiphase modelling.

PubMed

Byrne, Helen M; Owen, Markus R

2004-12-01

In this paper an alternative derivation and interpretation are presented of the classical Keller-Segel model of cell migration due to random motion and chemotaxis. A multiphase modelling approach is used to describe how a population of cells moves through a fluid containing a diffusible chemical to which the cells are attracted. The cells and fluid are viewed as distinct components of a two-phase mixture. The principles of mass and momentum balance are applied to each phase, and appropriate constitutive laws imposed to close the resulting equations. A key assumption here is that the stress in the cell phase is influenced by the concentration of the diffusible chemical. By restricting attention to one-dimensional cartesian geometry we show how the model reduces to a pair of nonlinear coupled partial differential equations for the cell density and the chemical concentration. These equations may be written in the form of the Patlak-Keller-Segel model, naturally including density-dependent nonlinearities in the cell motility coefficients. There is a direct relationship between the random motility and chemotaxis coefficients, both depending in an inter-related manner on the chemical concentration. We suggest that this may explain why many chemicals appear to stimulate both chemotactic and chemokinetic responses in cell populations. After specialising our model to describe slime mold we then show how the functional form of the chemical potential that drives cell locomotion influences the ability of the system to generate spatial patterns. The paper concludes with a summary of the key results and a discussion of avenues for future research.

Tumor-volume simulation during radiotherapy for head-and-neck cancer using a four-level cell population model.

PubMed

Chvetsov, Alexei V; Dong, Lei; Palta, Jantinder R; Amdur, Robert J

2009-10-01

To develop a fast computational radiobiologic model for quantitative analysis of tumor volume during fractionated radiotherapy. The tumor-volume model can be useful for optimizing image-guidance protocols and four-dimensional treatment simulations in proton therapy that is highly sensitive to physiologic changes. The analysis is performed using two approximations: (1) tumor volume is a linear function of total cell number and (2) tumor-cell population is separated into four subpopulations: oxygenated viable cells, oxygenated lethally damaged cells, hypoxic viable cells, and hypoxic lethally damaged cells. An exponential decay model is used for disintegration and removal of oxygenated lethally damaged cells from the tumor. We tested our model on daily volumetric imaging data available for 14 head-and-neck cancer patients treated with an integrated computed tomography/linear accelerator system. A simulation based on the averaged values of radiobiologic parameters was able to describe eight cases during the entire treatment and four cases partially (50% of treatment time) with a maximum 20% error. The largest discrepancies between the model and clinical data were obtained for small tumors, which may be explained by larger errors in the manual tumor volume delineation procedure. Our results indicate that the change in gross tumor volume for head-and-neck cancer can be adequately described by a relatively simple radiobiologic model. In future research, we propose to study the variation of model parameters by fitting to clinical data for a cohort of patients with head-and-neck cancer and other tumors. The potential impact of other processes, like concurrent chemotherapy, on tumor volume should be evaluated.

Lgr6 labels a rare population of mammary gland progenitor cells that are able to originate luminal mammary tumours

PubMed Central

Messal, Hendrik A.; Andersson, Agneta B.; Ruiz, E. Josue; Gerling, Marco; Douagi, Iyadh; Spencer-Dene, Bradley; Musch, Alexandra; Mitter, Richard; Bhaw, Leena; Stone, Richard; Bornhorst, Dorothee; Sesay, Abdul K.; Jonkers, Jos; Stamp, Gordon; Malanchi, Ilaria; Toftgård, Rune; Behrens, Axel

2018-01-01

The mammary gland is composed of a complex cellular hierarchy with unusual postnatal plasticity. The identities of stem/progenitor cell populations, as well as tumour-initiating cells that give rise to breast cancer, are incompletely understood. Here we show that Lgr6 marks rare populations of cells in both basal and luminal mammary gland compartments in mice. Lineage tracing analysis showed that Lgr6+ cells are unipotent progenitors, which expand clonally during puberty but diminish in adulthood. In pregnancy or upon stimulation with ovarian hormones, adult Lgr6+ cells regained proliferative potency and their progeny formed alveoli over repeated pregnancies. Oncogenic mutations in Lgr6+ cells resulted in expansion of luminal cells, culminating in mammary gland tumours. Conversely, depletion of Lgr6+ cells in the MMTV-PyMT model of mammary tumourigenesis significantly impaired tumour growth. Thus, Lgr6 marks mammary gland progenitor cells that can initiate tumours, and cells of luminal breast tumours required for efficient tumour maintenance. PMID:27798604

Fluid and mass transport modelling to drive the design of cell-packed hollow fibre bioreactors for tissue engineering applications.

PubMed

Shipley, Rebecca J; Waters, Sarah L

2012-12-01

A model for fluid and mass transport in a single module of a tissue engineering hollow fibre bioreactor (HFB) is developed. Cells are seeded in alginate throughout the extra-capillary space (ECS), and fluid is pumped through a central lumen to feed the cells and remove waste products. Fluid transport is described using Navier-Stokes or Darcy equations as appropriate; this is overlaid with models of mass transport in the form of advection-diffusion-reaction equations that describe the distribution and uptake/production of nutrients/waste products. The small aspect ratio of a module is exploited and the option of opening an ECS port is explored. By proceeding analytically, operating equations are determined that enable a tissue engineer to prescribe the geometry and operation of the HFB by ensuring the nutrient and waste product concentrations are consistent with a functional cell population. Finally, results for chondrocyte and cardiomyocyte cell populations are presented, typifying two extremes of oxygen uptake rates.

Biology as population dynamics: heuristics for transmission risk.

PubMed

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

Population-type models, accounting for phenomena such as population lifetimes, mixing patterns, recruitment patterns, genetic evolution and environmental conditions, can be usefully applied to the biology of HIV infection and viral replication. A simple dynamic model can explore the effect of a vaccine-like stimulus on the mortality and infectiousness, which formally looks like fertility, of invading virions; the mortality of freshly infected cells; and the availability of target cells, all of which impact on the probability of infection. Variations on this model could capture the importance of the timing and duration of different key events in viral transmission, and hence be applied to questions of mucosal immunology. The dynamical insights and assumptions of such models are compatible with the continuum of between- and within-individual risks in sexual violence and may be helpful in making sense of the sparse data available on the association between HIV transmission and sexual violence. © 2012 John Wiley & Sons A/S.

Adaptive therapy.

PubMed

Gatenby, Robert A; Silva, Ariosto S; Gillies, Robert J; Frieden, B Roy

2009-06-01

A number of successful systemic therapies are available for treatment of disseminated cancers. However, tumor response is often transient, and therapy frequently fails due to emergence of resistant populations. The latter reflects the temporal and spatial heterogeneity of the tumor microenvironment as well as the evolutionary capacity of cancer phenotypes to adapt to therapeutic perturbations. Although cancers are highly dynamic systems, cancer therapy is typically administered according to a fixed, linear protocol. Here we examine an adaptive therapeutic approach that evolves in response to the temporal and spatial variability of tumor microenvironment and cellular phenotype as well as therapy-induced perturbations. Initial mathematical models find that when resistant phenotypes arise in the untreated tumor, they are typically present in small numbers because they are less fit than the sensitive population. This reflects the "cost" of phenotypic resistance such as additional substrate and energy used to up-regulate xenobiotic metabolism, and therefore not available for proliferation, or the growth inhibitory nature of environments (i.e., ischemia or hypoxia) that confer resistance on phenotypically sensitive cells. Thus, in the Darwinian environment of a cancer, the fitter chemosensitive cells will ordinarily proliferate at the expense of the less fit chemoresistant cells. The models show that, if resistant populations are present before administration of therapy, treatments designed to kill maximum numbers of cancer cells remove this inhibitory effect and actually promote more rapid growth of the resistant populations. We present an alternative approach in which treatment is continuously modulated to achieve a fixed tumor population. The goal of adaptive therapy is to enforce a stable tumor burden by permitting a significant population of chemosensitive cells to survive so that they, in turn, suppress proliferation of the less fit but chemoresistant subpopulations. Computer simulations show that this strategy can result in prolonged survival that is substantially greater than that of high dose density or metronomic therapies. The feasibility of adaptive therapy is supported by in vivo experiments. [Cancer Res 2009;69(11):4894-903] Major FindingsWe present mathematical analysis of the evolutionary dynamics of tumor populations with and without therapy. Analytic solutions and numerical simulations show that, with pretreatment, therapy-resistant cancer subpopulations are present due to phenotypic or microenvironmental factors; maximum dose density chemotherapy hastens rapid expansion of resistant populations. The models predict that host survival can be maximized if "treatment-for-cure strategy" is replaced by "treatment-for-stability." Specifically, the models predict that an optimal treatment strategy will modulate therapy to maintain a stable population of chemosensitive cells that can, in turn, suppress the growth of resistant populations under normal tumor conditions (i.e., when therapy-induced toxicity is absent). In vivo experiments using OVCAR xenografts treated with carboplatin show that adaptive therapy is feasible and, in this system, can produce long-term survival.

Modeling the lung: Design and development of tissue engineered macro- and micro-physiologic lung models for research use.

PubMed

Nichols, Joan E; Niles, Jean A; Vega, Stephanie P; Argueta, Lissenya B; Eastaway, Adriene; Cortiella, Joaquin

2014-09-01

Respiratory tract specific cell populations, or tissue engineered in vitro grown human lung, have the potential to be used as research tools to mimic physiology, toxicology, pathology, as well as infectious diseases responses of cells or tissues. Studies related to respiratory tract pathogenesis or drug toxicity testing in the past made use of basic systems where single cell populations were exposed to test agents followed by evaluations of simple cellular responses. Although these simple single-cell-type systems provided good basic information related to cellular responses, much more can be learned from cells grown in fabricated microenvironments which mimic in vivo conditions in specialized microfabricated chambers or by human tissue engineered three-dimensional (3D) models which allow for more natural interactions between cells. Recent advances in microengineering technology, microfluidics, and tissue engineering have provided a new approach to the development of 2D and 3D cell culture models which enable production of more robust human in vitro respiratory tract models. Complex models containing multiple cell phenotypes also provide a more reasonable approximation of what occurs in vivo without the confounding elements in the dynamic in vivo environment. The goal of engineering good 3D human models is the formation of physiologically functional respiratory tissue surrogates which can be used as pathogenesis models or in the case of 2D screening systems for drug therapy evaluation as well as human toxicity testing. We hope that this manuscript will serve as a guide for development of future respiratory tract model systems as well as a review of conventional models. © 2014 by the Society for Experimental Biology and Medicine.

Digital Image Analysis of Yeast Single Cells Growing in Two Different Oxygen Concentrations to Analyze the Population Growth and to Assist Individual-Based Modeling

PubMed Central

Ginovart, Marta; Carbó, Rosa; Blanco, Mónica; Portell, Xavier

2018-01-01

Nowadays control of the growth of Saccharomyces to obtain biomass or cellular wall components is crucial for specific industrial applications. The general aim of this contribution is to deal with experimental data obtained from yeast cells and from yeast cultures to attempt the integration of the two levels of information, individual and population, to progress in the control of yeast biotechnological processes by means of the overall analysis of this set of experimental data, and to assist in the improvement of an individual-based model, namely, INDISIM-Saccha. Populations of S. cerevisiae growing in liquid batch culture, in aerobic and microaerophilic conditions, were studied. A set of digital images was taken during the population growth, and a protocol for the treatment and analyses of the images obtained was established. The piecewise linear model of Buchanan was adjusted to the temporal evolutions of the yeast populations to determine the kinetic parameters and changes of growth phases. In parallel, for all the yeast cells analyzed, values of direct morphological parameters, such as area, perimeter, major diameter, minor diameter, and derived ones, such as circularity and elongation, were obtained. Graphical and numerical methods from descriptive statistics were applied to these data to characterize the growth phases and the budding state of the yeast cells in both experimental conditions, and inferential statistical methods were used to compare the diverse groups of data achieved. Oxidative metabolism of yeast in a medium with oxygen available and low initial sugar concentration can be taken into account in order to obtain a greater number of cells or larger cells. Morphological parameters were analyzed statistically to identify which were the most useful for the discrimination of the different states, according to budding and/or growth phase, in aerobic and microaerophilic conditions. The use of the experimental data for subsequent modeling work was then discussed and compared to simulation results generated with INDISIM-Saccha, which allowed us to advance in the development of this yeast model, and illustrated the utility of data at different levels of observation and the needs and logic behind the development of a microbial individual-based model. PMID:29354112

The Impact of Prophage on the Equilibria and Stability of Phage and Host

NASA Astrophysics Data System (ADS)

Yu, Pei; Nadeem, Alina; Wahl, Lindi M.

2017-06-01

In this paper, we present a bacteriophage model that includes prophage, that is, phage genomes that are incorporated into the host cell genome. The general model is described by an 18-dimensional system of ordinary differential equations. This study focuses on asymptotic behaviour of the model, and thus the system is reduced to a simple six-dimensional model, involving uninfected host cells, infected host cells and phage. We use dynamical system theory to explore the dynamic behaviour of the model, studying in particular the impact of prophage on the equilibria and stability of phage and host. We employ bifurcation and stability theory, centre manifold and normal form theory to show that the system has multiple equilibrium solutions which undergo a series of bifurcations, finally leading to oscillating motions. Numerical simulations are presented to illustrate and confirm the analytical predictions. The results of this study indicate that in some parameter regimes, the host cell population may drive the phage to extinction through diversification, that is, if multiple types of host emerge; this prediction holds even if the phage population is likewise diverse. This parameter regime is restricted, however, if infecting phage are able to recombine with prophage sequences in the host cell genome.

Epithelial-mesenchymal transition can suppress major attributes of human epithelial tumor-initiating cells

PubMed Central

Celià-Terrassa, Toni; Meca-Cortés, Óscar; Mateo, Francesca; Martínez de Paz, Alexia; Rubio, Nuria; Arnal-Estapé, Anna; Ell, Brian J.; Bermudo, Raquel; Díaz, Alba; Guerra-Rebollo, Marta; Lozano, Juan José; Estarás, Conchi; Ulloa, Catalina; ρlvarez-Simón, Daniel; Milà, Jordi; Vilella, Ramón; Paciucci, Rosanna; Martínez-Balbás, Marian; García de Herreros, Antonio; Gomis, Roger R.; Kang, Yibin; Blanco, Jerónimo; Fernández, Pedro L.; Thomson, Timothy M.

2012-01-01

Malignant progression in cancer requires populations of tumor-initiating cells (TICs) endowed with unlimited self renewal, survival under stress, and establishment of distant metastases. Additionally, the acquisition of invasive properties driven by epithelial-mesenchymal transition (EMT) is critical for the evolution of neoplastic cells into fully metastatic populations. Here, we characterize 2 human cellular models derived from prostate and bladder cancer cell lines to better understand the relationship between TIC and EMT programs in local invasiveness and distant metastasis. The model tumor subpopulations that expressed a strong epithelial gene program were enriched in highly metastatic TICs, while a second subpopulation with stable mesenchymal traits was impoverished in TICs. Constitutive overexpression of the transcription factor Snai1 in the epithelial/TIC-enriched populations engaged a mesenchymal gene program and suppressed their self renewal and metastatic phenotypes. Conversely, knockdown of EMT factors in the mesenchymal-like prostate cancer cell subpopulation caused a gain in epithelial features and properties of TICs. Both tumor cell subpopulations cooperated so that the nonmetastatic mesenchymal-like prostate cancer subpopulation enhanced the in vitro invasiveness of the metastatic epithelial subpopulation and, in vivo, promoted the escape of the latter from primary implantation sites and accelerated their metastatic colonization. Our models provide new insights into how dynamic interactions among epithelial, self-renewal, and mesenchymal gene programs determine the plasticity of epithelial TICs. PMID:22505459

Comparison of individual-based modeling and population approaches for prediction of foodborne pathogens growth.

PubMed

Augustin, Jean-Christophe; Ferrier, Rachel; Hezard, Bernard; Lintz, Adrienne; Stahl, Valérie

2015-02-01

Individual-based modeling (IBM) approach combined with the microenvironment modeling of vacuum-packed cold-smoked salmon was more effective to describe the variability of the growth of a few Listeria monocytogenes cells contaminating irradiated salmon slices than the traditional population models. The IBM approach was particularly relevant to predict the absence of growth in 25% (5 among 20) of artificially contaminated cold-smoked salmon samples stored at 8 °C. These results confirmed similar observations obtained with smear soft cheese (Ferrier et al., 2013). These two different food models were used to compare the IBM/microscale and population/macroscale modeling approaches in more global exposure and risk assessment frameworks taking into account the variability and/or the uncertainty of the factors influencing the growth of L. monocytogenes. We observed that the traditional population models significantly overestimate exposure and risk estimates in comparison to IBM approach when contamination of foods occurs with a low number of cells (<100 per serving). Moreover, the exposure estimates obtained with the population model were characterized by a great uncertainty. The overestimation was mainly linked to the ability of IBM to predict no growth situations rather than the consideration of microscale environment. On the other hand, when the aim of quantitative risk assessment studies is only to assess the relative impact of changes in control measures affecting the growth of foodborne bacteria, the two modeling approach gave similar results and the simplest population approach was suitable. Copyright © 2014 Elsevier Ltd. All rights reserved.

The growth threshold conjecture: a theoretical framework for understanding T-cell tolerance.

PubMed

Arias, Clemente F; Herrero, Miguel A; Cuesta, José A; Acosta, Francisco J; Fernández-Arias, Cristina

2015-07-01

Adaptive immune responses depend on the capacity of T cells to target specific antigens. As similar antigens can be expressed by pathogens and host cells, the question naturally arises of how can T cells discriminate friends from foes. In this work, we suggest that T cells tolerate cells whose proliferation rates remain below a permitted threshold. Our proposal relies on well-established facts about T-cell dynamics during acute infections: T-cell populations are elastic (they expand and contract) and they display inertia (contraction is delayed relative to antigen removal). By modelling inertia and elasticity, we show that tolerance to slow-growing populations can emerge as a population-scale feature of T cells. This result suggests a theoretical framework to understand immune tolerance that goes beyond the self versus non-self dichotomy. It also accounts for currently unexplained observations, such as the paradoxical tolerance to slow-growing pathogens or the presence of self-reactive T cells in the organism.

Mathematical modelling of phenotypic plasticity and conversion to a stem-cell state under hypoxia

NASA Astrophysics Data System (ADS)

Dhawan, Andrew; Madani Tonekaboni, Seyed Ali; Taube, Joseph H.; Hu, Stephen; Sphyris, Nathalie; Mani, Sendurai A.; Kohandel, Mohammad

2016-02-01

Hypoxia, or oxygen deficiency, is known to be associated with breast tumour progression, resistance to conventional therapies and poor clinical prognosis. The epithelial-mesenchymal transition (EMT) is a process that confers invasive and migratory capabilities as well as stem cell properties to carcinoma cells thus promoting metastatic progression. In this work, we examined the impact of hypoxia on EMT-associated cancer stem cell (CSC) properties, by culturing transformed human mammary epithelial cells under normoxic and hypoxic conditions, and applying in silico mathematical modelling to simulate the impact of hypoxia on the acquisition of CSC attributes and the transitions between differentiated and stem-like states. Our results indicate that both the heterogeneity and the plasticity of the transformed cell population are enhanced by exposure to hypoxia, resulting in a shift towards a more stem-like population with increased EMT features. Our findings are further reinforced by gene expression analyses demonstrating the upregulation of EMT-related genes, as well as genes associated with therapy resistance, in hypoxic cells compared to normoxic counterparts. In conclusion, we demonstrate that mathematical modelling can be used to simulate the role of hypoxia as a key contributor to the plasticity and heterogeneity of transformed human mammary epithelial cells.

Chronology of Islet Differentiation Revealed By Temporal Cell Labeling

PubMed Central

Miyatsuka, Takeshi; Li, Zhongmei; German, Michael S.

2009-01-01

OBJECTIVE Neurogenin 3 plays a pivotal role in pancreatic endocrine differentiation. Whereas mouse models expressing reporters such as eGFP or LacZ under the control of the Neurog3 gene enable us to label cells in the pancreatic endocrine lineage, the long half-life of most reporter proteins makes it difficult to distinguish cells actively expressing neurogenin 3 from differentiated cells that have stopped transcribing the gene. RESEARCH DESIGN AND METHODS In order to separate the transient neurogenin 3 –expressing endocrine progenitor cells from the differentiating endocrine cells, we developed a mouse model (Ngn3-Timer) in which DsRed-E5, a fluorescent protein that shifts its emission spectrum from green to red over time, was expressed transgenically from the NEUROG3 locus. RESULTS In the Ngn3-Timer embryos, green-dominant cells could be readily detected by microscopy or flow cytometry and distinguished from green/red double-positive cells. When fluorescent cells were sorted into three different populations by a fluorescence-activated cell sorter, placed in culture, and then reanalyzed by flow cytometry, green-dominant cells converted to green/red double-positive cells within 6 h. The sorted cell populations were then used to determine the temporal patterns of expression for 145 transcriptional regulators in the developing pancreas. CONCLUSIONS The precise temporal resolution of this model defines the narrow window of neurogenin 3 expression in islet progenitor cells and permits sequential analyses of sorted cells as well as the testing of gene regulatory models for the differentiation of pancreatic islet cells. PMID:19478145

Accurate Prediction of Drug-Induced Liver Injury Using Stem Cell-Derived Populations

PubMed Central

Szkolnicka, Dagmara; Farnworth, Sarah L.; Lucendo-Villarin, Baltasar; Storck, Christopher; Zhou, Wenli; Iredale, John P.; Flint, Oliver

2014-01-01

Despite major progress in the knowledge and management of human liver injury, there are millions of people suffering from chronic liver disease. Currently, the only cure for end-stage liver disease is orthotopic liver transplantation; however, this approach is severely limited by organ donation. Alternative approaches to restoring liver function have therefore been pursued, including the use of somatic and stem cell populations. Although such approaches are essential in developing scalable treatments, there is also an imperative to develop predictive human systems that more effectively study and/or prevent the onset of liver disease and decompensated organ function. We used a renewable human stem cell resource, from defined genetic backgrounds, and drove them through developmental intermediates to yield highly active, drug-inducible, and predictive human hepatocyte populations. Most importantly, stem cell-derived hepatocytes displayed equivalence to primary adult hepatocytes, following incubation with known hepatotoxins. In summary, we have developed a serum-free, scalable, and shippable cell-based model that faithfully predicts the potential for human liver injury. Such a resource has direct application in human modeling and, in the future, could play an important role in developing renewable cell-based therapies. PMID:24375539

Modeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation

PubMed Central

Espinosa Angarica, Vladimir

2016-01-01

Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self‐renewal and differentiation. In particular, we suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation‐specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine. PMID:27321053

A new ODE tumor growth modeling based on tumor population dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oroji, Amin; Omar, Mohd bin; Yarahmadian, Shantia

2015-10-22

In this paper a new mathematical model for the population of tumor growth treated by radiation is proposed. The cells dynamics population in each state and the dynamics of whole tumor population are studied. Furthermore, a new definition of tumor lifespan is presented. Finally, the effects of two main parameters, treatment parameter (q), and repair mechanism parameter (r) on tumor lifespan are probed, and it is showed that the change in treatment parameter (q) highly affects the tumor lifespan.

Destruction of solid tumors by immune cells

NASA Astrophysics Data System (ADS)

López, Álvaro G.; Seoane, Jesús M.; Sanjuán, Miguel A. F.

2017-03-01

The fractional cell kill is a mathematical expression describing the rate at which a certain population of cells is reduced to a fraction of itself. In order to investigate the fractional cell kill that governs the rate at which a solid tumor is lysed by a cell population of cytotoxic CD8+ T cells (CTLs), we present several in silico simulations and mathematical analyses. When the CTLs eradicate efficiently the tumor cells, the models predict a correlation between the morphology of the tumors and the rate at which they are lysed. However, when the effectiveness of the immune cells is decreased, the mathematical function fails to reproduce the process of lysis. This limit is thoroughly discussed and a new fractional cell kill is proposed.

Population Pharmacokinetic-Pharmacodynamic Modeling of 5-Fluorouracil for Toxicities in Rats.

PubMed

Kobuchi, Shinji; Ito, Yukako; Sakaeda, Toshiyuki

2017-08-01

Myelosuppression is a dose-limiting toxicity of 5-fluorouracil (5-FU). Predicting the inter- and intra-patient variability in pharmacokinetics and toxicities of 5-FU may contribute to the individualized medicine. This study aimed to establish a population pharmacokinetic-pharmacodynamic model that could evaluate the inter- and intra-individual variability in the plasma 5-FU concentration, 5-FU-induced body weight loss and myelosuppression in rats. Plasma 5-FU concentrations, body weight loss, and blood cell counts in rats following the intravenous administration of various doses of 5-FU for 4 days were used to develop the population pharmacokinetic-pharmacodynamic model. The population pharmacokinetic model consisting of a two-compartment model with Michaelis-Menten elimination kinetics successfully characterized the individual and population predictions of the plasma concentration of 5-FU and provided credible parameter estimates. The estimates of inter-individual variability in maximal rate of saturable metabolism and residual variability were 8.1 and 22.0%, respectively. The population pharmacokinetic-pharmacodynamic model adequately described the individual complete time-course of alterations in body weight loss, erythrocyte, leukocyte, and lymphocyte counts in rats treated with various doses of 5-FU. The inter-individual variability of the drug effects in the pharmacodynamic model for body weight loss was 82.6%, which was relatively high. The results of the present study suggest that not only individual fluctuations in the 5-FU concentration but also the cell sensitivity would affect the onset and degree of 5-FU-induced toxicity. This population pharmacokinetic-pharmacodynamic model could evaluate the inter- and intra-individual variability in drug-induced toxicity and guide the assessments of novel anticancer agents in drug development.

A Cell Model to Evaluate Chemical Effects on Adult Human Cardiac Progenitor Cell Differentiation and Function

EPA Science Inventory

Adult cardiac stem cells (CSC) and progenitor cells (CPC) represent a population of cells in the heart critical for its regeneration and function over a lifetime. The impact of chemicals on adult human CSC/CPC differentiation and function is unknown. Research was conducted to dev...

Differentiation Generates Paracrine Cell Pairs That Maintain Basaloid Mouse Mammary Tumors: Proof of Concept

PubMed Central

Kim, Soyoung; Goel, Shruti; Alexander, Caroline M.

2011-01-01

There is a paradox offered up by the cancer stem cell hypothesis. How are the mixed populations that are characteristic of heterogeneous solid tumors maintained at constant proportion, given their high, and different, mitotic indices? In this study, we evaluate a well-characterized mouse model of human basaloid tumors (induced by the oncogene Wnt1), which comprise mixed populations of mammary epithelial cells resembling their normal basal and luminal counterparts. We show that these cell types are substantially inter-dependent, since the MMTV LTR drives expression of Wnt1 ligand in luminal cells, whereas the functional Wnt1-responsive receptor (Lrp5) is expressed by basal cells, and both molecules are necessary for tumor growth. There is a robust tumor initiating activity (tumor stem cell) in the basal cell population, which is associated with the ability to differentiate into luminal and basal cells, to regenerate the oncogenic paracrine signaling cell pair. However, we found an additional tumor stem cell activity in the luminal cell population. Knowing that tumors depend upon Wnt1-Lrp5, we hypothesized that this stem cell must express Lrp5, and found that indeed, all the stem cell activity could be retrieved from the Lrp5-positive cell population. Interestingly, this reflects post-transcriptional acquisition of Lrp5 protein expression in luminal cells. Furthermore, this plasticity of molecular expression is reflected in plasticity of cell fate determination. Thus, in vitro, Wnt1-expressing luminal cells retro-differentiate to basal cell types, and in vivo, tumors initiated with pure luminal cells reconstitute a robust basal cell subpopulation that is indistinguishable from the populations initiated by pure basal cells. We propose this is an important proof of concept, demonstrating that bipotential tumor stem cells are essential in tumors where oncogenic ligand-receptor pairs are separated into different cell types, and suggesting that Wnt-induced molecular and fate plasticity can close paracrine loops that are usually separated into distinct cell types. PMID:21541292

Adoptive cell transfer in autoimmune hepatitis.

PubMed

Czaja, Albert J

2015-06-01

Adoptive cell transfer is an intervention in which autologous immune cells that have been expanded ex vivo are re-introduced to mitigate a pathological process. Tregs, mesenchymal stromal cells, dendritic cells, macrophages and myeloid-derived suppressor cells have been transferred in diverse immune-mediated diseases, and Tregs have been the focus of investigations in autoimmune hepatitis. Transferred Tregs have improved histological findings in animal models of autoimmune hepatitis and autoimmune cholangitis. Key challenges relate to discrepant findings among studies, phenotypic instability of the transferred population, uncertain side effects and possible need for staged therapy involving anti-inflammatory drugs. Future investigations must resolve issues about the purification, durability and safety of these cells and consider alternative populations if necessary.

Modeled Microgravity Inhibits Apoptosis in Peripheral Blood Lymphocytes

NASA Technical Reports Server (NTRS)

Risin, Diana; Pellis, Neal R.

2000-01-01

Microgravity interferes with numerous lymphocyte functions (expression of cell surface molecules, locomotion, polyclonal and antigen-specific activation, and the protein kinase C activity in signal transduction). The latter suggests that gravity may also affect programmed cell death (PCD) in lymphocyte populations. To test this hypothesis, we investigated spontaneous, activation- and radiation-induced PCD in peripheral blood mononuclear cells (PBMC) exposed to modeled microgravity using a rotating cell culture system. The results showed significant inhibition of radiation- and activation-induced apoptosis in modeled microgravity and provide insights into the potential mechanisms of this phenomenon.

Head and Neck Cancer Stem Cells: The Side Population

PubMed Central

Tabor, Mark H.; Clay, Matthew R.; Owen, John H.; Bradford, Carol R.; Carey, Thomas E.; Wolf, Gregory T.; Prince, Mark E.P.

2014-01-01

Background The cancer stem cell (CSC) hypothesis concludes that a subpopulation of tumor cells can self-renew, causing tumor growth, treatment failure, and recurrence. Several tumor studies have identified cells able to efflux Hoechst 33342 dye; the side population (SP). SP cells and CSCs share many characteristics, suggesting the SP isolated from malignant tumors contains CSCs. Methods The SP was isolated from a head and neck cancer cell line and analyzed for CSC-like characteristics. Results The SP demonstrated the ability to reproduce both SP and non-side population (NSP) cells from as few as one cell. The SP had lower expression of active β-catenin and more resistance to 5-Fluorouracil; the SP also demonstrated greater expression of BMI-1 (4.3-fold) and ABCG2 (1.4-fold). SPs were identified in 2 primary human tumors. Conclusions The SP in head and neck cancer cell lines may serve as a valuable in-vitro model for CSCs leading to the development of novel treatment strategies. PMID:21344428

Strategic priming with multiple antigens can yield memory cell phenotypes optimized for infection with Mycobacterium tuberculosis: A computational study

DOE PAGES

Ziraldo, Cordelia; Gong, Chang; Kirschner, Denise E.; ...

2016-01-06

Lack of an effective vaccine results in 9 million new cases of tuberculosis (TB) every year and 1.8 million deaths worldwide. While many infants are vaccinated at birth with BCG (an attenuated M. bovis), this does not prevent infection or development of TB after childhood. Immune responses necessary for prevention of infection or disease are still unknown, making development of effective vaccines against TB challenging. Several new vaccines are ready for human clinical trials, but these trials are difficult and expensive; especially challenging is determining the appropriate cellular response necessary for protection. The magnitude of an immune response is likelymore » key to generating a successful vaccine. Characteristics such as numbers of central memory (CM) and effector memory (EM) T cells responsive to a diverse set of epitopes are also correlated with protection. Promising vaccines against TB contain mycobacterial subunit antigens (Ag) present during both active and latent infection. We hypothesize that protection against different key immunodominant antigens could require a vaccine that produces different levels of EM and CM for each Ag-specific memory population. We created a computational model to explore EM and CM values, and their ratio, within what we term Memory Design Space. Our model captures events involved in T cell priming within lymph nodes and tracks their circulation through blood to peripheral tissues. We used the model to test whether multiple Ag-specific memory cell populations could be generated with distinct locations within Memory Design Space at a specific time point post vaccination. Boosting can further shift memory populations to memory cell ratios unreachable by initial priming events. By strategically varying antigen load, properties of cellular interactions within the LN, and delivery parameters (e.g., number of boosts) of multi-subunit vaccines, we can generate multiple Ag-specific memory populations that cover a wide range of Memory Design Space. As a result, given a set of desired characteristics for Ag-specific memory populations, we can use our model as a tool to predict vaccine formulations that will generate those populations.« less

Strategic priming with multiple antigens can yield memory cell phenotypes optimized for infection with Mycobacterium tuberculosis: A computational study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ziraldo, Cordelia; Gong, Chang; Kirschner, Denise E.

Lack of an effective vaccine results in 9 million new cases of tuberculosis (TB) every year and 1.8 million deaths worldwide. While many infants are vaccinated at birth with BCG (an attenuated M. bovis), this does not prevent infection or development of TB after childhood. Immune responses necessary for prevention of infection or disease are still unknown, making development of effective vaccines against TB challenging. Several new vaccines are ready for human clinical trials, but these trials are difficult and expensive; especially challenging is determining the appropriate cellular response necessary for protection. The magnitude of an immune response is likelymore » key to generating a successful vaccine. Characteristics such as numbers of central memory (CM) and effector memory (EM) T cells responsive to a diverse set of epitopes are also correlated with protection. Promising vaccines against TB contain mycobacterial subunit antigens (Ag) present during both active and latent infection. We hypothesize that protection against different key immunodominant antigens could require a vaccine that produces different levels of EM and CM for each Ag-specific memory population. We created a computational model to explore EM and CM values, and their ratio, within what we term Memory Design Space. Our model captures events involved in T cell priming within lymph nodes and tracks their circulation through blood to peripheral tissues. We used the model to test whether multiple Ag-specific memory cell populations could be generated with distinct locations within Memory Design Space at a specific time point post vaccination. Boosting can further shift memory populations to memory cell ratios unreachable by initial priming events. By strategically varying antigen load, properties of cellular interactions within the LN, and delivery parameters (e.g., number of boosts) of multi-subunit vaccines, we can generate multiple Ag-specific memory populations that cover a wide range of Memory Design Space. As a result, given a set of desired characteristics for Ag-specific memory populations, we can use our model as a tool to predict vaccine formulations that will generate those populations.« less

Androgen deprivation and stem cell markers in prostate cancers

PubMed Central

Tang, Yao; Hamburger, Anne W; Wang, Linbo; Khan, Mohammad Afnan; Hussain, Arif

2010-01-01

In our previous studies using human LNCaP xenografts and TRAMP (transgenic adenocarcinoma of mouse prostate) mice, androgen deprivation therapy (ADT) resulted in a temporary cessation of prostate cancer (PCa) growth, but then tumors grew faster with more malignant behaviour. To understand whether cancer stem cells might play a role in PCa progression in these animal models, we investigated the expressions of stem cell-related markers in tumors at different time points after ADT. In both animal models, enhanced expressions of stem cell markers were observed in tumors of castrated mice, as compared to non-castrated controls. This increased cell population that expressed stem cell markers is designated as stem-like cells (SLC) in this article. We also observed that the SLC peaked at relatively early time points after ADT, before tumors resumed their growth. These results suggest that the SLC population may play a role in tumor re-growth and disease progression, and that targeting the SLC at their peak-expression time point may prevent tumor recurrence following ADT. PMID:20126580

Generation of Regionally Specific Neural Progenitor Cells (NPCs) and Neurons from Human Pluripotent Stem Cells (hPSCs).

PubMed

Cutts, Josh; Brookhouser, Nicholas; Brafman, David A

2016-01-01

Neural progenitor cells (NPCs) derived from human pluripotent stem cells (hPSCs) are a multipotent cell population capable of long-term expansion and differentiation into a variety of neuronal subtypes. As such, NPCs have tremendous potential for disease modeling, drug screening, and regenerative medicine. Current methods for the generation of NPCs results in cell populations homogenous for pan-neural markers such as SOX1 and SOX2 but heterogeneous with respect to regional identity. In order to use NPCs and their neuronal derivatives to investigate mechanisms of neurological disorders and develop more physiologically relevant disease models, methods for generation of regionally specific NPCs and neurons are needed. Here, we describe a protocol in which exogenous manipulation of WNT signaling, through either activation or inhibition, during neural differentiation of hPSCs, promotes the formation of regionally homogenous NPCs and neuronal cultures. In addition, we provide methods to monitor and characterize the efficiency of hPSC differentiation to these regionally specific cell identities.

Cell population structure prior to bifurcation predicts efficiency of directed differentiation in human induced pluripotent cells

PubMed Central

Bargaje, Rhishikesh; Trachana, Kalliopi; Shelton, Martin N.; McGinnis, Christopher S.; Zhou, Joseph X.; Chadick, Cora; Cook, Savannah; Cavanaugh, Christopher; Huang, Sui; Hood, Leroy

2017-01-01

Steering the differentiation of induced pluripotent stem cells (iPSCs) toward specific cell types is crucial for patient-specific disease modeling and drug testing. This effort requires the capacity to predict and control when and how multipotent progenitor cells commit to the desired cell fate. Cell fate commitment represents a critical state transition or “tipping point” at which complex systems undergo a sudden qualitative shift. To characterize such transitions during iPSC to cardiomyocyte differentiation, we analyzed the gene expression patterns of 96 developmental genes at single-cell resolution. We identified a bifurcation event early in the trajectory when a primitive streak-like cell population segregated into the mesodermal and endodermal lineages. Before this branching point, we could detect the signature of an imminent critical transition: increase in cell heterogeneity and coordination of gene expression. Correlation analysis of gene expression profiles at the tipping point indicates transcription factors that drive the state transition toward each alternative cell fate and their relationships with specific phenotypic readouts. The latter helps us to facilitate small molecule screening for differentiation efficiency. To this end, we set up an analysis of cell population structure at the tipping point after systematic variation of the protocol to bias the differentiation toward mesodermal or endodermal cell lineage. We were able to predict the proportion of cardiomyocytes many days before cells manifest the differentiated phenotype. The analysis of cell populations undergoing a critical state transition thus affords a tool to forecast cell fate outcomes and can be used to optimize differentiation protocols to obtain desired cell populations. PMID:28167799

Cell population structure prior to bifurcation predicts efficiency of directed differentiation in human induced pluripotent cells.

PubMed

Bargaje, Rhishikesh; Trachana, Kalliopi; Shelton, Martin N; McGinnis, Christopher S; Zhou, Joseph X; Chadick, Cora; Cook, Savannah; Cavanaugh, Christopher; Huang, Sui; Hood, Leroy

2017-02-28

Steering the differentiation of induced pluripotent stem cells (iPSCs) toward specific cell types is crucial for patient-specific disease modeling and drug testing. This effort requires the capacity to predict and control when and how multipotent progenitor cells commit to the desired cell fate. Cell fate commitment represents a critical state transition or "tipping point" at which complex systems undergo a sudden qualitative shift. To characterize such transitions during iPSC to cardiomyocyte differentiation, we analyzed the gene expression patterns of 96 developmental genes at single-cell resolution. We identified a bifurcation event early in the trajectory when a primitive streak-like cell population segregated into the mesodermal and endodermal lineages. Before this branching point, we could detect the signature of an imminent critical transition: increase in cell heterogeneity and coordination of gene expression. Correlation analysis of gene expression profiles at the tipping point indicates transcription factors that drive the state transition toward each alternative cell fate and their relationships with specific phenotypic readouts. The latter helps us to facilitate small molecule screening for differentiation efficiency. To this end, we set up an analysis of cell population structure at the tipping point after systematic variation of the protocol to bias the differentiation toward mesodermal or endodermal cell lineage. We were able to predict the proportion of cardiomyocytes many days before cells manifest the differentiated phenotype. The analysis of cell populations undergoing a critical state transition thus affords a tool to forecast cell fate outcomes and can be used to optimize differentiation protocols to obtain desired cell populations.

Live Imaging-Based Model Selection Reveals Periodic Regulation of the Stochastic G1/S Phase Transition in Vertebrate Axial Development

PubMed Central

Kurokawa, Hiroshi; Sakaue-Sawano, Asako; Imamura, Takeshi; Miyawaki, Atsushi; Iimura, Tadahiro

2014-01-01

In multicellular organism development, a stochastic cellular response is observed, even when a population of cells is exposed to the same environmental conditions. Retrieving the spatiotemporal regulatory mode hidden in the heterogeneous cellular behavior is a challenging task. The G1/S transition observed in cell cycle progression is a highly stochastic process. By taking advantage of a fluorescence cell cycle indicator, Fucci technology, we aimed to unveil a hidden regulatory mode of cell cycle progression in developing zebrafish. Fluorescence live imaging of Cecyil, a zebrafish line genetically expressing Fucci, demonstrated that newly formed notochordal cells from the posterior tip of the embryonic mesoderm exhibited the red (G1) fluorescence signal in the developing notochord. Prior to their initial vacuolation, these cells showed a fluorescence color switch from red to green, indicating G1/S transitions. This G1/S transition did not occur in a synchronous manner, but rather exhibited a stochastic process, since a mixed population of red and green cells was always inserted between newly formed red (G1) notochordal cells and vacuolating green cells. We termed this mixed population of notochordal cells, the G1/S transition window. We first performed quantitative analyses of live imaging data and a numerical estimation of the probability of the G1/S transition, which demonstrated the existence of a posteriorly traveling regulatory wave of the G1/S transition window. To obtain a better understanding of this regulatory mode, we constructed a mathematical model and performed a model selection by comparing the results obtained from the models with those from the experimental data. Our analyses demonstrated that the stochastic G1/S transition window in the notochord travels posteriorly in a periodic fashion, with doubled the periodicity of the neighboring paraxial mesoderm segmentation. This approach may have implications for the characterization of the pathophysiological tissue growth mode. PMID:25474567

A generalized model for multi-marker analysis of cell cycle progression in synchrony experiments

PubMed Central

Mayhew, Michael B.; Robinson, Joshua W.; Jung, Boyoun; Haase, Steven B.; Hartemink, Alexander J.

2011-01-01

Motivation: To advance understanding of eukaryotic cell division, it is important to observe the process precisely. To this end, researchers monitor changes in dividing cells as they traverse the cell cycle, with the presence or absence of morphological or genetic markers indicating a cell's position in a particular interval of the cell cycle. A wide variety of marker data is available, including information-rich cellular imaging data. However, few formal statistical methods have been developed to use these valuable data sources in estimating how a population of cells progresses through the cell cycle. Furthermore, existing methods are designed to handle only a single binary marker of cell cycle progression at a time. Consequently, they cannot facilitate comparison of experiments involving different sets of markers. Results: Here, we develop a new sampling model to accommodate an arbitrary number of different binary markers that characterize the progression of a population of dividing cells along a branching process. We engineer a strain of Saccharomyces cerevisiae with fluorescently labeled markers of cell cycle progression, and apply our new model to two image datasets we collected from the strain, as well as an independent dataset of different markers. We use our model to estimate the duration of post-cytokinetic attachment between a S.cerevisiae mother and daughter cell. The Java implementation is fast and extensible, and includes a graphical user interface. Our model provides a powerful and flexible cell cycle analysis tool, suitable to any type or combination of binary markers. Availability: The software is available from: http://www.cs.duke.edu/~amink/software/cloccs/. Contact: michael.mayhew@duke.edu; amink@cs.duke.edu PMID:21685084

An Animal Model of Chronic Aplastic Bone Marrow Failure Following Pesticide Exposure in Mice

PubMed Central

Chatterjee, Sumanta; Chaklader, Malay; Basak, Pratima; Das, Prosun; Das, Madhurima; Pereira, Jacintha Archana; Dutta, Ranjan Kumar; Chaudhuri, Samaresh; Law, Sujata

2010-01-01

The wide use of pesticides for agriculture, domestic and industrial purposes and evaluation of their subsequent effect is of major concern for public health. Human exposure to these contaminants especially bone marrow with its rapidly renewing cell population is one of the most sensitive tissues to these toxic agents represents a risk for the immune system leading to the onset of different pathologies. In this experimental protocol we have developed a mouse model of pesticide(s) induced hypoplastic/aplastic marrow failure to study quantitative changes in the bone marrow hematopoietic stem cell (BMHSC) population through flowcytometric analysis, defects in the stromal microenvironment through short term adherent cell colony (STACC) forming assay and immune functional capacity of the bone marrow derived cells through cell mediated immune (CMI) parameter study. A time course dependent analysis for consecutive 90 days were performed to monitor the associated changes in the marrow’s physiology after 30th, 60th and 90th days of chronic pesticide exposure. The peripheral blood showed maximum lowering of the blood cell count after 90 days which actually reflected the bone marrow scenario. Severe depression of BMHSC population, immune profile of the bone marrow derived cells and reduction of adherent cell colonies pointed towards an essentially empty and hypoplastic marrow condition that resembled the disease aplastic anemia. The changes were accompanied by splenomegaly and splenic erythroid hyperplasia. In conclusion, this animal model allowed us a better understanding of clinico-biological findings of the disease aplastic anemia following toxic exposure to the pesticide(s) used for agricultural and industrial purposes. PMID:24855541

Combining magnetic sorting of mother cells and fluctuation tests to analyze genome instability during mitotic cell aging in Saccharomyces cerevisiae.

PubMed

Patterson, Melissa N; Maxwell, Patrick H

2014-10-16

Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on mutation accumulation to address mechanisms underlying genome instability during replicative aging.

Embryoid body attachment to reconstituted basement membrane induces a genetic program of epithelial differentiation via jun N-terminal kinase signaling.

PubMed

Ho, Hoang-Yen; Moffat, Ryan C; Patel, Rupal V; Awah, Franklin N; Baloue, Kaitrin; Crowe, David L

2010-09-01

Embryonic stem (ES) cells are derived from early stage mammalian embryos and have broad developmental potential. These cells can be manipulated experimentally to generate cells of multiple tissue types which could be important in treating human diseases. The ability to produce relevant amounts of these differentiated cell populations creates the basis for clinical interventions in tissue regeneration and repair. Understanding how embryonic stem cells differentiate also can reveal important insights into cell biology. A previously reported mouse embryonic stem cell model demonstrated that differentiated epithelial cells migrated out of embryoid bodies attached to reconstituted basement membrane. We used genomic technology to profile ES cell populations in order to understand the molecular mechanisms leading to epithelial differentiation. Cells with characteristics of cultured epithelium migrated from embryoid bodies attached to reconstituted basement membrane. However, cells that comprised embryoid bodies also rapidly lost ES cell-specific gene expression and expressed proteins characteristic of stratified epithelia within hours of attachment to basement membrane. Gene expression profiling of sorted cell populations revealed upregulation of the BMP/TGFbeta signaling pathway, which was not sufficient for epithelial differentiation in the absence of basement membrane attachment. Activation of c-jun N-terminal kinase 1 (JNK1) and increased expression of Jun family transcription factors was observed during epithelial differentiation of ES cells. Inhibition of JNK signaling completely blocked epithelial differentiation in this model, revealing a key mechanism by which ES cells adopt epithelial characteristics via basement membrane attachment. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Immune Tolerance Maintained by Cooperative Interactions between T Cells and Antigen Presenting Cells Shapes a Diverse TCR Repertoire

PubMed Central

Best, Katharine; Chain, Benny; Watkins, Chris

2015-01-01

The T cell population in an individual needs to avoid harmful activation by self peptides while maintaining the ability to respond to an unknown set of foreign peptides. This property is acquired by a combination of thymic and extra-thymic mechanisms. We extend current models for the development of self/non-self discrimination to consider the acquisition of self-tolerance as an emergent system level property of the overall T cell receptor repertoire. We propose that tolerance is established at the level of the antigen presenting cell/T cell cluster, which facilitates and integrates cooperative interactions between T cells of different specificities. The threshold for self-reactivity is therefore imposed at a population level, and not at the level of the individual T cell/antigen encounter. Mathematically, the model can be formulated as a linear programing optimization problem that can be implemented as a multiplicative update algorithm, which shows a rapid convergence to a stable state. The model constrains self-reactivity within a predefined threshold, but maintains repertoire diversity and cross reactivity which are key characteristics of human T cell immunity. We show further that the size of individual clones in the model repertoire becomes heterogeneous, and that new clones can establish themselves even when the repertoire has stabilized. Our study combines the salient features of the “danger” model of self/non-self discrimination with the concepts of quorum sensing, and extends repertoire generation models to encompass the establishment of tolerance. Furthermore, the dynamic and continuous repertoire reshaping, which underlies tolerance in this model, suggests opportunities for therapeutic intervention to achieve long-term tolerance following transplantation. PMID:26300880

Modeling the winter-to-summer transition of prokaryotic and viral abundance in the Arctic Ocean.

PubMed

Winter, Christian; Payet, Jérôme P; Suttle, Curtis A

2012-01-01

One of the challenges in oceanography is to understand the influence of environmental factors on the abundances of prokaryotes and viruses. Generally, conventional statistical methods resolve trends well, but more complex relationships are difficult to explore. In such cases, Artificial Neural Networks (ANNs) offer an alternative way for data analysis. Here, we developed ANN-based models of prokaryotic and viral abundances in the Arctic Ocean. The models were used to identify the best predictors for prokaryotic and viral abundances including cytometrically-distinguishable populations of prokaryotes (high and low nucleic acid cells) and viruses (high- and low-fluorescent viruses) among salinity, temperature, depth, day length, and the concentration of Chlorophyll-a. The best performing ANNs to model the abundances of high and low nucleic acid cells used temperature and Chl-a as input parameters, while the abundances of high- and low-fluorescent viruses used depth, Chl-a, and day length as input parameters. Decreasing viral abundance with increasing depth and decreasing system productivity was captured well by the ANNs. Despite identifying the same predictors for the two populations of prokaryotes and viruses, respectively, the structure of the best performing ANNs differed between high and low nucleic acid cells and between high- and low-fluorescent viruses. Also, the two prokaryotic and viral groups responded differently to changes in the predictor parameters; hence, the cytometric distinction between these populations is ecologically relevant. The models imply that temperature is the main factor explaining most of the variation in the abundances of high nucleic acid cells and total prokaryotes and that the mechanisms governing the reaction to changes in the environment are distinctly different among the prokaryotic and viral populations.

Modeling the Winter–to–Summer Transition of Prokaryotic and Viral Abundance in the Arctic Ocean

PubMed Central

Winter, Christian; Payet, Jérôme P.; Suttle, Curtis A.

2012-01-01

One of the challenges in oceanography is to understand the influence of environmental factors on the abundances of prokaryotes and viruses. Generally, conventional statistical methods resolve trends well, but more complex relationships are difficult to explore. In such cases, Artificial Neural Networks (ANNs) offer an alternative way for data analysis. Here, we developed ANN-based models of prokaryotic and viral abundances in the Arctic Ocean. The models were used to identify the best predictors for prokaryotic and viral abundances including cytometrically-distinguishable populations of prokaryotes (high and low nucleic acid cells) and viruses (high- and low-fluorescent viruses) among salinity, temperature, depth, day length, and the concentration of Chlorophyll-a. The best performing ANNs to model the abundances of high and low nucleic acid cells used temperature and Chl-a as input parameters, while the abundances of high- and low-fluorescent viruses used depth, Chl-a, and day length as input parameters. Decreasing viral abundance with increasing depth and decreasing system productivity was captured well by the ANNs. Despite identifying the same predictors for the two populations of prokaryotes and viruses, respectively, the structure of the best performing ANNs differed between high and low nucleic acid cells and between high- and low-fluorescent viruses. Also, the two prokaryotic and viral groups responded differently to changes in the predictor parameters; hence, the cytometric distinction between these populations is ecologically relevant. The models imply that temperature is the main factor explaining most of the variation in the abundances of high nucleic acid cells and total prokaryotes and that the mechanisms governing the reaction to changes in the environment are distinctly different among the prokaryotic and viral populations. PMID:23285186

Choosing an Appropriate Modelling Framework for Analysing Multispecies Co-culture Cell Biology Experiments.

PubMed

Markham, Deborah C; Simpson, Matthew J; Baker, Ruth E

2015-04-01

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insufficient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

The effects of restricted glycolysis on stem-cell like characteristics of breast cancer cells

PubMed Central

Banerjee, Arindam; Arvinrad, Pardis; Darley, Matthew; Laversin, Stéphanie A.; Parker, Rachel; Rose-Zerilli, Matthew J.J.; Townsend, Paul A.; Cutress, Ramsey I.; Beers, Stephen A.; Houghton, Franchesca D.; Birts, Charles N.; Blaydes, Jeremy P.

2018-01-01

Altered glycolysis is a characteristic of many cancers, and can also be associated with changes in stem cell-like cancer (SCLC) cell populations. We therefore set out to directly examine the effect of glycolysis on SCLC cell phenotype, using a model where glycolysis is stably reduced by adapting the cells to a sugar source other than glucose. Restricting glycolysis using this approach consistently resulted in cells with increased oncogenic potential; including an increase in SCLC cells, proliferation in 3D matrigel, invasiveness, chemoresistance, and altered global gene expression. Tumorigenicity in vivo was also markedly increased. SCLC cells exhibited increased dependence upon alternate metabolic pathways. They also became c-KIT dependent, indicating that their apparent state of maturation is regulated by glycolysis. Single-cell mRNA sequencing identified altered networks of metabolic-, stem- and signaling- gene expression within SCLC-enriched populations in response to glycolytic restriction. Therefore, reduced glycolysis, which may occur in niches within tumors where glucose availability is limiting, can promote tumor aggressiveness by increasing SCLC cell populations, but can also introduce novel, potentially exploitable, vulnerabilities in SCLC cells. PMID:29796188

Improving dynamic phytoplankton reserve-utilization models with an indirect proxy for internal nitrogen.

PubMed

Malerba, Martino E; Heimann, Kirsten; Connolly, Sean R

2016-09-07

Ecologists have often used indirect proxies to represent variables that are difficult or impossible to measure directly. In phytoplankton, the internal concentration of the most limiting nutrient in a cell determines its growth rate. However, directly measuring the concentration of nutrients within cells is inaccurate, expensive, destructive, and time-consuming, substantially impairing our ability to model growth rates in nutrient-limited phytoplankton populations. The red chlorophyll autofluorescence (hereafter "red fluorescence") signal emitted by a cell is highly correlated with nitrogen quota in nitrogen-limited phytoplankton species. The aim of this study was to evaluate the reliability of including flow cytometric red fluorescence as a proxy for internal nitrogen status to model phytoplankton growth rates. To this end, we used the classic Quota model and designed three approaches to calibrate its model parameters to data: where empirical observations on cell internal nitrogen quota were used to fit the model ("Nitrogen-Quota approach"), where quota dynamics were inferred only from changes in medium nutrient depletion and population density ("Virtual-Quota approach"), or where red fluorescence emission of a cell was used as an indirect proxy for its internal nitrogen quota ("Fluorescence-Quota approach"). Two separate analyses were carried out. In the first analysis, stochastic model simulations were parameterized from published empirical relationships and used to generate dynamics of phytoplankton communities reared under nitrogen-limited conditions. Quota models were fitted to the dynamics of each simulated species with the three different approaches and the performance of each model was compared. In the second analysis, we fit Quota models to laboratory time-series and we calculate the ability of each calibration approach to describe the observed trajectories of internal nitrogen quota in the culture. Results from both analyses concluded that the Fluorescence-Quota approach including per-cell red fluorescence as a proxy of internal nitrogen substantially improved the ability of Quota models to describe phytoplankton dynamics, while still accounting for the biologically important process of cell nitrogen storage. More broadly, many population models in ecology implicitly recognize the importance of accounting for storage mechanisms to describe the dynamics of individual organisms. Hence, the approach documented here with phytoplankton dynamics may also be useful for evaluating the potential of indirect proxies in other ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Detection and isolation of rare cells by 2-step enrichment high-speed flow cytometry/cell sorting and single cell LEAP laser ablation

NASA Astrophysics Data System (ADS)

Zordan, M. D.; Leary, James F.

2011-02-01

The clonal isolation of rare cells, especially cancer and stem cells, in a population is important to the development of improved medical treatment. We have demonstrated that the Laser-Enabled Analysis and Processing (LEAP, Cyntellect Inc., San Diego, CA) instrument can be used to efficiently produce single cell clones by photoablative dilution. Additionally, we have also shown that cells present at low frequencies can be cloned by photoablative dilution after they are pre-enriched by flow cytometry based cell sorting. Circulating tumor cells were modeled by spiking isolated peripheral blood cells with cells from the lung carcinoma cell line A549. Flow cytometry based cell sorting was used to perform an enrichment sort of A549 cells directly into a 384 well plate. Photoablative dilution was performed with the LEAPTM instrument to remove any contaminating cells, and clonally isolate 1 side population cell per well. We were able to isolate and grow single clones of side population cells using this method at greater than 90% efficiency. We have developed a 2 step method that is able to perform the clonal isolation of rare cells based on a medically relevant functional phenotype.

Cellular aging (the Hayflick limit) and species longevity: a unification model based on clonal succession.

PubMed

Juckett, D A

1987-03-01

A model is presented which proposes a specific cause-and-effect relationship between a limited cell division potential and the maximum lifespan of humans and other mammals. It is based on the clonal succession hypothesis of Kay which states that continually replicating cell beds (e.g. bone marrow, intestinal crypts, epidermis) could be composed of cells with short, well-defined division potentials. In this model, the cells of these beds are proposed to exist in an ordered hierarchy which establishes a specific sequence for cell divisions throughout the organism's lifespan. The depletion of division potential at all hierarchical levels leads to a loss of bed function and sets an intrinsic limit to species longevity. A specific hierarchy for cell proliferation is defined which allows the calculation of time to bed depletion and, ultimately, to organism mortality. The model allows the existence of a small number (n) of critical cell beds within the organism and defines organism death as the inability of any one of these beds to produce cells. The model is consistent with all major observations related to cellular and organismic aging. In particular, it links the PDLs (population doubling limit) observed for various species to their mean lifespan; it explains the slow decline in PDL as a function of age of the donor; it establishes a thermodynamically stable maximum lifespan for a disease-free population; and it can explain why tissue transplants outlive donors or hosts.

Changes in the population of perivascular cells in the bone tissue remodeling zones under microgravity

NASA Astrophysics Data System (ADS)

Katkova, Olena; Rodionova, Natalia; Shevel, Ivan

2016-07-01

Microgravity and long-term hypokinesia induce reduction both in bone mass and mineral saturation, which can lead to the development of osteoporosis and osteopenia. (Oganov, 2003). Reorganizations and adaptive remodeling processes in the skeleton bones occur in the topographical interconnection with blood capillaries and perivascular cells. Radioautographic studies with 3H- thymidine (Kimmel, Fee, 1980; Rodionova, 1989, 2006) have shown that in osteogenesis zones there is sequential differentiation process of the perivascular cells into osteogenic. Hence the study of populations of perivascular stromal cells in areas of destructive changes is actual. Perivascular cells from metaphysis of the rat femoral bones under conditions of modeling microgravity were studied using electron microscopy and cytochemistry (hindlimb unloading, 28 days duration) and biosatellite «Bion-M1» (duration of flight from April 19 till May 19, 2013 on C57, black mice). It was revealed that both control and test groups populations of the perivascular cells are not homogeneous in remodeling adaptive zones. These populations comprise of adjacent to endothelium poorly differentiated forms and isolated cells with signs of differentiation (specific increased volume of rough endoplasmic reticulum in cytoplasm). Majority of the perivascular cells in the control group (modeling microgravity) reveals reaction to alkaline phosphatase (marker of the osteogenic differentiation). In poorly differentiated cells this reaction is registered in nucleolus, nucleous and cytoplasm. In differentiating cells activity of the alkaline phosphatase is also detected on the outer surface of the cellular membrane. Unlike the control group in the bones of experimental animals reaction to the alkaline phosphatase is registered not in all cells of perivascular population. Part of the differentiating perivascular cells does not contain a product of the reaction. Under microgravity some poorly differentiated perivascular cells reveal signs of destruction. Thus it was found that number of the alkaline phosphatase containing cells (i.e. osteogenic cells) declines in perivascular cells population. It is one of the mechanisms of the osteogenic process decrease of intensity in bones because of lessening support loading on the bone skeleton. In the adaptive remodeling zones of bone tissue (near the vascular canals) in experiments fibroblasts and fibrosis zones were found - areas filled with non-mineralized collagen fibrils on the bones surfaces. Hence it should be considered that decrease (removal) of support loading slows down osteogenic differentiation of the part of perivascular cells and stimulates differentiation of the fibroblast cells. Obtained data is considered as one of the cellular mechanisms of the adaptive reactions development in spongy bone under microgravity which could lead to the bone mass loss.

Reconstructing human pancreatic differentiation by mapping specific cell populations during development.

PubMed

Ramond, Cyrille; Glaser, Nicolas; Berthault, Claire; Ameri, Jacqueline; Kirkegaard, Jeannette Schlichting; Hansson, Mattias; Honoré, Christian; Semb, Henrik; Scharfmann, Raphaël

2017-07-21

Information remains scarce on human development compared to animal models. Here, we reconstructed human fetal pancreatic differentiation using cell surface markers. We demonstrate that at 7weeks of development, the glycoprotein 2 (GP2) marks a multipotent cell population that will differentiate into the acinar, ductal or endocrine lineages. Development towards the acinar lineage is paralleled by an increase in GP2 expression. Conversely, a subset of the GP2 + population undergoes endocrine differentiation by down-regulating GP2 and CD142 and turning on NEUROG3 , a marker of endocrine differentiation. Endocrine maturation progresses by up-regulating SUSD2 and lowering ECAD levels. Finally, in vitro differentiation of pancreatic endocrine cells derived from human pluripotent stem cells mimics key in vivo events. Our work paves the way to extend our understanding of the origin of mature human pancreatic cell types and how such lineage decisions are regulated.

Complex dynamics of selection and cellular memory in adaptation to a changing environment

NASA Astrophysics Data System (ADS)

Kussell, Edo; Lin, Wei-Hsiang

We study a synthetic evolutionary system in bacteria in which an antibiotic resistance gene is controlled by a stochastic on/off switching promoter. At the population level, this system displays all the basic ingredients for evolutionary selection, including diversity, fitness differences, and heritability. At the single cell level, physiological processes can modulate the ability of selection to act. We expose the stochastic switching strains to pulses of antibiotics of different durations in periodically changing environments using microfluidics. Small populations are tracked over a large number of periods at single cell resolution, allowing the visualization and quantification of selective sweeps and counter-sweeps at the population level, as well as detailed single cell analysis. A simple model is introduced to predict long-term population growth rates from single cell measurements, and reveals unexpected aspects of population dynamics, including cellular memory that acts on a fast timescale to modulate growth rates. This work is supported by NIH Grant No. R01-GM097356.

THE GERMLINE STEM CELL NICHE UNIT IN MAMMALIAN TESTES

PubMed Central

Oatley, Jon M.; Brinster, Ralph L.

2014-01-01

This review addresses current understanding of the germline stem cell niche unit in mammalian testes. Spermatogenesis is a classic model of tissue-specific stem cell function relying on self-renewal and differentiation of spermatogonial stem cells (SSCs). These fate decisions are influenced by a niche microenvironment composed of a growth factor milieu that is provided by several testis somatic support cell populations. Investigations over the last two decades have identified key determinants of the SSC niche including cytokines that regulate SSC functions and support cells providing these factors, adhesion molecules that influence SSC homing, and developmental heterogeneity of the niche during postnatal aging. Emerging evidence suggests that Sertoli cells are a key support cell population influencing the formation and function of niches by secreting soluble factors and possibly orchestrating contributions of other support cells. Investigations with mice have shown that niche influence on SSC proliferation differs during early postnatal development and adulthood. Moreover, there is mounting evidence of an age-related decline in niche function, which is likely influenced by systemic factors. Defining the attributes of stem cell niches is key to developing methods to utilize these cells for regenerative medicine. The SSC population and associated niche comprise a valuable model system for study that provides fundamental knowledge about the biology of tissue-specific stem cells and their capacity to sustain homeostasis of regenerating tissue lineages. While the stem cell is essential for maintenance of all self-renewing tissues and has received considerable attention, the role of niche cells is at least as important and may prove to be more receptive to modification in regenerative medicine. PMID:22535892

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

PubMed

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

PubMed Central

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity. PMID:28060865

Zonal hierarchy of differentiation markers and nestin expression during oval cell mediated rat liver regeneration.

PubMed

Koenig, Sarah; Probst, Irmelin; Becker, Heinz; Krause, Petra

2006-12-01

Oval cells constitute a heterogeneous population of proliferating progenitors found in rat livers following carcinogenic treatment (2-acetylaminofluorene and 70% hepatectomy). The aim of this study was to investigate the cellular pattern of various differentiation and cell type markers in this model of liver regeneration. Immunophenotypic characterisation revealed at least two subtypes emerging from the portal field. First, a population of oval cells formed duct-like structures and expressed bile duct (CD49f) as well as hepatocytic markers (alpha-foetoprotein, CD26). Second, a population of non-ductular oval cells was detected between and distally from the ductules expressing the neural marker nestin and the haematopoietic marker Thy1. Following oval cell isolation, a subset of the nestin-positive cells was shown to co-express hepatocytic and epithelial markers (albumin, CD26, pancytokeratin) and could be clearly distinguished from anti-desmin reactive hepatic stellate cells. The gene expression profiles (RT-PCR) of isolated oval cells and oval cell liver tissue were found to be similar to foetal liver (ED14). The present results suggest that the two oval cell populations are organised in a zonal hierarchy with a marker gradient from the inner (displaying hepatocytic and biliary markers) to the outer zone (showing hepatocytic and extrahepatic progenitor markers) of the proliferating progeny clusters.

Iterative sorting reveals CD133+ and CD133- melanoma cells as phenotypically distinct populations.

PubMed

Grasso, Carole; Anaka, Matthew; Hofmann, Oliver; Sompallae, Ramakrishna; Broadley, Kate; Hide, Winston; Berridge, Michael V; Cebon, Jonathan; Behren, Andreas; McConnell, Melanie J

2016-09-09

The heterogeneity and tumourigenicity of metastatic melanoma is attributed to a cancer stem cell model, with CD133 considered to be a cancer stem cell marker in melanoma as well as other tumours, but its role has remained controversial. We iteratively sorted CD133+ and CD133- cells from 3 metastatic melanoma cell lines, and observed tumourigenicity and phenotypic characteristics over 7 generations of serial xeno-transplantation in NOD/SCID mice. We demonstrate that iterative sorting is required to make highly pure populations of CD133+ and CD133- cells from metastatic melanoma, and that these two populations have distinct characteristics not related to the cancer stem cell phenotype. In vitro, gene set enrichment analysis indicated CD133+ cells were related to a proliferative phenotype, whereas CD133- cells were of an invasive phenotype. However, in vivo, serial transplantation of CD133+ and CD133- tumours over 7 generations showed that both populations were equally able to initiate and propagate tumours. Despite this, both populations remained phenotypically distinct, with CD133- cells only able to express CD133 in vivo and not in vitro. Loss of CD133 from the surface of a CD133+ cell was observed in vitro and in vivo, however CD133- cells derived from CD133+ retained the CD133+ phenotype, even in the presence of signals from the tumour microenvironment. We show for the first time the necessity of iterative sorting to isolate pure marker-positive and marker-negative populations for comparative studies, and present evidence that despite CD133+ and CD133- cells being equally tumourigenic, they display distinct phenotypic differences, suggesting CD133 may define a distinct lineage in melanoma.

Human TSCM cell dynamics in vivo are compatible with long-lived immunological memory and stemness.

PubMed

Del Amo, Pedro Costa; Beneytez, Julio Lahoz; Boelen, Lies; Ahmed, Raya; Miners, Kelly L; Zhang, Yan; Roger, Laureline; Jones, Rhiannon E; Marraco, Silvia A Fuertes; Speiser, Daniel E; Baird, Duncan M; Price, David A; Ladell, Kristin; Macallan, Derek; Asquith, Becca

2018-06-22

Adaptive immunity relies on the generation and maintenance of memory T cells to provide protection against repeated antigen exposure. It has been hypothesised that a self-renewing population of T cells, named stem cell-like memory T (TSCM) cells, are responsible for maintaining memory. However, it is not clear if the dynamics of TSCM cells in vivo are compatible with this hypothesis. To address this issue, we investigated the dynamics of TSCM cells under physiological conditions in humans in vivo using a multidisciplinary approach that combines mathematical modelling, stable isotope labelling, telomere length analysis, and cross-sectional data from vaccine recipients. We show that, unexpectedly, the average longevity of a TSCM clone is very short (half-life < 1 year, degree of self-renewal = 430 days): far too short to constitute a stem cell population. However, we also find that the TSCM population is comprised of at least 2 kinetically distinct subpopulations that turn over at different rates. Whilst one subpopulation is rapidly replaced (half-life = 5 months) and explains the rapid average turnover of the bulk TSCM population, the half-life of the other TSCM subpopulation is approximately 9 years, consistent with the longevity of the recall response. We also show that this latter population exhibited a high degree of self-renewal, with a cell residing without dying or differentiating for 15% of our lifetime. Finally, although small, the population was not subject to excessive stochasticity. We conclude that the majority of TSCM cells are not stem cell-like but that there is a subpopulation of TSCM cells whose dynamics are compatible with their putative role in the maintenance of T cell memory.

Infection Spread and Virus Release in Vitro in Cell Populations as a System with Percolation

NASA Astrophysics Data System (ADS)

Ochoa, Juan G. Diaz

The comprehension of the innate immune system of cell populations is not only of interest to understand systems in vivo but also in vitro, for example, in the control of the release of viral particles for the production of vaccines. In this report I introduce a model, based on dynamical networks, that simulates the cell signaling responsible for this innate immune response and its effect on the infection spread and virus production. The central motivation is to represent a cell population that is constantly mixed in a bio-reactor where there is a cell-to-cell signaling of cytokines (which are proteins responsible for the activation of the antiviral response inside the cell). Such signaling allows the definition of clusters of linked immune cells. Additionally, depending on the density of links, it is possible to identify critical threshold parameters associated to a percolation phase transition. I show that the control of this antiviral response is equivalent to a percolation process.

Game theory in the death galaxy: interaction of cancer and stromal cells in tumour microenvironment.

PubMed

Wu, Amy; Liao, David; Tlsty, Thea D; Sturm, James C; Austin, Robert H

2014-08-06

Preventing relapse is the major challenge to effective therapy in cancer. Within the tumour, stromal (ST) cells play an important role in cancer progression and the emergence of drug resistance. During cancer treatment, the fitness of cancer cells can be enhanced by ST cells because their molecular signalling interaction delays the drug-induced apoptosis of cancer cells. On the other hand, competition among cancer and ST cells for space or resources should not be ignored. We explore the population dynamics of multiple myeloma (MM) versus bone marrow ST cells by using an experimental microecology that we call the death galaxy, with a stable drug gradient and connected microhabitats. Evolutionary game theory is a quantitative way to capture the frequency-dependent nature of interactive populations. Therefore, we use evolutionary game theory to model the populations in the death galaxy with the gradients of pay-offs and successfully predict the future densities of MM and ST cells. We discuss the possible clinical use of such analysis for predicting cancer progression.

Division of Labor, Bet Hedging, and the Evolution of Mixed Biofilm Investment Strategies.

PubMed

Lowery, Nick Vallespir; McNally, Luke; Ratcliff, William C; Brown, Sam P

2017-08-08

Bacterial cells, like many other organisms, face a tradeoff between longevity and fecundity. Planktonic cells are fast growing and fragile, while biofilm cells are often slower growing but stress resistant. Here we ask why bacterial lineages invest simultaneously in both fast- and slow-growing types. We develop a population dynamic model of lineage expansion across a patchy environment and find that mixed investment is favored across a broad range of environmental conditions, even when transmission is entirely via biofilm cells. This mixed strategy is favored because of a division of labor where exponentially dividing planktonic cells can act as an engine for the production of future biofilm cells, which grow more slowly. We use experimental evolution to test our predictions and show that phenotypic heterogeneity is persistent even under selection for purely planktonic or purely biofilm transmission. Furthermore, simulations suggest that maintenance of a biofilm subpopulation serves as a cost-effective hedge against environmental uncertainty, which is also consistent with our experimental findings. IMPORTANCE Cell types specialized for survival have been observed and described within clonal bacterial populations for decades, but why are these specialists continually produced under benign conditions when such investment comes at a high reproductive cost? Conversely, when survival becomes an imperative, does it ever benefit the population to maintain a pool of rapidly growing but vulnerable planktonic cells? Using a combination of mathematical modeling, simulations, and experiments, we find that mixed investment strategies are favored over a broad range of environmental conditions and rely on a division of labor between cell types, where reproductive specialists amplify survival specialists, which can be transmitted through the environment with a limited mortality rate. We also show that survival specialists benefit rapidly growing populations by serving as a hedge against unpredictable changes in the environment. These results help to clarify the general evolutionary and ecological forces that can generate and maintain diverse subtypes within clonal bacterial populations. Copyright © 2017 Lowery et al.

PyClone: statistical inference of clonal population structure in cancer.

PubMed

Roth, Andrew; Khattra, Jaswinder; Yap, Damian; Wan, Adrian; Laks, Emma; Biele, Justina; Ha, Gavin; Aparicio, Samuel; Bouchard-Côté, Alexandre; Shah, Sohrab P

2014-04-01

We introduce PyClone, a statistical model for inference of clonal population structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced somatic mutations into putative clonal clusters while estimating their cellular prevalences and accounting for allelic imbalances introduced by segmental copy-number changes and normal-cell contamination. Single-cell sequencing validation demonstrates PyClone's accuracy.

Population Density and Moment-based Approaches to Modeling Domain Calcium-mediated Inactivation of L-type Calcium Channels.

PubMed

Wang, Xiao; Hardcastle, Kiah; Weinberg, Seth H; Smith, Gregory D

2016-03-01

We present a population density and moment-based description of the stochastic dynamics of domain [Formula: see text]-mediated inactivation of L-type [Formula: see text] channels. Our approach accounts for the effect of heterogeneity of local [Formula: see text] signals on whole cell [Formula: see text] currents; however, in contrast with prior work, e.g., Sherman et al. (Biophys J 58(4):985-995, 1990), we do not assume that [Formula: see text] domain formation and collapse are fast compared to channel gating. We demonstrate the population density and moment-based modeling approaches using a 12-state Markov chain model of an L-type [Formula: see text] channel introduced by Greenstein and Winslow (Biophys J 83(6):2918-2945, 2002). Simulated whole cell voltage clamp responses yield an inactivation function for the whole cell [Formula: see text] current that agrees with the traditional approach when domain dynamics are fast. We analyze the voltage-dependence of [Formula: see text] inactivation that may occur via slow heterogeneous domain [[Formula: see text

Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy

PubMed Central

Barish, Syndi; Ochs, Michael F.; Sontag, Eduardo D.; Gevertz, Jana L.

2017-01-01

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, mathematical modeling, and statistical analyses for identifying robust optimal treatment protocols. VEPART begins with time course experimental data for a sample population, and a mathematical model fit to aggregate data from that sample population. Using nonparametric statistics, the sample population is amplified and used to create a large number of virtual populations. At the final step of VEPART, robustness is assessed by identifying and analyzing the optimal therapy (perhaps restricted to a set of clinically realizable protocols) across each virtual population. As proof of concept, we have applied the VEPART method to study the robustness of treatment response in a mouse model of melanoma subject to treatment with immunostimulatory oncolytic viruses and dendritic cell vaccines. Our analysis (i) showed that every scheduling variant of the experimentally used treatment protocol is fragile (nonrobust) and (ii) discovered an alternative region of dosing space (lower oncolytic virus dose, higher dendritic cell dose) for which a robust optimal protocol exists. PMID:28716945

Slow and fast dynamics model of a Malaria with Sickle-Cell genetic disease with multi-stage infections of the mosquitoes population

NASA Astrophysics Data System (ADS)

Dewi Siawanta, Shanti; Adi-Kusumo, Fajar; Irwan Endrayanto, Aluicius

2018-03-01

Malaria, which is caused by Plasmodium, is a common disease in tropical areas. There are three types of Plasmodium i.e. Plasmodium Vivax, Plasmodium Malariae, and Plasmodium Falciparum. The most dangerous cases of the Malaria are mainly caused by the Plasmodium Falciparum. One of the important characteristics for the Plasmodium infection is due to the immunity of erythrocyte that contains HbS (Haemoglobin Sickle-cell) genes. The individuals who has the HbS gene has better immunity against the disease. In this paper, we consider a model that shows the spread of malaria involving the interaction between the mosquitos population, the human who has HbS genes population and the human with normal gene population. We do some analytical and numerical simulation to study the basic reproduction ratio and the slow-fast dynamics of the phase-portrait. The slow dynamics in our model represents the response of the human population with HbS gene to the Malaria disease while the fast dynamics show the response of the human population with the normal gene to the disease. The slow and fast dynamics phenomena are due to the fact that the population of the individuals who have HbS gene is much smaller than the individuals who has normal genes.

Vitamin K2-enhanced liver regeneration is associated with oval cell expansion and up-regulation of matrilin-2 expression in 2-AAF/PH rat model.

PubMed

Lin, M; Sun, P; Zhang, G; Xu, X; Liu, G; Miao, H; Yang, Y; Xu, H; Zhang, L; Wu, P; Li, M

2014-03-01

Normal liver has a great potential of regenerative capacity after partial hepatectomy. In clinic, however, most patients receiving partial hepatectomy are usually suffering from chronic liver diseases with severely damaged hepatocyte population. Under these conditions, activation of hepatic progenitor cell (oval cell in rodents) population might be considered as an alternative mean to enhance liver functional recovery. Vitamin K2 has been shown to promote liver functional recovery in patients with liver cirrhosis. In this study, we explored the possibility of vitamin K2 treatment in activating hepatic oval cell for liver regeneration with the classic 2-acetamido-fluorene/partial hepatectomy (2-AAF/PH) model in Sprague-Dawley rats. In 2-AAF/PH animals, vitamin K2 treatment induced a dose-dependent increase of liver regeneration as assessed by the weight ratio of remnant liver versus whole body and by measuring serum albumin level. In parallel, a drastic expansion of oval cell population as assessed by anti-OV6 and anti-CK19 immunostaining was noticed in the periportal zone of the remnant liver. Since matrilin-2 was linked to oval cell proliferation and liver regeneration after partial hepatectomy, we assessed its expression at both the mRNA and protein levels. The results revealed a significant increase after vitamin K2 treatment in parallel with the expansion of oval cell population. Consistently, knocking down matrilin-2 expression in vivo largely reduced vitamin K2-induced liver regeneration and oval cell proliferation in 2-AAF/PH animals. In conclusion, these data suggest that vitamin K2 treatment enhances liver regeneration after partial hepatectomy, which is associated with oval cell expansion and matrilin-2 up-regulation.

Primitive erythrocytes are generated from hemogenic endothelial cells.

PubMed

Stefanska, Monika; Batta, Kiran; Patel, Rahima; Florkowska, Magdalena; Kouskoff, Valerie; Lacaud, Georges

2017-07-25

Primitive erythroblasts are the first blood cells generated during embryonic hematopoiesis. Tracking their emergence both in vivo and in vitro has remained challenging due to the lack of specific cell surface markers. To selectively investigate primitive erythropoiesis, we have engineered a new transgenic embryonic stem (ES) cell line, where eGFP expression is driven by the regulatory sequences of the embryonic βH1 hemoglobin gene expressed specifically in primitive erythroid cells. Using this ES cell line, we observed that the first primitive erythroblasts are detected in vitro around day 1.5 of blast colony differentiation, within the cell population positive for the early hematopoietic progenitor marker CD41. Moreover, we establish that these eGFP + cells emerge from a hemogenic endothelial cell population similarly to their definitive hematopoietic counterparts. We further generated a corresponding βH1-eGFP transgenic mouse model and demonstrated the presence of a primitive erythroid primed hemogenic endothelial cell population in the developing embryo. Taken together, our findings demonstrate that both in vivo and in vitro primitive erythrocytes are generated from hemogenic endothelial cells.

Noise and Epigenetic Inheritance of Single-Cell Division Times Influence Population Fitness.

PubMed

Cerulus, Bram; New, Aaron M; Pougach, Ksenia; Verstrepen, Kevin J

2016-05-09

The fitness effect of biological noise remains unclear. For example, even within clonal microbial populations, individual cells grow at different speeds. Although it is known that the individuals' mean growth speed can affect population-level fitness, it is unclear how or whether growth speed heterogeneity itself is subject to natural selection. Here, we show that noisy single-cell division times can significantly affect population-level growth rate. Using time-lapse microscopy to measure the division times of thousands of individual S. cerevisiae cells across different genetic and environmental backgrounds, we find that the length of individual cells' division times can vary substantially between clonal individuals and that sublineages often show epigenetic inheritance of division times. By combining these experimental measurements with mathematical modeling, we find that, for a given mean division time, increasing heterogeneity and epigenetic inheritance of division times increases the population growth rate. Furthermore, we demonstrate that the heterogeneity and epigenetic inheritance of single-cell division times can be linked with variation in the expression of catabolic genes. Taken together, our results reveal how a change in noisy single-cell behaviors can directly influence fitness through dynamics that operate independently of effects caused by changes to the mean. These results not only allow a better understanding of microbial fitness but also help to more accurately predict fitness in other clonal populations, such as tumors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bayesian multivariate Poisson abundance models for T-cell receptor data.

PubMed

Greene, Joshua; Birtwistle, Marc R; Ignatowicz, Leszek; Rempala, Grzegorz A

2013-06-07

A major feature of an adaptive immune system is its ability to generate B- and T-cell clones capable of recognizing and neutralizing specific antigens. These clones recognize antigens with the help of the surface molecules, called antigen receptors, acquired individually during the clonal development process. In order to ensure a response to a broad range of antigens, the number of different receptor molecules is extremely large, resulting in a huge clonal diversity of both B- and T-cell receptor populations and making their experimental comparisons statistically challenging. To facilitate such comparisons, we propose a flexible parametric model of multivariate count data and illustrate its use in a simultaneous analysis of multiple antigen receptor populations derived from mammalian T-cells. The model relies on a representation of the observed receptor counts as a multivariate Poisson abundance mixture (m PAM). A Bayesian parameter fitting procedure is proposed, based on the complete posterior likelihood, rather than the conditional one used typically in similar settings. The new procedure is shown to be considerably more efficient than its conditional counterpart (as measured by the Fisher information) in the regions of m PAM parameter space relevant to model T-cell data. Copyright © 2013 Elsevier Ltd. All rights reserved.

Developing Laryngeal Muscle of Xenopus laevis as a Model System: Androgen-Driven Myogenesis Controls Fiber Type Transformation

PubMed Central

Nasipak, Brian; Kelley, Darcy B.

2014-01-01

The developmental programs that contribute to myogenic stem cell proliferation and muscle fiber differentiation control fiber numbers and twitch type. In this study, we describe the use of an experimental model system—androgen-regulated laryngeal muscle of juvenile clawed frogs, Xenopus laevis—to examine the contribution of proliferation by specific populations of myogenic stem cells to expression of the larynx-specific myosin heavy chain isoform, LM. Androgen treatment of juveniles (Stage PM0) resulted in up-regulation of an early (Myf-5) and a late (myogenin) myogenic regulatory factor; the time course of LM up-regulation tracked that of myogenin. Myogenic stem cells stimulated to proliferate by androgen include a population that expresses Pax-7, a marker for the satellite cell myogenic stem cell population. Since androgen can switch muscle fiber types from fast to slow even in denervated larynges, we developed an ex vivo culture system to explore the relation between proliferation and LM expression. Cultured whole larynges maintain sensitivity to androgen, increasing in size and LM expression. Blockade of cell proliferation with cis-platin prevents the switch from slow to fast twitch muscle fibers as assayed by ATPase activity. Blockade of cell proliferation in vivo also resulted in inhibition of LM expression. Thus, both in vivo and ex vivo, inhibition of myogenic stem cell proliferation blocks androgen-induced LM expression and fiber type switching in juveniles. PMID:21954146

Selective propagation of mouse-passaged scrapie prions with long incubation period from a mixed prion population using GT1-7 cells

PubMed Central

Masujin, Kentaro; Okada, Hiroyuki; Ushiki-Kaku, Yuko; Matsuura, Yuichi; Yokoyama, Takashi

2017-01-01

In our previous study, we demonstrated the propagation of mouse-passaged scrapie isolates with long incubation periods (L-type) derived from natural Japanese sheep scrapie cases in murine hypothalamic GT1-7 cells, along with disease-associated prion protein (PrPSc) accumulation. We here analyzed the susceptibility of GT1-7 cells to scrapie prions by exposure to infected mouse brains at different passages, following interspecies transmission. Wild-type mice challenged with a natural sheep scrapie case (Kanagawa) exhibited heterogeneity of transmitted scrapie prions in early passages, and this mixed population converged upon one with a short incubation period (S-type) following subsequent passages. However, when GT1-7 cells were challenged with these heterologous samples, L-type prions became dominant. This study demonstrated that the susceptibility of GT1-7 cells to L-type prions was at least 105 times higher than that to S-type prions and that L-type prion-specific biological characteristics remained unchanged after serial passages in GT1-7 cells. This suggests that a GT1-7 cell culture model would be more useful for the economical and stable amplification of L-type prions at the laboratory level. Furthermore, this cell culture model might be used to selectively propagate L-type scrapie prions from a mixed prion population. PMID:28636656

Selective propagation of mouse-passaged scrapie prions with long incubation period from a mixed prion population using GT1-7 cells.

PubMed

Miyazawa, Kohtaro; Masujin, Kentaro; Okada, Hiroyuki; Ushiki-Kaku, Yuko; Matsuura, Yuichi; Yokoyama, Takashi

2017-01-01

In our previous study, we demonstrated the propagation of mouse-passaged scrapie isolates with long incubation periods (L-type) derived from natural Japanese sheep scrapie cases in murine hypothalamic GT1-7 cells, along with disease-associated prion protein (PrPSc) accumulation. We here analyzed the susceptibility of GT1-7 cells to scrapie prions by exposure to infected mouse brains at different passages, following interspecies transmission. Wild-type mice challenged with a natural sheep scrapie case (Kanagawa) exhibited heterogeneity of transmitted scrapie prions in early passages, and this mixed population converged upon one with a short incubation period (S-type) following subsequent passages. However, when GT1-7 cells were challenged with these heterologous samples, L-type prions became dominant. This study demonstrated that the susceptibility of GT1-7 cells to L-type prions was at least 105 times higher than that to S-type prions and that L-type prion-specific biological characteristics remained unchanged after serial passages in GT1-7 cells. This suggests that a GT1-7 cell culture model would be more useful for the economical and stable amplification of L-type prions at the laboratory level. Furthermore, this cell culture model might be used to selectively propagate L-type scrapie prions from a mixed prion population.

Trail networks formed by populations of immune cells

NASA Astrophysics Data System (ADS)

Yang, Taeseok Daniel; Kwon, Tae Goo; Park, Jin-sung; Lee, Kyoung J.

2014-02-01

Populations of biological cells that communicate with each other can organize themselves to generate large-scale patterns. Examples can be found in diverse systems, ranging from developing embryos, cardiac tissues, chemotaxing ameba and swirling bacteria. The similarity, often shared by the patterns, suggests the existence of some general governing principle. On the other hand, rich diversity and system-specific properties are exhibited, depending on the type of involved cells and the nature of their interactions. The study on the similarity and the diversity constitutes a rapidly growing field of research. Here, we introduce a new class of self-organized patterns of cell populations that we term as ‘cellular trail networks’. They were observed with populations of rat microglia, the immune cells of the brain and the experimental evidence suggested that haptotaxis is the key element responsible for them. The essential features of the observed patterns are well captured by the mathematical model cells that actively crawl and interact with each other through a decomposing but non-diffusing chemical attractant laid down by the cells. Our finding suggests an unusual mechanism of socially cooperative long-range signaling for the crawling immune cells.

Cinnamides as selective small-molecule inhibitors of a cellular model of breast cancer stem cells.

PubMed

Germain, Andrew R; Carmody, Leigh C; Nag, Partha P; Morgan, Barbara; Verplank, Lynn; Fernandez, Cristina; Donckele, Etienne; Feng, Yuxiong; Perez, Jose R; Dandapani, Sivaraman; Palmer, Michelle; Lander, Eric S; Gupta, Piyush B; Schreiber, Stuart L; Munoz, Benito

2013-03-15

A high-throughput screen (HTS) was conducted against stably propagated cancer stem cell (CSC)-enriched populations using a library of 300,718 compounds from the National Institutes of Health (NIH) Molecular Libraries Small Molecule Repository (MLSMR). A cinnamide analog displayed greater than 20-fold selective inhibition of the breast CSC-like cell line (HMLE_sh_Ecad) over the isogenic control cell line (HMLE_sh_eGFP). Herein, we report structure-activity relationships of this class of cinnamides for selective lethality towards CSC-enriched populations. Copyright © 2013. Published by Elsevier Ltd.

Evolution of Cell Size Homeostasis and Growth Rate Diversity during Initial Surface Colonization of Shewanella oneidensis.

PubMed

Lee, Calvin K; Kim, Alexander J; Santos, Giancarlo S; Lai, Peter Y; Lee, Stella Y; Qiao, David F; Anda, Jaime De; Young, Thomas D; Chen, Yujie; Rowe, Annette R; Nealson, Kenneth H; Weiss, Paul S; Wong, Gerard C L

2016-09-06

Cell size control and homeostasis are fundamental features of bacterial metabolism. Recent work suggests that cells add a constant size between birth and division ("adder" model). However, it is not known how cell size homeostasis is influenced by the existence of heterogeneous microenvironments, such as those during biofilm formation. Shewanella oneidensis MR-1 can use diverse energy sources on a range of surfaces via extracellular electron transport (EET), which can impact growth, metabolism, and size diversity. Here, we track bacterial surface communities at single-cell resolution to show that not only do bacterial motility appendages influence the transition from two- to three-dimensional biofilm growth and control postdivisional cell fates, they strongly impact cell size homeostasis. For every generation, we find that the average growth rate for cells that stay on the surface and continue to divide (nondetaching population) and that for cells that detach before their next division (detaching population) are roughly constant. However, the growth rate distribution is narrow for the nondetaching population, but broad for the detaching population in each generation. Interestingly, the appendage deletion mutants (ΔpilA, ΔmshA-D, Δflg) have significantly broader growth rate distributions than that of the wild type for both detaching and nondetaching populations, which suggests that Shewanella appendages are important for sensing and integrating environmental inputs that contribute to size homeostasis. Moreover, our results suggest multiplexing of appendages for sensing and motility functions contributes to cell size dysregulation. These results can potentially provide a framework for generating metabolic diversity in S. oneidensis populations to optimize EET in heterogeneous environments.

Cellular automata approach for the dynamics of HIV infection under antiretroviral therapies: The role of the virus diffusion

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; de Figueirêdo, Pedro Hugo; Coutinho, Sérgio

2013-10-01

We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell-cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.

Lentiviral and targeted cellular barcoding reveals ongoing clonal dynamics of cell lines in vitro and in vivo

PubMed Central

2014-01-01

Background Cell lines are often regarded as clonal, even though this simplifies what is known about mutagenesis, transformation and other processes that destabilize them over time. Monitoring these clonal dynamics is important for multiple areas of biomedical research, including stem cell and cancer biology. Tracking the contributions of individual cells to large populations, however, has been constrained by limitations in sensitivity and complexity. Results We utilize cellular barcoding methods to simultaneously track the clonal contributions of tens of thousands of cells. We demonstrate that even with optimal culturing conditions, common cell lines including HeLa, K562 and HEK-293 T exhibit ongoing clonal dynamics. Starting a population with a single clone diminishes but does not eradicate this phenomenon. Next, we compare lentiviral and zinc-finger nuclease barcode insertion approaches, finding that the zinc-finger nuclease protocol surprisingly results in reduced clonal diversity. We also document the expected reduction in clonal complexity when cells are challenged with genotoxic stress. Finally, we demonstrate that xenografts maintain clonal diversity to a greater extent than in vitro culturing of the human non-small-cell lung cancer cell line HCC827. Conclusions We demonstrate the feasibility of tracking and quantifying the clonal dynamics of entire cell populations within multiple cultured cell lines. Our results suggest that cell heterogeneity should be considered in the design and interpretation of in vitro culture experiments. Aside from clonal cell lines, we propose that cellular barcoding could prove valuable in modeling the clonal behavior of heterogeneous cell populations over time, including tumor populations treated with chemotherapeutic agents. PMID:24886633

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

Intelligent Network Management and Functional Cerebellum Synthesis

NASA Technical Reports Server (NTRS)

Loebner, Egon E.

1989-01-01

Transdisciplinary modeling of the cerebellum across histology, physiology, and network engineering provides preliminary results at three organization levels: input/output links to central nervous system networks; links between the six neuron populations in the cerebellum; and computation among the neurons of the populations. Older models probably underestimated the importance and role of climbing fiber input which seems to supply write as well as read signals, not just to Purkinje but also to basket and stellate neurons. The well-known mossy fiber-granule cell-Golgi cell system should also respond to inputs originating from climbing fibers. Corticonuclear microcomplexing might be aided by stellate and basket computation and associate processing. Technological and scientific implications of the proposed cerebellum model are discussed.

Inflammatory arthritis increases mouse osteoclast precursors with myeloid suppressor function

PubMed Central

Charles, Julia F.; Hsu, Lih-Yun; Niemi, Erene C.; Weiss, Arthur; Aliprantis, Antonios O.; Nakamura, Mary C.

2012-01-01

Increased osteoclastic bone resorption leads to periarticular erosions and systemic osteoporosis in RA patients. Although a great deal is known about how osteoclasts differentiate from precursors and resorb bone, the identity of an osteoclast precursor (OCP) population in vivo and its regulatory role in RA remains elusive. Here, we report the identification of a CD11b–/loLy6Chi BM population with OCP activity in vitro and in vivo. These cells, which can be distinguished from previously characterized precursors in the myeloid lineage, display features of both M1 and M2 monocytes and expand in inflammatory arthritis models. Surprisingly, in one mouse model of RA (adoptive transfer of SKG arthritis), cotransfer of OCP with SKG CD4+ T cells diminished inflammatory arthritis. Similar to monocytic myeloid-derived suppressor cells (M-MDSCs), OCPs suppressed CD4+ and CD8+ T cell proliferation in vitro through the production of NO. This study identifies a BM myeloid precursor population with osteoclastic and T cell–suppressive activity that is expanded in inflammatory arthritis. Therapeutic strategies that prevent the development of OCPs into mature bone-resorbing cells could simultaneously prevent bone resorption and generate an antiinflammatory milieu in the RA joint. PMID:23114597

A van der Waals-like Transition Between Normal and Cancerous Phases in Cell Populations Dynamics of Colorectal Cancer

NASA Astrophysics Data System (ADS)

Qiu, Kang; Wang, Li-Fang; Shen, Jian; Yousif, Alssadig A. M.; He, Peng; Shao, Dan-Dan; Zhang, Xiao-Min; Kirunda, John B.; Jia, Ya

2016-11-01

Based on a deterministic continuous model of cell populations dynamics in the colonic crypt and in colorectal cancer, we propose four combinations of feedback mechanisms in the differentiations from stem cells (SCs) to transit cells (TCs) and then to differentiated cells (DCs), the four combinations include the double linear (LL), the linear and saturating (LS), the saturating and linear (SL), and the double saturating (SS) feedbacks, respectively. The relative fluctuations of the population of SCs, TCs, and DCs around equilibrium states with four feedback mechanisms are studied by using the Langevin method. With the increasing of net growth rate of TCs, it is found that the Fano factors of TCs and DCs go to a peak in a transient phase, and then increase again to infinity in the cases of LS and SS feedbacks. The “up-down-up” characteristic on the Fano factor (like the van der Waals loop) demonstrates that there exists a transient phase between the normal and cancerous phases, our novel findings suggest that the mathematical model with LS or SS feedback might be better to elucidate the dynamics of a normal and abnormal (cancerous) phases.

Loss of p19Arf in a Rag1−/− B-cell precursor population initiates acute B-lymphoblastic leukemia

PubMed Central

Hauer, Julia; Mullighan, Charles; Morillon, Estelle; Wang, Gary; Bruneau, Julie; Brousse, Nicole; Lelorc'h, Marc; Romana, Serge; Boudil, Amine; Tiedau, Daniela; Kracker, Sven; Bushmann, Frederic D.; Borkhardt, Arndt; Fischer, Alain; Hacein-Bey-Abina, Salima

2011-01-01

In human B-acute lymphoblastic leukemia (B-ALL), RAG1-induced genomic alterations are important for disease progression. However, given that biallelic loss of the RAG1 locus is observed in a subset of cases, RAG1's role in the development of B-ALL remains unclear. We chose a p19Arf−/−Rag1−/− mouse model to confirm the previously published results concerning the contribution of CDKN2A (p19ARF /INK4a) and RAG1 copy number alterations in precursor B cells to the initiation and/or progression to B-acute lymphoblastic leukemia (B-ALL). In this murine model, we identified a new, Rag1-independent leukemia-initiating mechanism originating from a Sca1+CD19+ precursor cell population and showed that Notch1 expression accelerates the cells' self-renewal capacity in vitro. In human RAG1-deficient BM, a similar CD34+CD19+ population expressed p19ARF. These findings suggest that combined loss of p19Arf and Rag1 results in B-cell precursor leukemia in mice and may contribute to the progression of precursor B-ALL in humans. PMID:21622646

Ovarian cancer stem cells.

PubMed

Zeimet, A G; Reimer, D; Sopper, S; Boesch, M; Martowicz, A; Roessler, J; Wiedemair, A M; Rumpold, H; Untergasser, G; Concin, N; Hofstetter, G; Muller-Holzner, E; Fiegl, H; Marth, C; Wolf, D; Pesta, M; Hatina, J

2012-01-01

Because of its semi-solid character in dissemination and growth, advanced ovarian cancer with its hundreds of peritoneal tumor nodules and plaques appears to be an excellent in vivo model for studying the cancer stem cell hypothesis. The most important obstacle, however, is to adequately define and isolate these tumor-initiating cells endowed with the properties of anoikis-resistance and unlimited self-renewal. Until now, no universal single marker or marker constellation has been found to faithfully isolate (ovarian) cancer stem cells. As these multipotent cells are known to possess highly elaborated efflux systems for cytotoxic agents, these pump systems have been exploited to outline putative stem cells as a side-population (SP) via dye exclusion analysis. Furthermore, the cells in question have been isolated via flow cytometry on the basis of cell surface markers thought to be characteristic for stem cells.In the Vienna variant of the ovarian cancer cell line A2780 a proof-of-principle model with both a stable SP and a stable ALDH1A1+ cell population was established. Double staining clearly revealed that both cell fractions were not identical. Of note, A2780V cells were negative for expression of surface markers CD44 and CD117 (c-kit). When cultured on monolayers of healthy human mesothelial cells, green-fluorescence-protein (GFP)-transfected SP of A2780V exhibited spheroid-formation, whereas non-side-population (NSP) developed a spare monolayer growing over the healthy mesothelium. Furthermore, A2780V SP was found to be partially resistant to platinum. However, this resistance could not be explained by over-expression of the "excision repair cross-complementation group 1" (ERCC1) gene, which is essentially involved in the repair of platinated DNA damage. ERCC1 was, nonetheless, over-expressed in A2780V cells grown as spheres under stem cell-selective conditions as compared to adherent monolayers cultured under differentiating conditions. The same was true for the primary ovarian cancer cells B-57.In summary our investigations indicate that even in multi-passaged cancer cell lines hierarchic government of growth and differentiation is conserved and that the key cancer stem cell population may be composed of small overlapping cell fractions defined by various arbitrary markers.

Purification of human induced pluripotent stem cell-derived neural precursors using magnetic activated cell sorting.

PubMed

Rodrigues, Gonçalo M C; Fernandes, Tiago G; Rodrigues, Carlos A V; Cabral, Joaquim M S; Diogo, Maria Margarida

2015-01-01

Neural precursor (NP) cells derived from human induced pluripotent stem cells (hiPSCs), and their neuronal progeny, will play an important role in disease modeling, drug screening tests, central nervous system development studies, and may even become valuable for regenerative medicine treatments. Nonetheless, it is challenging to obtain homogeneous and synchronously differentiated NP populations from hiPSCs, and after neural commitment many pluripotent stem cells remain in the differentiated cultures. Here, we describe an efficient and simple protocol to differentiate hiPSC-derived NPs in 12 days, and we include a final purification stage where Tra-1-60+ pluripotent stem cells (PSCs) are removed using magnetic activated cell sorting (MACS), leaving the NP population nearly free of PSCs.

Defining the cellular lineage hierarchy in the interfollicular epidermis of adult skin.

PubMed

Sada, Aiko; Jacob, Fadi; Leung, Eva; Wang, Sherry; White, Brian S; Shalloway, David; Tumbar, Tudorita

2016-06-01

The interfollicular epidermis regenerates from heterogeneous basal skin cell populations that divide at different rates. It has previously been presumed that infrequently dividing basal cells known as label-retaining cells (LRCs) are stem cells, whereas non-LRCs are short-lived progenitors. Here we employ the H2B-GFP pulse-chase system in adult mouse skin and find that epidermal LRCs and non-LRCs are molecularly distinct and can be differentiated by Dlx1(CreER) and Slc1a3(CreER) genetic marking, respectively. Long-term lineage tracing and mathematical modelling of H2B-GFP dilution data show that LRCs and non-LRCs constitute two distinct stem cell populations with different patterns of proliferation, differentiation and upward cellular transport. During homeostasis, these populations are enriched in spatially distinct skin territories and can preferentially produce unique differentiated lineages. On wounding or selective killing, they can temporarily replenish each other's territory. These two discrete interfollicular stem cell populations are functionally interchangeable and intrinsically well adapted to thrive in distinct skin environments.

Importance of the predator's ecological neighborhood in modeling predation on migrating prey

USGS Publications Warehouse

DeAngelis, Donald L.; Petersen, James H.

2001-01-01

Most mathematical descriptions of predator-prey interactions fail to take into account the spatio-temporal structures of the populations, which can lead to errors or misinterpretations. For example, a compact pulse of prey migrating through a field of quasi-stationary predators may not be well described by standard predator-prey models, because the predators and prey are unlikely to be well mixed; that is, the prey may be exposed to only a fraction of the predator population at a time. This underscores the importance of properly accounting for the ecological neighborhood, or effective feeding range, of predators in models. We illustrate this situation with a series of models of salmon smolts migrating through a reservoir arrayed with predators. The reservoir is divided into a number of longitudinal compartments or spatial cells, the length of each cell representing the upstream-downstream range over which predators can forage. In this series of models a 100-km-long reservoir is divided, successively into 2, 5, 10, 25, 50, 100, 200, and 400 cells, with respective cell lengths of 50, 20, 10, 4, 2, 1, 0.5, and 0.25 km. We used a detailed individual-based simulation model at first, but to ensure robustness of results we supplemented this with a simple analytic model. Both models showed sharp differences in the predicted mortality to a compact pulse of smolt prey moving through the reservoir, depending on the number of spatial cells in the model. In particular, models with fewer than about 10 cells vastly overpredicted the amount of mortality due to predators with activity ranges of not more than a few kilometers. These results corroborate recent theoretical and simulation studies on the importance of spatial scale and behavior in modeling predator-prey dynamics.

Host mediated inflammatory influence on glioblastoma multiforme recurrence following high-dose ionizing radiation

PubMed Central

Gao, Xuefeng; Steber, Cole; Lee Breed, Jawon; Pollock, Caitlin; Ma, Lili; Hlatky, Lynn

2017-01-01

Despite optimal clinical treatment, glioblastoma multiforme (GBM) inevitably recurs. Standard treatment of GBM, exposes patients to radiation which kills tumor cells, but also modulates the molecular fingerprint of any surviving tumor cells and the cross-talk between those cells and the host. Considerable investigation of short-term (hours to days) post-irradiation tumor cell response has been undertaken, yet long-term responses (weeks to months) which are potentially even more informative of recurrence, have been largely overlooked. To better understand the potential of these processes to reshape tumor regrowth, molecular studies in conjunction with in silico modeling were used to examine short- and long-term growth dynamics. Despite survival of 2.55% and 0.009% following 8 or 16Gy, GBM cell populations in vitro showed a robust escape from cellular extinction and a return to pre-irradiated growth rates with no changes in long-term population doublings. In contrast, these same irradiated GBM cell populations injected in vivo elicited tumors which displayed significantly suppressed growth rates compared to their pre-irradiated counterparts. Transcriptome analysis days to weeks after irradiation revealed, 281 differentially expressed genes with a robust increase for cytokines, histones and C-C or C-X-C motif chemokines in irradiated cells. Strikingly, this same inflammatory signature in vivo for IL1A, CXCL1, IL6 and IL8 was increased in xenografts months after irradiation. Computational modeling of tumor cell dynamics indicated a host-mediated negative pressure on the surviving cells was a source of inhibition consistent with the findings resulting in suppressed tumor growth. Thus, tumor cells surviving irradiation may shift the landscape of population doubling through inflammatory mediators interacting with the host in a way that impacts tumor recurrence and affects the efficacy of subsequent therapies. Clues to more effective therapies may lie in the development and use of pre-clinical models of post-treatment response to target the source of inflammatory mediators that significantly alter cellular dynamics and molecular pathways in the early stages of tumor recurrence. PMID:28542439

Immunomodulation of human B cells following treatment with intravenous immunoglobulins involves increased phosphorylation of extracellular signal-regulated kinases 1 and 2.

PubMed

Dussault, Nathalie; Ducas, Eric; Racine, Claudia; Jacques, Annie; Paré, Isabelle; Côté, Serge; Néron, Sonia

2008-11-01

In the treatment of autoimmune diseases, intravenous Igs (IVIg) are assumed to modulate immune cells through the binding of surface receptors. IVIg act upon definite human B cell populations to modulate Ig repertoire, and such modulation might proceed through intracellular signaling. However, the heterogeneity of human B cell populations complicates investigations of the intracellular pathways involved in IVIg-induced B cell modulation. The aim of this study was to establish a model allowing the screening of IVIg signal transduction in human B cell lines and to attempt transposing observations made in cell lines to normal human B lymphocytes. Nine human B cell lines were treated with IVIg with the goal of selecting the most suitable model for human B lymphocytes. The IgG(+) DB cell line, whose response was similar to that of human B lymphocytes, showed reduced IVIg modulation following addition of PD98059, an inhibitor of extracellular signal-regulated protein kinase 1/2 (ERK1/2). The IVIg-induced ERK1/2 phosphorylation was indeed proportional to the dosage of monomeric IVIg used when tested on DB cells as well as Pfeiffer cells, another IgG(+) cell line. In addition, two other intermediates, Grb2-associated binder 1 (Gab1) and Akt, showed increased phosphorylation in IVIg-treated DB cells. IVIg induction of ERK1/2 phosphorylation was finally observed in peripheral human B lymphocytes, specifically within the IgG(+) B cell population. In conclusion, IVIg immunomodulation of human B cells can thus be linked to intracellular transduction pathways involving the phosphorylation of ERK1/2, which in combination with Gab1 and Akt, may be related to B cell antigen receptor signaling.

Deconstructing (and reconstructing) cell migration.

PubMed

Maheshwari, G; Lauffenburger, D A

1998-12-01

An overriding objective in cell biology is to be able to relate properties of particular molecular components to cell behavioral functions and even physiology. In the "traditional" mode of molecular cell biology, this objective has been tackled on a molecule-by-molecule basis, and in the "future" mode sometimes termed "functional genomics," it might be attacked in a high-throughput, parallel manner. Regardless of the manner of approach, the relationship between molecular-level properties and cell-level function is exceedingly difficult to elucidate because of the large number of relevant components involved, their high degree of interconnectedness, and the inescapable fact that they operate as physico-chemical entities-according to the laws of kinetics and mechanics-in space and time within the cell. Cell migration is a prominent representative example of such a cell behavioral function that requires increased understanding for both scientific and technological advance. This article presents a framework, derived from an engineering perspective regarding complex systems, intended to aid in developing improved understanding of how properties of molecular components influence the function of cell migration. That is, cell population migration behavior can be deconstructed as follows: first in terms of a mathematical model comprising cell population parameters (random motility, chemotaxis/haptotaxis, and chemokinesis/haptokinesis coefficients), which in turn depend on characteristics of individual cell paths that can be analyzed in terms of a mathematical model comprising individual cell parameters (translocation speed, directional persistence time, chemotactic/haptotactic index), which in turn depend on cell-level physical processes underlying motility (membrane extension and retraction, cell/substratum adhesion, cell contractile force, front-vs.-rear asymmetry), which in turn depend on molecular-level properties of the plethora of components involved in governance and regulation of these processes. Hence, the influence of any molecular component on cell population migration can be understood by reconstructing these relationships from the molecular level to the physical process level to the individual cell path level to the cell population distribution level. This approach requires combining experimental, theoretical, and computational methodologies from molecular biology, biochemistry, biophysics, and bioengineering.

Changes in Circulating B Cell Subsets Associated with Aging and Acute SIV Infection in Rhesus Macaques.

PubMed

Chang, W L William; Gonzalez, Denise F; Kieu, Hung T; Castillo, Luis D; Messaoudi, Ilhem; Shen, Xiaoying; Tomaras, Georgia D; Shacklett, Barbara L; Barry, Peter A; Sparger, Ellen E

2017-01-01

Aging and certain viral infections can negatively impact humoral responses in humans. To further develop the nonhuman primate (NHP) model for investigating B cell dynamics in human aging and infectious disease, a flow cytometric panel was developed to characterize circulating rhesus B cell subsets. Significant differences between human and macaque B cells included the proportions of cells within IgD+ and switched memory populations and a prominent CD21-CD27+ unswitched memory population detected only in macaques. We then utilized the expanded panel to analyze B cell alterations associated with aging and acute simian immunodeficiency virus (SIV) infection in the NHP model. In the aging study, distinct patterns of B cell subset frequencies were observed for macaques aged one to five years compared to those between ages 5 and 30 years. In the SIV infection study, B cell frequencies and absolute number were dramatically reduced following acute infection, but recovered within four weeks of infection. Thereafter, the frequencies of activated memory B cells progressively increased; these were significantly correlated with the magnitude of SIV-specific IgG responses, and coincided with impaired maturation of anti-SIV antibody avidity, as previously reported for HIV-1 infection. These observations further validate the NHP model for investigation of mechanisms responsible for B cells alterations associated with immunosenescence and infectious disease.

Representation of Perceptual Color Space in Macaque Posterior Inferior Temporal Cortex (the V4 Complex)

PubMed Central

Bohon, Kaitlin S.; Hermann, Katherine L.; Hansen, Thorsten

2016-01-01

Abstract The lateral geniculate nucleus is thought to represent color using two populations of cone-opponent neurons [L vs M; S vs (L + M)], which establish the cardinal directions in color space (reddish vs cyan; lavender vs lime). How is this representation transformed to bring about color perception? Prior work implicates populations of glob cells in posterior inferior temporal cortex (PIT; the V4 complex), but the correspondence between the neural representation of color in PIT/V4 complex and the organization of perceptual color space is unclear. We compared color-tuning data for populations of glob cells and interglob cells to predictions obtained using models that varied in the color-tuning narrowness of the cells, and the color preference distribution across the populations. Glob cells were best accounted for by simulated neurons that have nonlinear (narrow) tuning and, as a population, represent a color space designed to be perceptually uniform (CIELUV). Multidimensional scaling and representational similarity analyses showed that the color space representations in both glob and interglob populations were correlated with the organization of CIELUV space, but glob cells showed a stronger correlation. Hue could be classified invariant to luminance with high accuracy given glob responses and above-chance accuracy given interglob responses. Luminance could be read out invariant to changes in hue in both populations, but interglob cells tended to prefer stimuli having luminance contrast, regardless of hue, whereas glob cells typically retained hue tuning as luminance contrast was modulated. The combined luminance/hue sensitivity of glob cells is predicted for neurons that can distinguish two colors of the same hue at different luminance levels (orange/brown). PMID:27595132

Modelling collective cell migration of neural crest

PubMed Central

Szabó, András; Mayor, Roberto

2016-01-01

Collective cell migration has emerged in the recent decade as an important phenomenon in cell and developmental biology and can be defined as the coordinated and cooperative movement of groups of cells. Most studies concentrate on tightly connected epithelial tissues, even though collective migration does not require a constant physical contact. Movement of mesenchymal cells is more independent, making their emergent collective behaviour less intuitive and therefore lending importance to computational modelling. Here we focus on such modelling efforts that aim to understand the collective migration of neural crest cells, a mesenchymal embryonic population that migrates large distances as a group during early vertebrate development. By comparing different models of neural crest migration, we emphasize the similarity and complementary nature of these approaches and suggest a future direction for the field. The principles derived from neural crest modelling could aid understanding the collective migration of other mesenchymal cell types. PMID:27085004

Modelling collective cell migration of neural crest.

PubMed

Szabó, András; Mayor, Roberto

2016-10-01

Collective cell migration has emerged in the recent decade as an important phenomenon in cell and developmental biology and can be defined as the coordinated and cooperative movement of groups of cells. Most studies concentrate on tightly connected epithelial tissues, even though collective migration does not require a constant physical contact. Movement of mesenchymal cells is more independent, making their emergent collective behaviour less intuitive and therefore lending importance to computational modelling. Here we focus on such modelling efforts that aim to understand the collective migration of neural crest cells, a mesenchymal embryonic population that migrates large distances as a group during early vertebrate development. By comparing different models of neural crest migration, we emphasize the similarity and complementary nature of these approaches and suggest a future direction for the field. The principles derived from neural crest modelling could aid understanding the collective migration of other mesenchymal cell types. Copyright © 2016 Elsevier Ltd. All rights reserved.

A CD133-expressing murine liver oval cell population with bilineage potential.

PubMed

Rountree, C Bart; Barsky, Lora; Ge, Shundi; Zhu, Judy; Senadheera, Shantha; Crooks, Gay M

2007-10-01

Although oval cells are postulated to be adult liver stem cells, a well-defined phenotype of a bipotent liver stem cell remains elusive. The heterogeneity of cells within the oval cell fraction has hindered lineage potential studies. Our goal was to identify an enriched population of bipotent oval cells using a combination of flow cytometry and single cell gene expression in conjunction with lineage-specific liver injury models. Expression of cell surface markers on nonparenchymal, nonhematopoietic (CD45-) cells were characterized. Cell populations were isolated by flow cytometry for gene expression studies. 3,5-Diethoxycarbonyl-1,4-dihydrocollidine toxic injury induced cell cycling and expansion specifically in the subpopulation of oval cells in the periportal zone that express CD133. CD133+CD45- cells expressed hepatoblast and stem cell-associated genes, and single cells coexpressed both hepatocyte and cholangiocyte-associated genes, indicating bilineage potential. CD133+CD45- cells proliferated in response to liver injury. Following toxic hepatocyte damage, CD133+CD45- cells demonstrated upregulated expression of the hepatocyte gene Albumin. In contrast, toxic cholangiocyte injury resulted in upregulation of the cholangiocyte gene Ck19. After 21-28 days in culture, CD133+CD45- cells continued to generate cells of both hepatocyte and cholangiocyte lineages. Thus, CD133 expression identifies a population of oval cells in adult murine liver with the gene expression profile and function of primitive, bipotent liver stem cells. In response to lineage-specific injury, these cells demonstrate a lineage-appropriate genetic response. Disclosure of potential conflicts of interest is found at the end of this article.

Linking micro- and macro-evolution at the cell type level: a view from the lophotrochozoan Platynereis dumerilii.

PubMed

Simakov, Oleg; Larsson, Tomas A; Arendt, Detlev

2013-09-01

Ever since the origin of the first metazoans over 600 million years ago, cell type diversification has been driven by micro-evolutionary processes at population level, leading to macro-evolution changes above species level. In this review, we introduce the marine annelid Platynereis dumerilii, a member of the lophotrochozoan clade (a key yet most understudied superphylum of bilaterians), as a suitable model system for the simultaneous study, at cellular resolution, of macro-evolutionary processes across phyla and of micro-evolutionary processes across highly polymorphic populations collected worldwide. Recent advances in molecular and experimental techniques, easy maintenance and breeding, and the fast, synchronous and stereotypical development have facilitated the establishment of Platynereis as one of the leading model species in the eco-evo-devo field. Most importantly, Platynereis allows the combination of expression profiling, morphological and physiological characterization at the single cell level. Here, we discuss recent advances in the collection of -omics data for the lab strain and for natural populations collected world-wide that can be integrated with population-specific cellular analyses to result in a cellular atlas integrating genetic, phenotypic and ecological variation. This makes Platynereis a tractable system to begin understanding the interplay between macro- and micro-evolutionary processes and cell type diversity.

Optimum survival strategies against zombie infestations - a population dynamics approach

NASA Astrophysics Data System (ADS)

Mota, Bruno

2014-03-01

We model a zombie infestation by three coupled ODEs that jointly describe the time evolution of three populations: regular humans, zombies, and survivors (humans that have survived at least one zombie encounter). This can be generalized to take into account more levels of expertise and/or skill degradation. We compute the fixed points, and stability thereof, that correspond to one of three possible outcomes: human extinction, zombie extermination or, if one allows for a human non-zero birth-rate, co-habitation. We obtain analytically the optimum strategy for humans in terms of the model's parameters (essentially, whether to flee and hide, or fight). Zombies notwithstanding, this can also be seen as a toy model for infections of immune system cells, such as CD4+ T cells in AIDS, and macrophages in tuberculosis, whereby cells are both the target of infection, and mediate the acquired immunity response against the same infection. I thank FAPERJ for financial support.

New factors controlling the balance between osteoblastogenesis and adipogenesis.

PubMed

Abdallah, Basem M; Kassem, Moustapha

2012-02-01

The majority of conditions associated with bone loss, including aging, are accompanied by increased marrow adiposity possibly due to shifting of the balance between osteoblast and adipocyte differentiation in bone marrow stromal (skeletal) stem cells (MSC). In order to study the relationship between osteoblastogenesis and adipogenesis in bone marrow, we have characterized cellular models of multipotent MSC as well as pre-osteoblastic and pre-adipocytic cell populations. Using these models, we identified two secreted factors in the bone marrow microenviroment: secreted frizzled-related protein 1 (sFRP-1) and delta-like1 (preadipocyte factor 1) (Dlk1/Pref-1). Both exert regulatory effects on osteoblastogenesis and adipogenesis. Our studies suggest a model for lineage fate determination of MSC that is regulated through secreted factors in the bone marrow microenvironment that mediate a cross-talk between lineage committed cell populations in addition to controlling differentiation choices of multipotent MSC. Copyright © 2011 Elsevier Inc. All rights reserved.

Identification of immunophenotypic subtypes with different prognoses in extranodal natural killer/T-cell lymphoma, nasal type.

PubMed

Yu, Jian-Bo; Zuo, Zhuo; Zhang, Wen-Yan; Yang, Qun-Pei; Zhang, Ying-Chun; Tang, Yuan; Zhao, Sha; Mo, Xian-Ming; Liu, Wei-Ping

2014-11-01

To analyze the differentiation characteristics of extranodal natural killer/T-cell lymphoma, nasal type, one nude mouse model, cell lines SNK6 and SNT8, and 16 fresh human samples were analyzed by flow cytometry immunophenotyping and immunohistochemistry staining; and 115 archived cases were used for phenotypic detection and prognostic analysis. We found that CD25 was expressed by most tumor cells in all samples, and CD56(+)CD25(+) cells were the predominant population in the mouse model, the 2 cell lines, and 10 of the 16 fresh tumor samples; in the other 6 fresh tumor samples, the predominant cell population was of the CD16(+)CD25(+) phenotype, and only a minor population showed the CD56(+)CD25(+) phenotype. The phenotype detected by immunohistochemistry staining generally was consistent with the phenotype found by flow cytometry immunophenotyping. According to the expression of CD56 and CD16, 115 cases could be classified into 3 phenotypic subtypes: CD56(-)CD16(-), CD56(+)CD16(-), and CD56(dim/-)CD16(+). Patients with tumors of the CD56(dim/-)CD16(+) phenotype had a poorer prognosis than patients with tumors of the other phenotypes. Differentiation of extranodal natural killer/T-cell lymphoma, nasal type apparently resembles the normal natural killer cell developmental pattern, and these tumors can be classified into 3 phenotypic subtypes of different aggressiveness. Expression of CD56(dim/-)CD16(+) implies a poorer prognosis. Copyright © 2014 Elsevier Inc. All rights reserved.

The osteo-inductive activity of bone-marrow-derived mononuclear cells resides within the CD14+ population and is independent of the CD34+ population.

PubMed

Henrich, D; Seebach, C; Verboket, R; Schaible, A; Marzi, I; Bonig, H

2018-03-06

Bone marrow mononuclear cells (BMC) seeded on a scaffold of β-tricalcium phosphate (β-TCP) promote bone healing in a critical-size femur defect model. Being BMC a mixed population of predominantly mature haematopoietic cells, which cell type(s) is(are) instrumental for healing remains elusive. Although clinical therapies using BMC are often dubbed as stem cell therapies, whether stem cells are relevant for the therapeutic effects is unclear and, at least in the context of bone repair, seems dubious. Instead, in light of the critical contribution of monocytes and macrophages to tissue development, homeostasis and injury repair, in the current study it was hypothesised that BMC-mediated bone healing derived from the stem cell population. To test this hypothesis, bone remodelling studies were performed in an established athymic rats critical-size femoral defect model, with β-TCP scaffolds augmented with complete BMC or BMC immunomagnetically depleted of stem cells (CD34+) or monocytes/macrophages (CD14+). Bone healing was assessed 8 weeks after transplantation. Compared to BMC-augmented controls, when CD14- BMC, but not CD34- BMC were transplanted into the bone defect, femora possessed dramatically decreased biomechanical stability and new bone formation was markedly reduced, as measured by histology. The degree of vascularisation did not differ between the two groups. It was concluded that the monocyte fraction within the BMC provided critical osteo-inductive cues during fracture healing. Which factors were responsible at the molecular levels remained elusive. However, this study marked a significant progress towards elucidating the mechanisms by which BMC elicit their therapeutic effects, at least in bone regeneration.

Treatment with integrase inhibitor suggests a new interpretation of HIV RNA decay curves that reveals a subset of cells with slow integration

DOE PAGES

Cardozo, Erwing Fabian; Andrade, Adriana; Mellors, John W.; ...

2017-07-05

The kinetics of HIV-1 decay under treatment depends on the class of antiretrovirals used. Mathematical models are useful to interpret the different profiles, providing quantitative information about the kinetics of virus replication and the cell populations contributing to viral decay. We modeled proviral integration in short- and long-lived infected cells to compare viral kinetics under treatment with and without the integrase inhibitor raltegravir (RAL). We fitted the model to data obtained from participants treated with RAL-containing regimes or with a four-drug regimen of protease and reverse transcriptase inhibitors. Our model explains the existence and quantifies the three phases of HIV-1more » RNA decay in RAL-based regimens vs. the two phases observed in therapies without RAL. Our findings indicate that HIV-1 infection is mostly sustained by short-lived infected cells with fast integration and a short viral production period, and by long-lived infected cells with slow integration but an equally short viral production period. We propose that these cells represent activated and resting infected CD4+ T-cells, respectively, and estimate that infection of resting cells represent ~4% of productive reverse transcription events in chronic infection. RAL reveals the kinetics of proviral integration, showing that in short-lived cells the pre-integration population has a half-life of ~7 hours, whereas in long-lived cells this half-life is ~6 weeks. We also show that the efficacy of RAL can be estimated by the difference in viral load at the start of the second phase in protocols with and without RAL. Altogether, we provide a mechanistic model of viral infection that parsimoniously explains the kinetics of viral load decline under multiple classes of antiretrovirals.« less

Treatment with integrase inhibitor suggests a new interpretation of HIV RNA decay curves that reveals a subset of cells with slow integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cardozo, Erwing Fabian; Andrade, Adriana; Mellors, John W.

The kinetics of HIV-1 decay under treatment depends on the class of antiretrovirals used. Mathematical models are useful to interpret the different profiles, providing quantitative information about the kinetics of virus replication and the cell populations contributing to viral decay. We modeled proviral integration in short- and long-lived infected cells to compare viral kinetics under treatment with and without the integrase inhibitor raltegravir (RAL). We fitted the model to data obtained from participants treated with RAL-containing regimes or with a four-drug regimen of protease and reverse transcriptase inhibitors. Our model explains the existence and quantifies the three phases of HIV-1more » RNA decay in RAL-based regimens vs. the two phases observed in therapies without RAL. Our findings indicate that HIV-1 infection is mostly sustained by short-lived infected cells with fast integration and a short viral production period, and by long-lived infected cells with slow integration but an equally short viral production period. We propose that these cells represent activated and resting infected CD4+ T-cells, respectively, and estimate that infection of resting cells represent ~4% of productive reverse transcription events in chronic infection. RAL reveals the kinetics of proviral integration, showing that in short-lived cells the pre-integration population has a half-life of ~7 hours, whereas in long-lived cells this half-life is ~6 weeks. We also show that the efficacy of RAL can be estimated by the difference in viral load at the start of the second phase in protocols with and without RAL. Altogether, we provide a mechanistic model of viral infection that parsimoniously explains the kinetics of viral load decline under multiple classes of antiretrovirals.« less

Tumour resistance to cisplatin: a modelling approach

NASA Astrophysics Data System (ADS)

Marcu, L.; Bezak, E.; Olver, I.; van Doorn, T.

2005-01-01

Although chemotherapy has revolutionized the treatment of haematological tumours, in many common solid tumours the success has been limited. Some of the reasons for the limitations are: the timing of drug delivery, resistance to the drug, repopulation between cycles of chemotherapy and the lack of complete understanding of the pharmacokinetics and pharmacodynamics of a specific agent. Cisplatin is among the most effective cytotoxic agents used in head and neck cancer treatments. When modelling cisplatin as a single agent, the properties of cisplatin only have to be taken into account, reducing the number of assumptions that are considered in the generalized chemotherapy models. The aim of the present paper is to model the biological effect of cisplatin and to simulate the consequence of cisplatin resistance on tumour control. The 'treated' tumour is a squamous cell carcinoma of the head and neck, previously grown by computer-based Monte Carlo techniques. The model maintained the biological constitution of a tumour through the generation of stem cells, proliferating cells and non-proliferating cells. Cell kinetic parameters (mean cell cycle time, cell loss factor, thymidine labelling index) were also consistent with the literature. A sensitivity study on the contribution of various mechanisms leading to drug resistance is undertaken. To quantify the extent of drug resistance, the cisplatin resistance factor (CRF) is defined as the ratio between the number of surviving cells of the resistant population and the number of surviving cells of the sensitive population, determined after the same treatment time. It is shown that there is a supra-linear dependence of CRF on the percentage of cisplatin-DNA adducts formed, and a sigmoid-like dependence between CRF and the percentage of cells killed in resistant tumours. Drug resistance is shown to be a cumulative process which eventually can overcome tumour regression leading to treatment failure.

Intratubular transplantation as a strategy for establishing animal models of testicular germ cell tumours

PubMed Central

Li, Yunmin; Kido, Tatsuo; Luo, Jinping; Fukuda, Michiko; Dobrinski, Ina; Lau, Yun-Fai Chris

2008-01-01

Testicular germ cell tumours (TGCTs) are prevalent cancers among young men. Currently, there is no reliable animal model for TGCTs. To establish such animal models, we have explored the possibility of intratubular testicular transplantation as means to deliver tumour cells into the seminiferous tubules of host animals. Our results demonstrated that transplanted cells could effectively populate the testis of a recipient mouse and develop into TGCTs. In addition, the donor cells could be transfected with a specific transgene before transplantation, thereby providing an approach to evaluate the specific effects of gene functions in the oncogenic processes. Hence, depending on selection of specific donor cells or mixtures of donor cells, transplantation models of TGCTs could be significant for studies on the pathogenesis, diagnosis and therapies of such a prevalent and important cancer in men. PMID:18808526

Differentiated cell behavior: a multiscale approach using measure theory.

PubMed

Colombi, Annachiara; Scianna, Marco; Tosin, Andrea

2015-11-01

This paper deals with the derivation of a collective model of cell populations out of an individual-based description of the underlying physical particle system. By looking at the spatial distribution of cells in terms of time-evolving measures, rather than at individual cell paths, we obtain an ensemble representation stemming from the phenomenological behavior of the single component cells. In particular, as a key advantage of our approach, the scale of representation of the system, i.e., microscopic/discrete vs. macroscopic/continuous, can be chosen a posteriori according only to the spatial structure given to the aforesaid measures. The paper focuses in particular on the use of different scales based on the specific functions performed by cells. A two-population hybrid system is considered, where cells with a specialized/differentiated phenotype are treated as a discrete population of point masses while unspecialized/undifferentiated cell aggregates are represented by a continuous approximation. Numerical simulations and analytical investigations emphasize the role of some biologically relevant parameters in determining the specific evolution of such a hybrid cell system.

Effect of Inhibition of Deoxyribonucleic Acid and Protein Synthesis on the Direction of Cell Wall Growth in Streptococcus faecalis

PubMed Central

Higgins, M. L.; Daneo-Moore, L.; Boothby, D.; Shockman, G. D.

1974-01-01

Selective inhibition of protein synthesis in Streptococcus faecalis (ATCC 9790) was accompanied by a rapid and severe inhibition of cell division and a reduction of enlargement of cellular surface area. Continued synthesis of cell wall polymers resulted in rapid thickening of the wall to an extent not seen in exponential-phase populations. Thus, the normal direction of wall growth was changed from a preferential feeding out of new wall surface to that of thickening existing cell surfaces. However, the overall manner in which the wall thickened, from nascent septa toward polar regions, was the same in both exponential-phase and inhibited populations. In contrast, selective inhibition of deoxyribonucleic acid (DNA) synthesis using mitomycin C was accompanied by an increase in cellular surface area and by division of about 80% of the cells in random populations. Little or no wall thickening was observed until the synthesis of macromolecules other than DNA was impaired and further cell division ceased. Concomitant inhibition of both DNA and protein synthesis inhibited cell division but permitted an increase in average cell volume. In such doubly inhibited cells, walls thickened less than in cells inhibited for protein synthesis only. On the basis of the results obtained, a model for cell surface enlargement and cell division is presented. The model proposes that: (i) each wall enlargement site is influenced by an individual chromosome replication cycle; (ii) during chromosome replication peripheral surface enlargement would be favored over thickening (or septation); (iii) a signal associated with chromosome termination would favor thickening (and septation) at the expense of surface enlargement; and (iv) a factor or signal related to protein synthesis would be required for one or more of the near terminal stages of cell division or cell separation, or both. Images PMID:4133352

Relationships of pancreatic beta-cell function with microalbuminuria and glomerular filtration rate in middle-aged and elderly population without type 2 diabetes mellitus: a Chinese community-based analysis.

PubMed

Fu, Shihui; Zhou, Shanjing; Luo, Leiming; Ye, Ping

2017-01-01

Relationships of pancreatic beta-cell function abnormality with microalbuminuria (MA) and glomerular filtration rate (GFR) may differ by age, ethnicity and accompanied diseases. Previous studies were generally conducted in Western adult patients with type 2 diabetes mellitus (T2DM), and it is uncertain whether pancreatic beta-cell function is associated with MA and GFR in Chinese community-dwelling middle-aged and elderly population without T2DM. We therefore examined the relationships of pancreatic beta-cell function with two indices of renal damage, MA and GFR, in Chinese community-dwelling middle-aged and elderly population without T2DM. This analysis focused on 380 Beijing residents older than 45 years who were free of T2DM and completed the evaluation of pancreatic beta-cell function. Median age was 67 (49-80) years. Levels of triglyceride, diastolic blood pressure and homeostasis model assessment-beta (HOMA-beta) index were positively related to urine microalbumin ( P <0.05 for all). Age, low-density lipoprotein cholesterol levels and HOMA-beta index were inversely correlated with GFR, while high-density lipoprotein cholesterol levels were positively correlated with GFR ( P <0.05 for all). In all three adjustment models, there was a significant positive association between HOMA-beta index and MA; subjects with higher beta-cell function had higher odds of MA ( P <0.05 for all). There was no association between HOMA-beta index and GFR <60 mL/min/1.73 m 2 in any model ( P >0.05 for all). Modeling the pancreatic beta-cell function with different adjusted variables provided the same conclusion of association with MA; beta-cell function was positively associated with MA. Additionally, there was a specific difference in the adjusted associations of pancreatic beta-cell function with MA and GFR <60 mL/min/1.73 m 2 ; beta-cell function was not independently associated with GFR <60 mL/min/1.73 m 2 . This result indicated that abnormal pancreatic beta-cell function plays an important role in the development of MA.

Quasispecies dynamics and the emergence of drug resistance during zidovudine therapy of HIV infection.

PubMed

Frost, S D; McLean, A R

1994-03-01

To investigate the roles of mutation, competition and population dynamics in the emergence of drug resistant mutants during zidovudine therapy. A mathematical model of the population dynamics of the viral quasispecies during zidovudine therapy was investigated. The model was used to simulate changes in the numbers of uninfected and infected cells and the composition of the viral quasispecies in the years following initiation of therapy. Resulting scenarios in asymptomatic and AIDS patients were compared. The model was also used to investigate the efficacy of a treatment regimen involving alternating zidovudine and dideoxyinosine therapy. The behaviour of the model can be divided into three stages. Before therapy, mutation maintains a small pool of resistant mutants, outcompeted to very low levels by sensitive strains. When therapy begins there is a dramatic fall in the total viral load and resistant strains suddenly have the competitive advantage. Thus, it is resistant strains that infect the rising number of uninfected CD4+ cells. During this second stage the rapid effects of population dynamics swamp any effects of mutation between strains. When the populations of infected and uninfected cells approach their treatment equilibrium levels, mutation again becomes important in the slow generation of highly resistant strains. The short-term reduction in viral replication at the initiation of therapy generates a pool of uninfected cells which cause the eventual increase in viral burden. This increase is associated with (but not caused by) a rise in frequency of resistant strains which are at a competitive advantage in the presence of the drug. When therapy is ceased, reversion of resistance is slow as resistant strains are nearly as fit as sensitive strains in the absence of drug.

Representation of memories in the cortical-hippocampal system: Results from the application of population similarity analyses

PubMed Central

McKenzie, Sam; Keene, Chris; Farovik, Anja; Blandon, John; Place, Ryan; Komorowski, Robert; Eichenbaum, Howard

2016-01-01

Here we consider the value of neural population analysis as an approach to understanding how information is represented in the hippocampus and cortical areas and how these areas might interact as a brain system to support memory. We argue that models based on sparse coding of different individual features by single neurons in these areas (e.g., place cells, grid cells) are inadequate to capture the complexity of experience represented within this system. By contrast, population analyses of neurons with denser coding and mixed selectivity reveal new and important insights into the organization of memories. Furthermore, comparisons of the organization of information in interconnected areas suggest a model of hippocampal-cortical interactions that mediates the fundamental features of memory. PMID:26748022

The requirement for freshly isolated human colorectal cancer (CRC) cells in isolating CRC stem cells.

PubMed

Fan, F; Bellister, S; Lu, J; Ye, X; Boulbes, D R; Tozzi, F; Sceusi, E; Kopetz, S; Tian, F; Xia, L; Zhou, Y; Bhattacharya, R; Ellis, L M

2015-02-03

Isolation of colorectal cancer (CRC) cell populations enriched for cancer stem cells (CSCs) may facilitate target identification. There is no consensus regarding the best methods for isolating CRC stem cells (CRC-SCs). We determined the suitability of various cellular models and various stem cell markers for the isolation of CRC-SCs. Established human CRC cell lines, established CRC cell lines passaged through mice, patient-derived xenograft (PDX)-derived cells, early passage/newly established cell lines, and cells directly from clinical specimens were studied. Cells were FAC-sorted for the CRC-SC markers CD44, CD133, and aldehyde dehydrogenase (ALDH). Sphere formation and in vivo tumorigenicity studies were used to validate CRC-SC enrichment. None of the markers studied in established cell lines, grown either in vitro or in vivo, consistently enriched for CRC-SCs. In the three other cellular models, CD44 and CD133 did not reliably enrich for stemness. In contrast, freshly isolated PDX-derived cells or early passage/newly established CRC cell lines with high ALDH activity formed spheres in vitro and enhanced tumorigenicity in vivo, whereas cells with low ALDH activity did not. PDX-derived cells, early passages/newly established CRC cell lines and cells from clinical specimen with high ALDH activity can be used to identify CRC-SC-enriched populations. Established CRC cell lines should not be used to isolate CSCs.

Dedifferentiation of Glioma Cells to Glioma Stem-like Cells By Therapeutic Stress-induced HIF Signaling in the Recurrent GBM Model.

PubMed

Lee, Gina; Auffinger, Brenda; Guo, Donna; Hasan, Tanwir; Deheeger, Marc; Tobias, Alex L; Kim, Jeong Yeon; Atashi, Fatemeh; Zhang, Lingjiao; Lesniak, Maciej S; James, C David; Ahmed, Atique U

2016-12-01

Increasing evidence exposes a subpopulation of cancer cells, known as cancer stem cells (CSCs), to be critical for the progression of several human malignancies, including glioblastoma multiforme. CSCs are highly tumorigenic, capable of self-renewal, and resistant to conventional therapies, and thus considered to be one of the key contributors to disease recurrence. To elucidate the poorly understood evolutionary path of tumor recurrence and the role of CSCs in this process, we developed patient-derived xenograft glioblastoma recurrent models induced by anti-glioma chemotherapy, temozolomide. In this model, we observed a significant phenotypic shift towards an undifferentiated population. We confirmed these findings in vitro as sorted CD133-negative populations cultured in differentiation-forcing media were found to acquire CD133 expression following chemotherapy treatment. To investigate this phenotypic switch at the single-cell level, glioma stem cell (GSC)-specific promoter-based reporter systems were engineered to track changes in the GSC population in real time. We observed the active phenotypic and functional switch of single non-stem glioma cells to a stem-like state and that temozolomide therapy significantly increased the rate of single-cell conversions. Importantly, we showed the therapy-induced hypoxia-inducible factors (HIF) 1α and HIF2α play key roles in allowing non-stem glioma cells to acquire stem-like traits, as the expression of both HIFs increase upon temozolomide therapy and knockdown of HIFs expression inhibits the interconversion between non-stem glioma cells and GSCs post-therapy. On the basis of our results, we propose that anti-glioma chemotherapy promotes the accumulation of HIFs in the glioblastoma multiforme cells that induces the formation of therapy-resistant GSCs responsible for recurrence. Mol Cancer Ther; 15(12); 3064-76. ©2016 AACR. ©2016 American Association for Cancer Research.

Polymorphonuclear Neutrophils Are Necessary for the Recruitment of CD8+ T Cells in the Liver in a Pregnant Mouse Model of Chlamydophila abortus (Chlamydia psittaci Serotype 1) Infection

PubMed Central

de Oca, Roberto Montes; Buendía, Antonio J.; Del Río, Laura; Sánchez, Joaquín; Salinas, Jesús; Navarro, Jose A.

2000-01-01

The role of polymorphonuclear neutrophils (PMNs) in the development of the specific immune response against Chlamydophila abortus (Chlamydia psittaci serotype 1) infection was studied in a pregnant mouse model involving treatment with RB6-8C5 monoclonal antibody. PMN depletion significantly affected the immune response in the liver, in which the T-lymphocyte and F4/80+ cell populations decreased, particularly the CD8+ T-cell population. A Th1-like response, characterized by high levels of gamma interferon without detectable levels of interleukin 4 (IL-4) in serum, was observed in both depleted and nondepleted mice, although an increased production of IL-10 was detected in the depleted group. Our results suggest that PMNs play a very important role in the recruitment of other leukocyte populations to the inflammatory foci but have little influence in the polarization of the immune specific response toward a Th1-like response. PMID:10679002

From Experiment to Theory: What Can We Learn from Growth Curves?

PubMed

Kareva, Irina; Karev, Georgy

2018-01-01

Finding an appropriate functional form to describe population growth based on key properties of a described system allows making justified predictions about future population development. This information can be of vital importance in all areas of research, ranging from cell growth to global demography. Here, we use this connection between theory and observation to pose the following question: what can we infer about intrinsic properties of a population (i.e., degree of heterogeneity, or dependence on external resources) based on which growth function best fits its growth dynamics? We investigate several nonstandard classes of multi-phase growth curves that capture different stages of population growth; these models include hyperbolic-exponential, exponential-linear, exponential-linear-saturation growth patterns. The constructed models account explicitly for the process of natural selection within inhomogeneous populations. Based on the underlying hypotheses for each of the models, we identify whether the population that it best fits by a particular curve is more likely to be homogeneous or heterogeneous, grow in a density-dependent or frequency-dependent manner, and whether it depends on external resources during any or all stages of its development. We apply these predictions to cancer cell growth and demographic data obtained from the literature. Our theory, if confirmed, can provide an additional biomarker and a predictive tool to complement experimental research.

Feline mammary carcinoma stem cells are tumorigenic, radioresistant, chemoresistant and defective in activation of the ATM/p53 DNA damage pathway

PubMed Central

Pang, L.Y.; Blacking, T.M.; Else, R.W.; Sherman, A.; Sang, H.M.; Whitelaw, B.A.; Hupp, T.R.; Argyle, D.J.

2013-01-01

Cancer stem cells were identified in a feline mammary carcinoma cell line by demonstrating expression of CD133 and utilising the tumour sphere assay. A population of cells was identified that had an invasive, mesenchymal phenotype, expressed markers of pluripotency and enhanced tumour formation in the NOD-SCID mouse and chick embryo models. This population of feline mammary carcinoma stem cells was resistant to chemotherapy and radiation, possibly due to aberrant activation of the ATM/p53 DNA damage pathway. Epithelial–mesenchymal transition was a feature of the invasive phenotype. These data demonstrate that cancer stem cells are a feature of mammary cancer in cats. PMID:23219486

General statistics of stochastic process of gene expression in eukaryotic cells.

PubMed Central

Kuznetsov, V A; Knott, G D; Bonner, R F

2002-01-01

Thousands of genes are expressed at such very low levels (< or =1 copy per cell) that global gene expression analysis of rarer transcripts remains problematic. Ambiguity in identification of rarer transcripts creates considerable uncertainty in fundamental questions such as the total number of genes expressed in an organism and the biological significance of rarer transcripts. Knowing the distribution of the true number of genes expressed at each level and the corresponding gene expression level probability function (GELPF) could help resolve these uncertainties. We found that all observed large-scale gene expression data sets in yeast, mouse, and human cells follow a Pareto-like distribution model skewed by many low-abundance transcripts. A novel stochastic model of the gene expression process predicts the universality of the GELPF both across different cell types within a multicellular organism and across different organisms. This model allows us to predict the frequency distribution of all gene expression levels within a single cell and to estimate the number of expressed genes in a single cell and in a population of cells. A random "basal" transcription mechanism for protein-coding genes in all or almost all eukaryotic cell types is predicted. This fundamental mechanism might enhance the expression of rarely expressed genes and, thus, provide a basic level of phenotypic diversity, adaptability, and random monoallelic expression in cell populations. PMID:12136033

Individual cell lag time distributions of Cronobacter (Enterobacter sakazakii) and impact of pooling samples on its detection in powdered infant formula.

PubMed

Miled, Rabeb Bennour; Guillier, Laurent; Neves, Sandra; Augustin, Jean-Christophe; Colin, Pierre; Besse, Nathalie Gnanou

2011-06-01

Cells of six strains of Cronobacter were subjected to dry stress and stored for 2.5 months at ambient temperature. The individual cell lag time distributions of recovered cells were characterized at 25 °C and 37 °C in non-selective broth. The individual cell lag times were deduced from the times taken by cultures from individual cells to reach an optical density threshold. In parallel, growth curves for each strain at high contamination levels were determined in the same growth conditions. In general, the extreme value type II distribution with a shape parameter fixed to 5 (EVIIb) was the most effective at describing the 12 observed distributions of individual cell lag times. Recently, a model for characterizing individual cell lag time distribution from population growth parameters was developed for other food-borne pathogenic bacteria such as Listeria monocytogenes. We confirmed this model's applicability to Cronobacter by comparing the mean and the standard deviation of individual cell lag times to populational lag times observed with high initial concentration experiments. We also validated the model in realistic conditions by studying growth in powdered infant formula decimally diluted in Buffered Peptone Water, which represents the first enrichment step of the standard detection method for Cronobacter. Individual lag times and the pooling of samples significantly affect detection performances. Copyright © 2010 Elsevier Ltd. All rights reserved.

Mathematical modeling provides kinetic details of the human immune response to vaccination

PubMed Central

Le, Dustin; Miller, Joseph D.; Ganusov, Vitaly V.

2015-01-01

With major advances in experimental techniques to track antigen-specific immune responses many basic questions on the kinetics of virus-specific immunity in humans remain unanswered. To gain insights into kinetics of T and B cell responses in human volunteers we combined mathematical models and experimental data from recent studies employing vaccines against yellow fever and smallpox. Yellow fever virus-specific CD8 T cell population expanded slowly with the average doubling time of 2 days peaking 2.5 weeks post immunization. Interestingly, we found that the peak of the yellow fever-specific CD8 T cell response was determined by the rate of T cell proliferation and not by the precursor frequency of antigen-specific cells as has been suggested in several studies in mice. We also found that while the frequency of virus-specific T cells increased slowly, the slow increase could still accurately explain clearance of yellow fever virus in the blood. Our additional mathematical model described well the kinetics of virus-specific antibody-secreting cell and antibody response to vaccinia virus in vaccinated individuals suggesting that most of antibodies in 3 months post immunization were derived from the population of circulating antibody-secreting cells. Taken together, our analysis provided novel insights into mechanisms by which live vaccines induce immunity to viral infections and highlighted challenges of applying methods of mathematical modeling to the current, state-of-the-art yet limited immunological data. PMID:25621280

Mathematical modeling provides kinetic details of the human immune response to vaccination.

PubMed

Le, Dustin; Miller, Joseph D; Ganusov, Vitaly V

2014-01-01

With major advances in experimental techniques to track antigen-specific immune responses many basic questions on the kinetics of virus-specific immunity in humans remain unanswered. To gain insights into kinetics of T and B cell responses in human volunteers we combined mathematical models and experimental data from recent studies employing vaccines against yellow fever and smallpox. Yellow fever virus-specific CD8 T cell population expanded slowly with the average doubling time of 2 days peaking 2.5 weeks post immunization. Interestingly, we found that the peak of the yellow fever-specific CD8 T cell response was determined by the rate of T cell proliferation and not by the precursor frequency of antigen-specific cells as has been suggested in several studies in mice. We also found that while the frequency of virus-specific T cells increased slowly, the slow increase could still accurately explain clearance of yellow fever virus in the blood. Our additional mathematical model described well the kinetics of virus-specific antibody-secreting cell and antibody response to vaccinia virus in vaccinated individuals suggesting that most of antibodies in 3 months post immunization were derived from the population of circulating antibody-secreting cells. Taken together, our analysis provided novel insights into mechanisms by which live vaccines induce immunity to viral infections and highlighted challenges of applying methods of mathematical modeling to the current, state-of-the-art yet limited immunological data.

Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; Coutinho, Sérgio; Zorzenon dos Santos, Rita Maria; de Figueirêdo, Pedro Hugo

2013-10-01

The dynamics of human immunodeficiency virus infection under antiretroviral therapy is investigated using a cellular automata model where the effectiveness of each drug is self-adjusted by the concentration of CD4+ T infected cells present at each time step. The effectiveness of the drugs and the infected cell concentration at the beginning of treatment are the control parameters of the cell population’s dynamics during therapy. The model allows describing processes of mono and combined therapies. The dynamics that emerges from this model when considering combined antiretroviral therapies reproduces with fair qualitative agreement the phases and different time scales of the process. As observed in clinical data, the results reproduce the significant decrease in the population of infected cells and a concomitant increase of the population of healthy cells in a short timescale (weeks) after the initiation of treatment. Over long time scales, early treatment with potent drugs may lead to undetectable levels of infection. For late treatment or treatments starting with a low density of CD4+ T healthy cells it was observed that the treatment may lead to a steady state in which the T cell counts are above the threshold associated with the onset of AIDS. The results obtained are validated through comparison to available clinical trial data.

Kinetic Modeling of ABCG2 Transporter Heterogeneity: A Quantitative, Single-Cell Analysis of the Side Population Assay

PubMed Central

Prasanphanich, Adam F.; White, Douglas E.; Gran, Margaret A.

2016-01-01

The side population (SP) assay, a technique used in cancer and stem cell research, assesses the activity of ABC transporters on Hoechst staining in the presence and absence of transporter inhibition, identifying SP and non-SP cell (NSP) subpopulations by differential staining intensity. The interpretation of the assay is complicated because the transporter-mediated mechanisms fail to account for cell-to-cell variability within a population or adequately control the direct role of transporter activity on staining intensity. We hypothesized that differences in dye kinetics at the single-cell level, such as ABCG2 transporter-mediated efflux and DNA binding, are responsible for the differential cell staining that demarcates SP/NSP identity. We report changes in A549 phenotype during time in culture and with TGFβ treatment that correlate with SP size. Clonal expansion of individually sorted cells re-established both SP and NSPs, indicating that SP membership is dynamic. To assess the validity of a purely kinetics-based interpretation of SP/NSP identity, we developed a computational approach that simulated cell staining within a heterogeneous cell population; this exercise allowed for the direct inference of the role of transporter activity and inhibition on cell staining. Our simulated SP assay yielded appropriate SP responses for kinetic scenarios in which high transporter activity existed in a portion of the cells and little differential staining occurred in the majority of the population. With our approach for single-cell analysis, we observed SP and NSP cells at both ends of a transporter activity continuum, demonstrating that features of transporter activity as well as DNA content are determinants of SP/NSP identity. PMID:27851764

A tissue-engineered subcutaneous pancreatic cancer model for antitumor drug evaluation.

PubMed

He, Qingyi; Wang, Xiaohui; Zhang, Xing; Han, Huifang; Han, Baosan; Xu, Jianzhong; Tang, Kanglai; Fu, Zhiren; Yin, Hao

2013-01-01

The traditional xenograft subcutaneous pancreatic cancer model is notorious for its low incidence of tumor formation, inconsistent results for the chemotherapeutic effects of drug molecules of interest, and a poor predictive capability for the clinical efficacy of novel drugs. These drawbacks are attributed to a variety of factors, including inoculation of heterogeneous tumor cells from patients with different pathological histories, and use of poorly defined Matrigel(®). In this study, we aimed to tissue-engineer a pancreatic cancer model that could readily cultivate a pancreatic tumor derived from highly homogenous CD24(+)CD44(+) pancreatic cancer stem cells delivered by a well defined electrospun scaffold of poly(glycolide-co-trimethylene carbonate) and gelatin. The scaffold supported in vitro tumorigenesis from CD24(+)CD44(+) cancer stem cells for up to 7 days without inducing apoptosis. Moreover, CD24(+)CD44(+) cancer stem cells delivered by the scaffold grew into a native-like mature pancreatic tumor within 8 weeks in vivo and exhibited accelerated tumorigenesis as well as a higher incidence of tumor formation than the traditional model. In the scaffold model, we discovered that oxaliplatin-gemcitabine (OXA-GEM), a chemotherapeutic regimen, induced tumor regression whereas gemcitabine alone only capped tumor growth. The mechanistic study attributed the superior antitumorigenic performance of OXA-GEM to its ability to induce apoptosis of CD24(+)CD44(+) cancer stem cells. Compared with the traditional model, the scaffold model demonstrated a higher incidence of tumor formation and accelerated tumor growth. Use of a tiny population of highly homogenous CD24(+)CD44(+) cancer stem cells delivered by a well defined scaffold greatly reduces the variability associated with the traditional model, which uses a heterogeneous tumor cell population and poorly defined Matrigel. The scaffold model is a robust platform for investigating the antitumorigenesis mechanism of novel chemotherapeutic drugs with a special focus on cancer stem cells.

Population activity statistics dissect subthreshold and spiking variability in V1.

PubMed

Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

2017-07-01

Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of variability. Our work shows that stimulus-dependent changes in pairwise but not in single-cell statistics can differentiate between two widely used models of neuronal variability. Contrasting model predictions with neuronal data provides hints on the noise sources in spiking and provides constraints on statistical models of population activity. Copyright © 2017 the American Physiological Society.

Side population cells of pancreatic cancer show characteristics of cancer stem cells responsible for resistance and metastasis.

PubMed

Niess, Hanno; Camaj, Peter; Renner, Andrea; Ischenko, Ivan; Zhao, Yue; Krebs, Stefan; Mysliwietz, Josef; Jäckel, Carsten; Nelson, Peter J; Blum, Helmut; Jauch, Karl-Walter; Ellwart, Joachim W; Bruns, Christiane J

2015-06-01

Cancer stem cells (CSCs) have been proposed to underlie the initiation and maintenance of tumor growth and the development of chemoresistance in solid tumors. The identification and role of these important cells in pancreatic cancer remains controversial. Here, we isolate side population (SP) cells from the highly aggressive and metastatic human pancreatic cancer cell line L3.6pl and evaluate their potential role as models for CSCs. SP cells were isolated following Hoechst 33342 staining of L3.6pl cells. SP, non-SP, and unsorted L3.6pl cells were orthotopically xenografted into the pancreas of nude mice and tumor growth observed. RNA was analyzed by whole genome array and pathway mapping was performed. Drug resistant variants of L3.6pl were developed and examined for SP proportions and evaluated for surface expression of known CSC markers. A distinct SP with the ability to self-renew and differentiate into non-SP cells was isolated from L3.6pl (0.9 % ± 0.22). SP cells showed highly tumorigenic and metastatic characteristics after orthotopic injection. Transcriptomic analysis identified modulation of gene networks linked to tumorigenesis, differentiation, and metastasization in SP cells relative to non-SP cells. Wnt, NOTCH, and EGFR signaling pathways associated with tumor stem cells were altered in SP cells. When cultured with increasing concentrations of gemcitabine, the proportion of SP cells, ABCG2(+), and CD24(+) cells were significantly enriched, whereas 5-fluorouracil (5-FU) treatment lowered the percentage of SP cells. SP cells were distinct from cells positive for previously postulated pancreatic CSC markers. The Hoechst-induced side population in L3.6pl cells comprises a subset of tumor cells displaying aggressive growth and metastasization, increased gemcitabine-, but not 5-FU resistance. The cells may act as a partial model for CSC biology.

Fetal liver contains committed NK progenitors, but is not a site for development of CD34+ cells into T cells.

PubMed

Jaleco, A C; Blom, B; Res, P; Weijer, K; Lanier, L L; Phillips, J H; Spits, H

1997-07-15

The presence of T and NK cells in the human fetal liver and the fact that fetal liver hemopoietic progenitor cells develop into T and NK cells suggest a role for the fetal liver compartment in T and NK cell development. In this work, we show that the capacity of fetal liver progenitors to develop into T cells, in a human/mouse fetal thymic organ culture system, is restricted to an immature subset of CD34+ CD38- cells. No T cell-committed precursors are contained within the more differentiated CD34+ CD38+ population. This conclusion is supported by the observations that no TCR-delta gene rearrangements and no pre-TCR-alpha expression can be detected in this population. However, NK cells were derived from CD34+ CD38- and CD34+ CD38+ fetal liver cells cultured in the presence of IL-15, IL-7, and Flt-3 ligand. Eighty to ninety percent of cells arising from the CD34+ CD38+ population expressed the NK cell-associated markers CD56, CD16, CD94, and NKR-P1A. Several subpopulations of NK cell precursors were identified by differential expression of these receptors. Based on the detection of populations with a similar antigenic profile in freshly isolated fetal liver cells, we propose a model of NK cell differentiation. Collectively, our findings suggest that CD34+ cells differentiate into NK cells, but not into mature T cells, in the human fetal liver.

Neural Stem Cells Derived Directly from Adipose Tissue.

PubMed

Petersen, Eric D; Zenchak, Jessica R; Lossia, Olivia V; Hochgeschwender, Ute

2018-05-01

Neural stem cells (NSCs) are characterized as self-renewing cell populations with the ability to differentiate into the multiple tissue types of the central nervous system. These cells can differentiate into mature neurons, astrocytes, and oligodendrocytes. This category of stem cells has been shown to be a promisingly effective treatment for neurodegenerative diseases and neuronal injury. Most treatment studies with NSCs in animal models use embryonic brain-derived NSCs. This approach presents both ethical and feasibility issues for translation to human patients. Adult tissue is a more practical source of stem cells for transplantation therapies in humans. Some adult tissues such as adipose tissue and bone marrow contain a wide variety of stem cell populations, some of which have been shown to be similar to embryonic stem cells, possessing many pluripotent properties. Of these stem cell populations, some are able to respond to neuronal growth factors and can be expanded in vitro, forming neurospheres analogous to cells harvested from embryonic brain tissue. In this study, we describe a method for the collection and culture of cells from adipose tissue that directly, without going through intermediates such as mesenchymal stem cells, results in a population of NSCs that are able to be expanded in vitro and be differentiated into functional neuronal cells. These adipose-derived NSCs display a similar phenotype to those directly derived from embryonic brain. When differentiated into neurons, cells derived from adipose tissue have spontaneous spiking activity with network characteristics similar to that of neuronal cultures.

Hpm of Estrogen Model on the Dynamics of Breast Cancer

NASA Astrophysics Data System (ADS)

Govindarajan, A.; Balamuralitharan, S.; Sundaresan, T.

2018-04-01

We enhance a deterministic mathematical model involving universal dynamics on breast cancer with immune response. This is population model so includes Normal cells class, Tumor cells, Immune cells and Estrogen. The eects regarding Estrogen are below incorporated in the model. The effects show to that amount the arrival of greater Estrogen increases the danger over growing breast cancer. Furthermore, approximate solution regarding nonlinear differential equations is arrived by Homotopy Perturbation Method (HPM). Hes HPM is good and correct technique after solve nonlinear differential equation directly. Approximate solution learnt with the support of that method is suitable same as like the actual results in accordance with this models.

Phenotypes and distribution of mucosal memory B-cell populations in the SIV/SHIV Rhesus macaque model

PubMed Central

Demberg, Thorsten; Mohanram, Venkatramanan; Venzon, David; Robert-Guroff, Marjorie

2014-01-01

As vaccine-elicited antibodies have now been associated with HIV protective efficacy, a thorough understanding of mucosal and systemic B-cell development and maturation is needed. We phenotyped mucosal memory B-cells, investigated isotype expression and homing patterns, and defined plasmablasts and plasma cells at three mucosal sites (duodenum, jejunum and rectum) in rhesus macaques, the commonly used animal model for pre-clinical vaccine studies. Unlike humans, macaque mucosal memory B-cells lacked CD27 expression; only two sub-populations were present: naïve (CD21+CD27−) and tissue-like (CD21−CD27−) memory. Similar to humans, IgA was the dominant isotype expressed. The homing markers CXCR4, CCR6, CCR9 and α4β7 were differentially expressed between naïve and tissue-like memory B-cells. Mucosal plasmablasts were identified as CD19+CD20+/−HLA-DR+Ki-67+IRF4+CD138+/− and mucosal plasma cells as CD19+CD20−HLA-DR−Ki-67−IRF4+CD138+. Both populations were CD39+/−CD27−. Plasma cell phenotype was confirmed by spontaneous IgA secretion by ELISpot of positively-selected cells and J-chain expression by real-time PCR. Duodenal, jejunal and rectal samples were similar in B-cell memory phenotype, isotype expression, homing receptors and plasmablast/plasma cell distribution among the three tissues. Thus rectal biopsies adequately monitor B-cell dynamics in the gut mucosa, and provide a critical view of mucosal B-cell events associated with development of vaccine-elicited protective immune responses and SIV/SHIV pathogenesis and disease control. PMID:24814239

[A simplified model for kinetics of a tumor cells' population].

PubMed

Gut, R; Zharinov, G M; Iakubov, E

2009-01-01

A mathematical model of solid tumor growth is suggested. The external influence from the tumor-bearing organism is described separately for cell growth and apoptosis. The model is an ordinary differential equation which provides for use of a variety of dependences for both processes. A solution for a specific example of the processes is obtained in the form of a generalized logistic curve. Our results give clues for such experimental phenomena as spontaneous cessation of cell growth, dependence of life duration on insignificant variations in apoptosis, etc.

Morphological and functional maturation of Leydig cells: from rodent models to primates.

PubMed

Teerds, Katja J; Huhtaniemi, Ilpo T

2015-01-01

Leydig cells (LC) are the sites of testicular androgen production. Development of LC occurs in the testes of most mammalian species as two distinct growth phases, i.e. as fetal and pubertal/adult populations. In primates there are indications of a third neonatal growth phase. LC androgen production begins in embryonic life and is crucial for the intrauterine masculinization of the male fetal genital tract and brain, and continues until birth after which it rapidly declines. A short post-natal phase of LC activity in primates (including human) termed 'mini-puberty' precedes the period of juvenile quiescence. The adult population of LC evolves, depending on species, in mid- to late-prepuberty upon reawakening of the hypothalamic-pituitary-testicular axis, and these cells are responsible for testicular androgen production in adult life, which continues with a slight gradual decline until senescence. This review is an updated comparative analysis of the functional and morphological maturation of LC in model species with special reference to rodents and primates. Pubmed, Scopus, Web of Science and Google Scholar databases were searched between December 2012 and October 2014. Studies published in languages other than English or German were excluded, as were data in abstract form only. Studies available on primates were primarily examined and compared with available data from specific animal models with emphasis on rodents. Expression of different marker genes in rodents provides evidence that at least two distinct progenitor lineages give rise to the fetal LC (FLC) population, one arising from the coelomic epithelium and the other from specialized vascular-associated cells along the gonad-mesonephros border. There is general agreement that the formation and functioning of the FLC population in rodents is gonadotrophin-responsive but not gonadotrophin-dependent. In contrast, although there is in primates some controversy on the role of gonadotrophins in the formation of the FLC population, there is consensus about the essential role of gonadotrophins in testosterone production. Like the FLC population, adult Leydig cells (ALC) in rodents arise from stem cells, which have their origin in the fetal testis. In contrast, in primates the ALC population is thought to originate from FLC, which undergo several cycles of regression and redifferentiation before giving rise to the mature ALC population, as well as from differentiation of stem cells/precursor cells. Despite this difference in origin, both in primates and rodents the formation of the mature and functionally active ALC population is critically dependent on the pituitary gonadotrophin, LH. From studies on rodents considerable knowledge has emerged on factors that are involved besides LH in the regulation of this developmental process. Whether the same factors also play a role in the development of the mature primate LC population awaits further investigation. Distinct populations of LC develop along the life span of males, including fetal, neonatal (primates) and ALC. Despite differences in the LC lineages of rodents and primates, the end product is a mature population of LC with the main function to provide androgens necessary for the maintenance of spermatogenesis and extra-gonadal androgen actions. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The zebrafish tailbud contains two independent populations of midline progenitor cells that maintain long-term germ layer plasticity and differentiate in response to local signaling cues

PubMed Central

Row, Richard H.; Tsotras, Steve R.; Goto, Hana; Martin, Benjamin L.

2016-01-01

Vertebrate body axis formation depends on a population of bipotential neuromesodermal cells along the posterior wall of the tailbud that make a germ layer decision after gastrulation to form spinal cord and mesoderm. Despite exhibiting germ layer plasticity, these cells never give rise to midline tissues of the notochord, floor plate and dorsal endoderm, raising the question of whether midline tissues also arise from basal posterior progenitors after gastrulation. We show in zebrafish that local posterior signals specify germ layer fate in two basal tailbud midline progenitor populations. Wnt signaling induces notochord within a population of notochord/floor plate bipotential cells through negative transcriptional regulation of sox2. Notch signaling, required for hypochord induction during gastrulation, continues to act in the tailbud to specify hypochord from a notochord/hypochord bipotential cell population. Our results lend strong support to a continuous allocation model of midline tissue formation in zebrafish, and provide an embryological basis for zebrafish and mouse bifurcated notochord phenotypes as well as the rare human congenital split notochord syndrome. We demonstrate developmental equivalency between the tailbud progenitor cell populations. Midline progenitors can be transfated from notochord to somite fate after gastrulation by ectopic expression of msgn1, a master regulator of paraxial mesoderm fate, or if transplanted into the bipotential progenitors that normally give rise to somites. Our results indicate that the entire non-epidermal posterior body is derived from discrete, basal tailbud cell populations. These cells remain receptive to extracellular cues after gastrulation and continue to make basic germ layer decisions. PMID:26674311

Evolutionary dynamics of imatinib-treated leukemic cells by stochastic approach

NASA Astrophysics Data System (ADS)

Pizzolato, Nicola; Valenti, Davide; Adorno, Dominique Persano; Spagnolo, Bernardo

2009-09-01

The evolutionary dynamics of a system of cancerous cells in a model of chronic myeloid leukemia (CML) is investigated by a statistical approach. Cancer progression is explored by applying a Monte Carlo method to simulate the stochastic behavior of cell reproduction and death in a population of blood cells which can experience genetic mutations. In CML front line therapy is represented by the tyrosine kinase inhibitor imatinib which strongly affects the reproduction of leukemic cells only. In this work, we analyze the effects of a targeted therapy on the evolutionary dynamics of normal, first-mutant and cancerous cell populations. Several scenarios of the evolutionary dynamics of imatinib-treated leukemic cells are described as a consequence of the efficacy of the different modelled therapies. We show how the patient response to the therapy changes when a high value of the mutation rate from healthy to cancerous cells is present. Our results are in agreement with clinical observations. Unfortunately, development of resistance to imatinib is observed in a fraction of patients, whose blood cells are characterized by an increasing number of genetic alterations. We find that the occurrence of resistance to the therapy can be related to a progressive increase of deleterious mutations.

Colony Expansion of Socially Motile Myxococcus xanthus Cells Is Driven by Growth, Motility, and Exopolysaccharide Production

PubMed Central

Patra, Pintu; Kissoon, Kimberley; Cornejo, Isabel; Kaplan, Heidi B.; Igoshin, Oleg A.

2016-01-01

Myxococcus xanthus, a model organism for studies of multicellular behavior in bacteria, moves exclusively on solid surfaces using two distinct but coordinated motility mechanisms. One of these, social (S) motility is powered by the extension and retraction of type IV pili and requires the presence of exopolysaccharides (EPS) produced by neighboring cells. As a result, S motility requires close cell-to-cell proximity and isolated cells do not translocate. Previous studies measuring S motility by observing the colony expansion of cells deposited on agar have shown that the expansion rate increases with initial cell density, but the biophysical mechanisms involved remain largely unknown. To understand the dynamics of S motility-driven colony expansion, we developed a reaction-diffusion model describing the effects of cell density, EPS deposition and nutrient exposure on the expansion rate. Our results show that at steady state the population expands as a traveling wave with a speed determined by the interplay of cell motility and growth, a well-known characteristic of Fisher’s equation. The model explains the density-dependence of the colony expansion by demonstrating the presence of a lag phase–a transient period of very slow expansion with a duration dependent on the initial cell density. We propose that at a low initial density, more time is required for the cells to accumulate enough EPS to activate S-motility resulting in a longer lag period. Furthermore, our model makes the novel prediction that following the lag phase the population expands at a constant rate independent of the cell density. These predictions were confirmed by S motility experiments capturing long-term expansion dynamics. PMID:27362260

Colony Expansion of Socially Motile Myxococcus xanthus Cells Is Driven by Growth, Motility, and Exopolysaccharide Production.

PubMed

Patra, Pintu; Kissoon, Kimberley; Cornejo, Isabel; Kaplan, Heidi B; Igoshin, Oleg A

2016-06-01

Myxococcus xanthus, a model organism for studies of multicellular behavior in bacteria, moves exclusively on solid surfaces using two distinct but coordinated motility mechanisms. One of these, social (S) motility is powered by the extension and retraction of type IV pili and requires the presence of exopolysaccharides (EPS) produced by neighboring cells. As a result, S motility requires close cell-to-cell proximity and isolated cells do not translocate. Previous studies measuring S motility by observing the colony expansion of cells deposited on agar have shown that the expansion rate increases with initial cell density, but the biophysical mechanisms involved remain largely unknown. To understand the dynamics of S motility-driven colony expansion, we developed a reaction-diffusion model describing the effects of cell density, EPS deposition and nutrient exposure on the expansion rate. Our results show that at steady state the population expands as a traveling wave with a speed determined by the interplay of cell motility and growth, a well-known characteristic of Fisher's equation. The model explains the density-dependence of the colony expansion by demonstrating the presence of a lag phase-a transient period of very slow expansion with a duration dependent on the initial cell density. We propose that at a low initial density, more time is required for the cells to accumulate enough EPS to activate S-motility resulting in a longer lag period. Furthermore, our model makes the novel prediction that following the lag phase the population expands at a constant rate independent of the cell density. These predictions were confirmed by S motility experiments capturing long-term expansion dynamics.

Population Genetics of Three Dimensional Range Expansions

NASA Astrophysics Data System (ADS)

Lavrentovich, Maxim; Nelson, David

2014-03-01

We develop a simple model of genetic diversity in growing spherical cell clusters, where the growth is confined to the cluster surface. This kind of growth occurs in cells growing in soft agar, and can also serve as a simple model of avascular tumors. Mutation-selection balance in these radial expansions is strongly influenced by scaling near a neutral, voter model critical point and by the inflating frontier. We develop a scaling theory to describe how the dynamics of mutation-selection balance is cut off by inflation. Genetic drift, i.e., local fluctuations in the genetic diversity, also plays an important role, and can lead to the extinction even of selectively advantageous strains. We calculate this extinction probability, taking into account the effect of rough population frontiers.

The stochastic dance of early HIV infection

NASA Astrophysics Data System (ADS)

Merrill, Stephen J.

2005-12-01

The stochastic nature of early HIV infection is described in a series of models, each of which captures aspects of the dance of HIV during the early stages of infection. It is to this highly variable target that the immune response must respond. The adaptability of the various components of the immune response is an important aspect of the system's operation, as the nature of the pathogens that the response will be required to respond to and the order in which those responses must be made cannot be known beforehand. As HIV infection has direct influence over cells responsible for the immune response, the dance predicts that the immune response will be also in a variable state of readiness and capability for this task of adaptation. The description of the stochastic dance of HIV here will use the tools of stochastic models, and for the most part, simulation. The justification for this approach is that the early stages and the development of HIV diversity require that the model to be able to describe both individual sample path and patient-to-patient variability. In addition, as early viral dynamics are best described using branching processes, the explosive growth of these models both predicts high variability and rapid response of HIV to changes in system parameters.In this paper, a basic viral growth model based on a time dependent continuous-time branching process is used to describe the growth of HIV infected cells in the macrophage and lymphocyte populations. Immigration from the reservoir population is added to the basic model to describe the incubation time distribution. This distribution is deduced directly from the modeling assumptions and the model of viral growth. A system of two branching processes, one in the infected macrophage population and one in the infected lymphocyte population is used to provide a description of the relationship between the development of HIV diversity as it relates to tropism (host cell preference). The role of the immune response to HIV and HIV infected cells is used to describe the movement of the infection from a few infected macrophages to a disease of infected CD4+ T lymphocytes.

Generation and expansion of highly pure motor neuron progenitors from human pluripotent stem cells.

PubMed

Du, Zhong-Wei; Chen, Hong; Liu, Huisheng; Lu, Jianfeng; Qian, Kun; Huang, CindyTzu-Ling; Zhong, Xiaofen; Fan, Frank; Zhang, Su-Chun

2015-03-25

Human pluripotent stem cells (hPSCs) have opened new opportunities for understanding human development, modelling disease processes and developing new therapeutics. However, these applications are hindered by the low efficiency and heterogeneity of cell types, such as motorneurons (MNs), differentiated from hPSCs as well as our inability to maintain the potency of lineage-committed progenitors. Here by using a combination of small molecules that regulate multiple signalling pathways, we develop a method to guide human embryonic stem cells to a near-pure population (>95%) of motor neuron progenitors (MNPs) in 12 days, and an enriched population (>90%) of functionally mature MNs in an additional 16 days. More importantly, the MNPs can be expanded for at least five passages so that a single MNP can be amplified to 1 × 10(4). This method is reproducible in human-induced pluripotent stem cells and is applied to model MN-degenerative diseases and in proof-of-principle drug-screening assays.

Computational Fluid Dynamics-Population Balance Model Simulation of Effects of Cell Design and Operating Parameters on Gas-Liquid Two-Phase Flows and Bubble Distribution Characteristics in Aluminum Electrolysis Cells

NASA Astrophysics Data System (ADS)

Zhan, Shuiqing; Wang, Junfeng; Wang, Zhentao; Yang, Jianhong

2018-02-01

The effects of different cell design and operating parameters on the gas-liquid two-phase flows and bubble distribution characteristics under the anode bottom regions in aluminum electrolysis cells were analyzed using a three-dimensional computational fluid dynamics-population balance model. These parameters include inter-anode channel width, anode-cathode distance (ACD), anode width and length, current density, and electrolyte depth. The simulations results show that the inter-anode channel width has no significant effect on the gas volume fraction, electrolyte velocity, and bubble size. With increasing ACD, the above values decrease and more uniform bubbles can be obtained. Different effects of the anode width and length can be concluded in different cell regions. With increasing current density, the gas volume fraction and electrolyte velocity increase, but the bubble size keeps nearly the same. Increasing electrolyte depth decreased the gas volume fraction and bubble size in particular areas and the electrolyte velocity increased.

Cellular replication limits in the Luria-Delbrück mutation model

NASA Astrophysics Data System (ADS)

Rodriguez-Brenes, Ignacio A.; Wodarz, Dominik; Komarova, Natalia L.

2016-08-01

Originally developed to elucidate the mechanisms of natural selection in bacteria, the Luria-Delbrück model assumed that cells are intrinsically capable of dividing an unlimited number of times. This assumption however, is not true for human somatic cells which undergo replicative senescence. Replicative senescence is thought to act as a mechanism to protect against cancer and the escape from it is a rate-limiting step in cancer progression. Here we introduce a Luria-Delbrück model that explicitly takes into account cellular replication limits in the wild type cell population and models the emergence of mutants that escape replicative senescence. We present results on the mean, variance, distribution, and asymptotic behavior of the mutant population in terms of three classical formulations of the problem. More broadly the paper introduces the concept of incorporating replicative limits as part of the Luria-Delbrück mutational framework. Guidelines to extend the theory to include other types of mutations and possible applications to the modeling of telomere crisis and fluctuation analysis are also discussed.

Multiscale Modeling of Microbial Communities

NASA Astrophysics Data System (ADS)

Blanchard, Andrew

Although bacteria are single-celled organisms, they exist in nature primarily in the form of complex communities, participating in a vast array of social interactions through regulatory gene networks. The social interactions between individual cells drive the emergence of community structures, resulting in an intricate relationship across multiple spatiotemporal scales. Here, I present my work towards developing and applying the tools necessary to model the complex dynamics of bacterial communities. In Chapter 2, I utilize a reaction-diffusion model to determine the population dynamics for a population with two species. One species (CDI+) utilizes contact dependent inhibition to kill the other sensitive species (CDI-). The competition can produce diverse patterns, including extinction, coexistence, and localized aggregation. The emergence, relative abundance, and characteristic features of these patterns are collectively determined by the competitive benefit of CDI and its growth disadvantage for a given rate of population diffusion. The results provide a systematic and statistical view of CDI-based bacterial population competition, expanding the spectrum of our knowledge about CDI systems and possibly facilitating new experimental tests for a deeper understanding of bacterial interactions. In the following chapter, I present a systematic computational survey on the relationship between social interaction types and population structures for two-species communities by developing and utilizing a hybrid computational framework that combines discrete element techniques with reaction-diffusion equations. The impact of deleterious and beneficial interactions on the community are quantified. Deleterious interactions generate an increased variance in relative abundance, a drastic decrease in surviving lineages, and a rough expanding front. In contrast, beneficial interactions contribute to a reduced variance in relative abundance, an enhancement in lineage number, and a smooth expanding front. More specifically, mutualism promotes spatial homogeneity and population robustness while competition increases spatial segregation and population fluctuations. To examine the generality of these findings, a large set of initial conditions with varying density and species abundance was tested and analyzed. The results and the computational framework presented provide the basis for further explorations of individual based simulations of bacterial communities. For Chapter 4, I consider the role of gene regulation in shaping the outcome of competition between a bacteriocin (i.e. toxin) producing and sensitive strain. In natural systems, bacteriocin production is often conditional, governed by underlying quorum sensing regulatory circuitry. By developing an ordinary differential equation (ODE) model integrating population dynamics with molecular regulation, we find that the ecological contribution of bacteriocin production can be positive or negative, determined by the tradeoff between the benefit of bacteriocins in mediating competition and the fitness cost due to metabolic load. Interestingly, under the naturally occurring scenario where bacteriocin production has a high cost, density-dependent synthesis is more advantageous than constitutive synthesis, which offers a quantitative interpretation for the wide prevalence of density-related bacteriocin production in nature. By incorporating the modeling framework presented in Chapter 3, the results of the ODE model were extended to the spatial setting, providing ecological insights into the costs and benefits of bacteriocin synthesis in competitive environments. For the final research chapter, I consider the impact of growth coupling on protein production at both the single cell and population scales. The same machinery (e.g. ribosomes) and resources (e.g. amino acids and ATP) are used within cells to produce both endogenous (host) and exogenous (circuit) proteins. Thus, the introduction of a gene circuit generates a metabolic burden on the cell which can slow its growth rate relative to the wild type. Building off of the computational framework introduced in Chapter 3 with single cell resolution, I utilize deterministic and stochastic simulations to characterize the changes in protein production due to host-circuit coupling for a simple gene regulatory architecture. Analytical arguments and simulation results show that incorporating growth can lead to drastic changes in both the steady state and time scales for protein production at the single cell and population level. Furthermore, host-circuit coupling can induce bimodality at the population level well outside the bistable region for single cell dynamics.

Reconstructing human pancreatic differentiation by mapping specific cell populations during development

PubMed Central

Ramond, Cyrille; Glaser, Nicolas; Berthault, Claire; Ameri, Jacqueline; Kirkegaard, Jeannette Schlichting; Hansson, Mattias; Honoré, Christian; Semb, Henrik; Scharfmann, Raphaël

2017-01-01

Information remains scarce on human development compared to animal models. Here, we reconstructed human fetal pancreatic differentiation using cell surface markers. We demonstrate that at 7weeks of development, the glycoprotein 2 (GP2) marks a multipotent cell population that will differentiate into the acinar, ductal or endocrine lineages. Development towards the acinar lineage is paralleled by an increase in GP2 expression. Conversely, a subset of the GP2+ population undergoes endocrine differentiation by down-regulating GP2 and CD142 and turning on NEUROG3, a marker of endocrine differentiation. Endocrine maturation progresses by up-regulating SUSD2 and lowering ECAD levels. Finally, in vitro differentiation of pancreatic endocrine cells derived from human pluripotent stem cells mimics key in vivo events. Our work paves the way to extend our understanding of the origin of mature human pancreatic cell types and how such lineage decisions are regulated. DOI: http://dx.doi.org/10.7554/eLife.27564.001 PMID:28731406

The Emergence of Blood and Blood Vessels in the Embryo and Its Relevance to Postnatal Biology and Disease

NASA Astrophysics Data System (ADS)

Sills, Tiffany M.; Hirschi, Karen K.

Blood and blood vessels develop in parallel within mammalian systems, and this temporal and spatial association has led to the confirmation of an endothelial origin of hematopoiesis. The extraembryonic yolk sac and aorto-gonado-mesonephros (AGM) region both contain a specialized population of endothelial cells ("hemogenic endothelium") that function to produce hematopoietic stem and progenitor cells, which then differentiate to provide the full complement of blood cells within the developing embryo and furthermore in the adult system. Therefore, this population has great therapeutic potential in the fields of regenerative medicine and tissue engineering. This chapter reviews the development of the vascular and hematopoietic systems, characterization and function of the hemogenic endothelium within embryonic and embryonic stem cell (ES cell) models, and speculate on the presence of such a population within the adult system. In order to harness this endothelial subtype for clinical application, we must understand both the normal functions of these cells and the potential for misregulation in disease states.

Self-Organizing and Stochastic Behaviors During the Regeneration of Hair Stem Cells

PubMed Central

Plikus, Maksim V.; Baker, Ruth E.; Chen, Chih-Chiang; Fare, Clyde; de la Cruz, Damon; Andl, Thomas; Maini, Philip K.; Millar, Sarah E.; Widelitz, Randall; Chuong, Cheng-Ming

2012-01-01

Stem cells cycle through active and quiescent states. Large populations of stem cells in an organ may cycle randomly or in a coordinated manner. Although stem cell cycling within single hair follicles has been studied, less is known about regenerative behavior in a hair follicle population. By combining predictive mathematical modeling with in vivo studies in mice and rabbits, we show that a follicle progresses through cycling stages by continuous integration of inputs from intrinsic follicular and extrinsic environmental signals based on universal patterning principles. Signaling from the WNT/bone morphogenetic protein activator/inhibitor pair is coopted to mediate interactions among follicles in the population. This regenerative strategy is robust and versatile because relative activator/inhibitor strengths can be modulated easily, adapting the organism to different physiological and evolutionary needs. PMID:21527712

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vassilevska, Tanya

This is the first code, designed to run on a desktop, which models the intracellular replication and the cell-to-cell infection and demonstrates virus evolution at the molecular level. This code simulates the infection of a population of "idealized biological cells" (represented as objects that do not divide or have metabolism) with "virus" (represented by its genetic sequence), the replication and simultaneous mutation of the virus which leads to evolution of the population of genetically diverse viruses. The code is built to simulate single-stranded RNA viruses. The input for the code is 1. the number of biological cells in the culture,more » 2. the initial composition of the virus population, 3. the reference genome of the RNA virus, 4. the coordinates of the genome regions and their significance and, 5. parameters determining the dynamics of virus replication, such as the mutation rate. The simulation ends when all cells have been infected or when no more infections occurs after a given number of attempts. The code has the ability to simulate the evolution of the virus in serial passage of cell "cultures", i.e. after the end of a simulation, a new one is immediately scheduled with a new culture of infected cells. The code outputs characteristics of the resulting virus population dynamics and genetic composition of the virus population, such as the top dominant genomes, percentage of a genome with specific characteristics.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Šefl, Martin, E-mail: martin.sefl@gmail.com; Kyriakou, Ioanna; Emfietzoglou, Dimitris, E-mail: demfietz@cc.uoi.gr

Purpose: To study theoretically the impact on cell survival of the radionuclide uptake rate inside tumor cells for a single administration of a radiopharmaceutical. Methods: The instantaneous-uptake model of O’Donoghue [“The impact of tumor cell proliferation in radioimmunotherapy,” Cancer 73, 974–980 (1994)] for a proliferating cell population irradiated by an exponentially decreasing dose-rate is here extended to allow for the monoexponential uptake of the radiopharmaceutical by the targeted cells. The time derivative of the survival curve is studied in detail deducing an expression for the minimum of the surviving fraction and the biologically effective dose (BED). Results: Surviving fractions aremore » calculated over a parameter range that is clinically relevant and broad enough to establish general trends. Specifically, results are presented for the therapy radionuclides Y-90, I-131, and P-32, assuming uptake half-times 1–24 h, extrapolated initial dose-rates 0.5–1 Gy h{sup −1}, and a biological clearance half-life of seven days. Representative radiobiological parameters for radiosensitive and rapidly proliferating tumor cells are used, with cell doubling time equal to 2 days and α-coefficient equal to 0.3 and 0.5 Gy{sup −1}. It is shown that neglecting the uptake phase of the radiopharmaceutical (i.e., assuming instantaneous-uptake) results in a sizeable over-estimation of cell-kill (i.e., under-estimation of cell survival) even for uptake half-times of only a few hours. The differences between the exponential-uptake model and the instantaneous-uptake model become larger for high peak dose-rates, slow uptakes, and (slightly) for long-lived radionuclides. Moreover, the sensitivity of the survival curve on the uptake model was found to be higher for the tumor cells with the larger α-coefficient. Conclusions: The exponential-uptake rate of the radiopharmaceutical inside targeted cells appears to have a considerable effect on the survival of a proliferating cell population and might need to be considered in radiobiological models of tumor cell-kill in radionuclide therapy.« less

Critical high-dimensional state transitions in cell populations or why cancers follow the principle ``What does not kill me makes me stronger''

NASA Astrophysics Data System (ADS)

Huang, Sui

Transitions between high-dimensional attractor states in the quasi-potential landscape of the gene regulatory network, induced by environmental perturbations and/or facilitated by mutational rewiring of the network, underlie cell phenotype switching in development as well as in cancer progression, including acquisition of drug-resistant phenotypes. Considering heterogeneous cell populations as statistical ensembles of cells, and single-cell resolution gene expression profiling of cell populations undergoing a cell phenotype shift allow us now to map the topography of the landscape and its distortion. From snapshots of single-cell expression patterns of a cell population measured during major transitions we compute a quantity that identifies symmetry-breaking destabilization of attractors (bifurcation) and concomitant dimension-reduction of the state space manifold (landscape distortion) which precede critical transitions to new attractor states. The model predicts, and we show experimentally, the almost inevitable generation of aberrant cells associated with such critical transitions in multi-attractor landscapes: therapeutic perturbations which seek to push cancer cells to the apoptotic state, almost always produce ``rebellious'' cells which move in the ``opposite direction'': instead of dying they become more stem-cell-like and malignant. We show experimentally that the inadvertent generation of more malignant cancer cells by therapy indeed results from transition of surviving (but stressed) cells into unforeseen attractor states and not simply from selection of inherently more resistant cells. Thus, cancer cells follow not so much Darwin, as generally thought (survival of the fittest), but rather Nietzsche (What does not kill me makes me stronger). Supported by NIH (NCI, NIGMS), Alberta Innovates.

A Simulation To Model Exponential Growth.

ERIC Educational Resources Information Center

Appelbaum, Elizabeth Berman

2000-01-01

Describes a simulation using dice-tossing students in a population cluster to model the growth of cancer cells. This growth is recorded in a scatterplot and compared to an exponential function graph. (KHR)

Computing local edge probability in natural scenes from a population of oriented simple cells

PubMed Central

Ramachandra, Chaithanya A.; Mel, Bartlett W.

2013-01-01

A key computation in visual cortex is the extraction of object contours, where the first stage of processing is commonly attributed to V1 simple cells. The standard model of a simple cell—an oriented linear filter followed by a divisive normalization—fits a wide variety of physiological data, but is a poor performing local edge detector when applied to natural images. The brain's ability to finely discriminate edges from nonedges therefore likely depends on information encoded by local simple cell populations. To gain insight into the corresponding decoding problem, we used Bayes's rule to calculate edge probability at a given location/orientation in an image based on a surrounding filter population. Beginning with a set of ∼ 100 filters, we culled out a subset that were maximally informative about edges, and minimally correlated to allow factorization of the joint on- and off-edge likelihood functions. Key features of our approach include a new, efficient method for ground-truth edge labeling, an emphasis on achieving filter independence, including a focus on filters in the region orthogonal rather than tangential to an edge, and the use of a customized parametric model to represent the individual filter likelihood functions. The resulting population-based edge detector has zero parameters, calculates edge probability based on a sum of surrounding filter influences, is much more sharply tuned than the underlying linear filters, and effectively captures fine-scale edge structure in natural scenes. Our findings predict nonmonotonic interactions between cells in visual cortex, wherein a cell may for certain stimuli excite and for other stimuli inhibit the same neighboring cell, depending on the two cells' relative offsets in position and orientation, and their relative activation levels. PMID:24381295

A Novel Porcine Model for Future Studies of Cell-enriched Fat Grafting

PubMed Central

Sørensen, Celine L.; Vester-Glowinski, Peter V.; Herly, Mikkel; Kurbegovic, Sorel; Ørholt, Mathias; Svalgaard, Jesper D.; Kølle, Stig-Frederik T.; Kristensen, Annemarie T.; Talman, Maj-Lis M.; Drzewiecki, Krzysztof T.; Fischer-Nielsen, Anne

2018-01-01

Background: Cell-enriched fat grafting has shown promising results for improving graft survival, although many questions remain unanswered. A large animal model is crucial for bridging the gap between rodent studies and human trials. We present a step-by-step approach in using the Göttingen minipig as a model for future studies of cell-enriched large volume fat grafting. Methods: Fat grafting was performed as bolus injections and structural fat grafting. Graft retention was assessed by magnetic resonance imaging after 120 days. The stromal vascular fraction (SVF) was isolated from excised fat and liposuctioned fat from different anatomical sites and analyzed. Porcine adipose-derived stem/stromal cells (ASCs) were cultured in different growth supplements, and population doubling time, maximum cell yield, expression of surface markers, and differentiation potential were investigated. Results: Structural fat grafting in the breast and subcutaneous bolus grafting in the abdomen revealed average graft retention of 53.55% and 15.28%, respectively, which are similar to human reports. Liposuction yielded fewer SVF cells than fat excision, and abdominal fat had the most SVF cells/g fat with SVF yields similar to humans. Additionally, we demonstrated that porcine ASCs can be readily isolated and expanded in culture in allogeneic porcine platelet lysate and fetal bovine serum and that the use of 10% porcine platelet lysate or 20% fetal bovine serum resulted in population doubling time, maximum cell yield, surface marker profile, and trilineage differentiation that were comparable with humans. Conclusions: The Göttingen minipig is a feasible and cost-effective, large animal model for future translational studies of cell-enriched fat grafting. PMID:29876178

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua E.; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

2016-09-01

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of "stiff" equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of ``stiff'' equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Modeled microgravity inhibits apoptosis in peripheral blood lymphocytes

NASA Technical Reports Server (NTRS)

Risin, D.; Pellis, N. R.; McIntire, L. V. (Principal Investigator)

2001-01-01

Microgravity interferes with numerous lymphocyte functions (expression of cell surface molecules, locomotion, polyclonal and antigen-specific activation, and the protein kinase C activity in signal transduction). The latter suggests that gravity may also affect programmed cell death (PCD) in lymphocyte populations. To test this hypothesis, we investigated spontaneous, activation- and radiation-induced PCD in peripheral blood mononuclear cells exposed to modeled microgravity (MMG) using a rotating cell culture system. The results showed significant inhibition of radiation- and activation-induced apoptosis in MMG and provide insights into the potential mechanisms of this phenomenon.

Aurora B kinase inhibition in mitosis: strategies for optimising the use of aurora kinase inhibitors such as AT9283.

PubMed

Curry, Jayne; Angove, Hayley; Fazal, Lynsey; Lyons, John; Reule, Matthias; Thompson, Neil; Wallis, Nicola

2009-06-15

Aurora kinases play a key role in regulating mitotic division and are attractive oncology targets. AT9283, a multi-targeted kinase inhibitor with potent activity against Aurora A and B kinases, inhibited growth and survival of multiple solid tumor cell lines and was efficacious in mouse xenograft models. AT9283-treatment resulted in endoreduplication and ablation of serine-10 histone H3 phosphorylation in both cells and tumor samples, confirming that in these models it acts as an Aurora B kinase inhibitor. In vitro studies demonstrated that exposure to AT9283 for one complete cell cycle committed an entire population of p53 checkpoint-compromised cells (HCT116) to multinucleation and death whereas treatment of p53 checkpoint-competent cells (HMEC, A549) for a similar length of time led to a reversible arrest of cells with 4N DNA. Further studies in synchronized cell populations suggested that exposure to AT9283 during mitosis was critical for optimal cytotoxicity. We therefore investigated ways in which these properties might be exploited to optimize the efficacy and therapeutic index of Aurora kinase inhibitors for p53 checkpoint compromised tumors in vivo. Combining Aurora B kinase inhibition with paclitaxel, which arrests cells in mitosis, in a xenograft model resulted in promising efficacy without additional toxicity. These findings have implications for optimizing the efficacy of Aurora kinase inhibitors in clinical practice.

Cell rejuvenation and social behaviors promoted by LPS exchange in myxobacteria.

PubMed

Vassallo, Christopher; Pathak, Darshankumar T; Cao, Pengbo; Zuckerman, David M; Hoiczyk, Egbert; Wall, Daniel

2015-06-02

Bacterial cells in their native environments must cope with factors that compromise the integrity of the cell. The mechanisms of coping with damage in a social or multicellular context are poorly understood. Here we investigated how a model social bacterium, Myxococcus xanthus, approaches this problem. We focused on the social behavior of outer membrane exchange (OME), in which cells transiently fuse and exchange their outer membrane (OM) contents. This behavior requires TraA, a homophilic cell surface receptor that identifies kin based on similarities in a polymorphic region, and the TraB cohort protein. As observed by electron microscopy, TraAB overexpression catalyzed a prefusion OM junction between cells. We then showed that damage sustained by the OM of one population was repaired by OME with a healthy population. Specifically, LPS mutants that were defective in motility and sporulation were rescued by OME with healthy donors. In addition, a mutant with a conditional lethal mutation in lpxC, an essential gene required for lipid A biosynthesis, was rescued by Tra-dependent interactions with a healthy population. Furthermore, lpxC cells with damaged OMs, which were more susceptible to antibiotics, had resistance conferred to them by OME with healthy donors. We also show that OME has beneficial fitness consequences to all cells. Here, in merged populations of damaged and healthy cells, OME catalyzed a dilution of OM damage, increasing developmental sporulation outcomes of the combined population by allowing it to reach a threshold density. We propose that OME is a mechanism that myxobacteria use to overcome cell damage and to transition to a multicellular organism.

Cancer immunotherapy and immunological memory.

PubMed

Murata, Kenji; Tsukahara, Tomohide; Torigoe, Toshihiko

2016-01-01

Human immunological memory is the key distinguishing hallmark of the adaptive immune system and plays an important role in the prevention of morbidity and the severity of infection. The differentiation system of T cell memory has been clarified using mouse models. However, the human T cell memory system has great diversity induced by natural antigens derived from many pathogens and tumor cells throughout life, and profoundly differs from the mouse memory system constructed using artificial antigens and transgenic T cells. We believe that only human studies can elucidate the human immune system. The importance of immunological memory in cancer immunotherapy has been pointed out, and the trafficking properties and long-lasting anti-tumor capacity of memory T cells play a crucial role in the control of malignant tumors. Adoptive cell transfer of less differentiated T cells has consistently demonstrated superior anti-tumor capacity relative to more differentiated T cells. Therefore, a human T cell population with the characteristics of stem cell memory is thought to be attractive for peptide vaccination and adoptive cell transfer. A novel human memory T cell population that we have identified is closer to the naive state than previous memory T cells in the T cell differentiation lineage, and has the characteristics of stem-like chemoresistance. Here we introduce this novel population and describe the fundamentals of immunological memory in cancer immunotherapy.

Quantifying cell turnover using CFSE data.

PubMed

Ganusov, Vitaly V; Pilyugin, Sergei S; de Boer, Rob J; Murali-Krishna, Kaja; Ahmed, Rafi; Antia, Rustom

2005-03-01

The CFSE dye dilution assay is widely used to determine the number of divisions a given CFSE labelled cell has undergone in vitro and in vivo. In this paper, we consider how the data obtained with the use of CFSE (CFSE data) can be used to estimate the parameters determining cell division and death. For a homogeneous cell population (i.e., a population with the parameters for cell division and death being independent of time and the number of divisions cells have undergone), we consider a specific biologically based "Smith-Martin" model of cell turnover and analyze three different techniques for estimation of its parameters: direct fitting, indirect fitting and rescaling method. We find that using only CFSE data, the duration of the division phase (i.e., approximately the S+G2+M phase of the cell cycle) can be estimated with the use of either technique. In some cases, the average division or cell cycle time can be estimated using the direct fitting of the model solution to the data or by using the Gett-Hodgkin method [Gett A. and Hodgkin, P. 2000. A cellular calculus for signal integration by T cells. Nat. Immunol. 1:239-244]. Estimation of the death rates during commitment to division (i.e., approximately the G1 phase of the cell cycle) and during the division phase may not be feasible with the use of only CFSE data. We propose that measuring an additional parameter, the fraction of cells in division, may allow estimation of all model parameters including the death rates during different stages of the cell cycle.

Th1-like Plasmodium-Specific Memory CD4+ T Cells Support Humoral Immunity.

PubMed

Zander, Ryan A; Vijay, Rahul; Pack, Angela D; Guthmiller, Jenna J; Graham, Amy C; Lindner, Scott E; Vaughan, Ashley M; Kappe, Stefan H I; Butler, Noah S

2017-11-14

Effector T cells exhibiting features of either T helper 1 (Th1) or T follicular helper (Tfh) populations are essential to control experimental Plasmodium infection and are believed to be critical for resistance to clinical malaria. To determine whether Plasmodium-specific Th1- and Tfh-like effector cells generate memory populations that contribute to protection, we developed transgenic parasites that enable high-resolution study of anti-malarial memory CD4 T cells in experimental models. We found that populations of both Th1- and Tfh-like Plasmodium-specific memory CD4 T cells persist. Unexpectedly, Th1-like memory cells exhibit phenotypic and functional features of Tfh cells during recall and provide potent B cell help and protection following transfer, characteristics that are enhanced following ligation of the T cell co-stimulatory receptor OX40. Our findings delineate critical functional attributes of Plasmodium-specific memory CD4 T cells and identify a host-specific factor that can be targeted to improve resolution of acute malaria and provide durable, long-term protection against Plasmodium parasite re-exposure. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

A stem cell apostasy: A tale of 4 H words

PubMed Central

Quesenberry, Peter J.; Goldberg, Laura R.; Dooner, Mark S.

2014-01-01

The field of hematopoietic stem cell biology has become increasingly dominated by the pursuit and study of highly purified populations of hematopoietic stem cells (HSCs). Such HSCs are typically isolated based on their cell surface marker expression patterns and ultimately defined by their multipotency and capacity for self-generation. However, even with progressively more stringent stem cell separation techniques, the resultant HSC population remains heterogeneous with respect to both self-renewal and differentiation capacity. Critical studies on un-separated whole bone marrow (WBM) have definitively shown that long-term engraftable hematopoietic stem cells are in active cell cycle and thus continually changing phenotype. Therefore, they cannot be purified by current approaches dependent on stable surface epitope expression because the surface markers are continually changing as well. These critical cycling cells are discarded with current stem cell purifications. Despite this, research defining such characteristics as self-renewal capacity, lineage-commitment, bone marrow niches, and proliferative state of HSCs continues to focus predominantly on this small sub-population of purified marrow cells. This review discusses the research leading to the hierarchical model of hematopoiesis and questions the dogmas pertaining to HSC quiescence and purification. PMID:25183450

Vagal nerve stimulation modulates the dendritic cell profile in posthemorrhagic shock mesenteric lymph.

PubMed

Morishita, Koji; Costantini, Todd W; Eliceiri, Brian; Bansal, Vishal; Coimbra, Raul

2014-03-01

Previous studies have established that posthemorrhagic shock mesenteric lymph (PHSML) contains proinflammatory mediators, while the cellular basis of PHSML is less well characterized in acute models of injury. CD103 dendritic cells (DCs) have been identified in the mesenteric lymph (ML) in models of chronic intestinal inflammation, suggesting an important role in the gut response to injury. We have previously demonstrated the ability of vagal nerve stimulation (VNS) to prevent gut barrier failure after trauma/hemorrhagic shock (T/HS); however, the ability of VNS to alter ML DCs is unknown. We hypothesized that the CD103 MHC-II DC population would change in PHSML and that VNS would prevent injury-induced changes in this population in PHSML. Male Sprague-Dawley rats were randomly assigned to trauma/sham shock or T/HS. T/HS was induced by midline laparotomy and 60 minutes of HS (blood pressure, 35 mm Hg), followed by fluid resuscitation. A separate cohort of animals underwent cervical VNS after the HS phase. Gut tissue was harvested at 2 hours after injury for histologic analysis. ML was collected during the pre-HS, HS, and post-HS phase. For flow cytometric analysis, ML cells were subjected to staining with CD103 and MHC-II antibodies, and this cell population was compared in the pre-HS and post-HS phase from the same animal. The CD4Foxp3 cell (T reg) population in the ML node (MLN) was also tested to determine effects of CD103 DC modulation in the ML. VNS reduced histologic gut injury and ML flow seen after injury. The CD103 MHC-II DC population in the PHSML was significantly decreased compared with pre-HS and was associated with decreased T reg expression in the MLN. VNS prevented the injury-induced decrease in the CD103 MHC-II+ DC population in the ML and restored the T reg population in the MLN. These findings suggest that VNS mediates the inflammatory responses in ML DCs and MLN T reg cells by affecting the set point of T/HS responsiveness.

Dormancy in a model of murine B cell lymphoma.

PubMed

Uhr, J W; Marches, R

2001-08-01

A B cell lymphoma model of dormancy in mice was established by prior immunization to the B cell membrane immunoglobulin idiotype. The antibody to the idiotype was the major factor in inducing and maintaining dormancy and acted primarily as an agonist rather than via effector functions. CD8+ T cells synergized with anti-Id in inducing dormancy by secreting IFN-gamma. Cycling in the dormant population was reduced 3-5 fold, but each mouse contained approximately 10(6) tumor cells in its spleen, some of which were cycling, during the 1.5 years of observation. Thus, replication is balanced by cell death. Copyright 2001 Academic Press.

Heart grafts tolerized through third-party multipotent adult progenitor cells can be retransplanted to secondary hosts with no immunosuppression.

PubMed

Eggenhofer, Elke; Popp, Felix C; Mendicino, Michael; Silber, Paula; Van't Hof, Wouter; Renner, Philipp; Hoogduijn, Martin J; Pinxteren, Jef; van Rooijen, Nico; Geissler, Edward K; Deans, Robert; Schlitt, Hans J; Dahlke, Marc H

2013-08-01

Multipotent adult progenitor cells (MAPCs) are an adherent stem cell population that belongs to the mesenchymal-type progenitor cell family. Although MAPCs are emerging as candidate agents for immunomodulation after solid organ transplantation, their value requires further validation in a clinically relevant cell therapy model using an organ donor- and organ recipient-independent, third-party cell product. We report that stable allograft survival can be achieved following third-party MAPC infusion in a rat model of fully allogeneic, heterotopic heart transplantation. Furthermore, long-term accepted heart grafts recovered from MAPC-treated animals can be successfully retransplanted to naïve animals without additional immunosuppression. This prolongation of MAPC-mediated allograft acceptance depends upon a myeloid cell population since depletion of macrophages by clodronate abrogates the tolerogenic MAPC effect. We also show that MAPC-mediated allograft acceptance differs mechanistically from drug-induced tolerance regarding marker gene expression, T regulatory cell induction, retransplantability, and macrophage dependence. MAPC-based immunomodulation represents a promising pathway for clinical immunotherapy that has led us to initiate a phase I clinical trial for testing safety and feasibility of third-party MAPC therapy after liver transplantation.

Stem cells in pharmaceutical biotechnology.

PubMed

Zuba-Surma, Ewa K; Józkowicz, Alicja; Dulak, Józef

2011-11-01

Multiple populations of stem cells have been indicated to potentially participate in regeneration of injured organs. Especially, embryonic stem cells (ESC) and recently inducible pluripotent stem cells (iPS) receive a marked attention from scientists and clinicians for regenerative medicine because of their high proliferative and differentiation capacities. Despite that ESC and iPS cells are expected to give rise into multiple regenerative applications when their side effects are overcame during appropriate preparation procedures, in fact their most recent application of human ESC may, however, reside in their use as a tool in drug development and disease modeling. This review focuses on the applications of stem cells in pharmaceutical biotechnology. We discuss possible relevance of pluripotent cell stem populations in developing physiological models for any human tissue cell type useful for pharmacological, metabolic and toxicity evaluation necessary in the earliest steps of drug development. The present models applied for preclinical drug testing consist of primary cells or immortalized cell lines that show limitations in terms of accessibility or relevance to their in vivo counterparts. The availability of renewable human cells with functional similarities to their in vivo counterparts is the first landmark for a new generation of cell-based assays. We discuss the approaches for using stem cells as valuable physiological targets of drug activity which may increase the strength of target validation and efficacy potentially resulting in introducing new safer remedies into clinical trials and the marketplace. Moreover, we discuss the possible applications of stem cells for elucidating mechanisms of disease pathogenesis. The knowledge about the mechanisms governing the development and progression of multitude disorders which would come from the cellular models established based on stem cells, may give rise to new therapeutical strategies for such diseases. All together, the applications of various cell types derived from patient specific pluripotent stem cells may lead to targeted drug and cellular therapies for certain individuals.

Interactions between Inhibitory Interneurons and Excitatory Associational Circuitry in Determining Spatio-Temporal Dynamics of Hippocampal Dentate Granule Cells: A Large-Scale Computational Study

PubMed Central

Hendrickson, Phillip J.; Yu, Gene J.; Song, Dong; Berger, Theodore W.

2015-01-01

This paper reports on findings from a million-cell granule cell model of the rat dentate gyrus that was used to explore the contributions of local interneuronal and associational circuits to network-level activity. The model contains experimentally derived morphological parameters for granule cells, which each contain approximately 200 compartments, and biophysical parameters for granule cells, basket cells, and mossy cells that were based both on electrophysiological data and previously published models. Synaptic input to cells in the model consisted of glutamatergic AMPA-like EPSPs and GABAergic-like IPSPs from excitatory and inhibitory neurons, respectively. The main source of input to the model was from layer II entorhinal cortical neurons. Network connectivity was constrained by the topography of the system, and was derived from axonal transport studies, which provided details about the spatial spread of axonal terminal fields, as well as how subregions of the medial and lateral entorhinal cortices project to subregions of the dentate gyrus. Results of this study show that strong feedback inhibition from the basket cell population can cause high-frequency rhythmicity in granule cells, while the strength of feedforward inhibition serves to scale the total amount of granule cell activity. Results furthermore show that the topography of local interneuronal circuits can have just as strong an impact on the development of spatio-temporal clusters in the granule cell population as the perforant path topography does, both sharpening existing clusters and introducing new ones with a greater spatial extent. Finally, results show that the interactions between the inhibitory and associational loops can cause high frequency oscillations that are modulated by a low-frequency oscillatory signal. These results serve to further illustrate the importance of topographical constraints on a global signal processing feature of a neural network, while also illustrating how rich spatio-temporal and oscillatory dynamics can evolve from a relatively small number of interacting local circuits. PMID:26635545

Therapeutic manipulation of natural killer (NK) T cells in autoimmunity: are we close to reality?

PubMed Central

Simoni, Y; Diana, J; Ghazarian, L; Beaudoin, L; Lehuen, A

2013-01-01

T cells reactive to lipids and restricted by major histocompatibility complex (MHC) class I-like molecules represent more than 15% of all lymphocytes in human blood. This heterogeneous population of innate cells includes the invariant natural killer T cells (iNK T), type II NK T cells, CD1a,b,c-restricted T cells and mucosal-associated invariant T (MAIT) cells. These populations are implicated in cancer, infection and autoimmunity. In this review, we focus on the role of these cells in autoimmunity. We summarize data obtained in humans and preclinical models of autoimmune diseases such as primary biliary cirrhosis, type 1 diabetes, multiple sclerosis, systemic lupus erythematosus, rheumatoid arthritis, psoriasis and atherosclerosis. We also discuss the promise of NK T cell manipulations: restoration of function, specific activation, depletion and the relevance of these treatments to human autoimmune diseases. PMID:23199318

Identification of a unique hepatocellular carcinoma line, Li-7, with CD13(+) cancer stem cells hierarchy and population change upon its differentiation during culture and effects of sorafenib.

PubMed

Yamada, Takeshi; Abei, Masato; Danjoh, Inaho; Shirota, Ryoko; Yamashita, Taro; Hyodo, Ichinosuke; Nakamura, Yukio

2015-04-11

Cancer stem cell (CSC) research has highlighted the necessity of developing drugs targeting CSCs. We investigated a hepatocellular carcinoma (HCC) cell line that not only has CSC hierarchy but also shows phenotypic changes (population changes) upon differentiation of CSC during culture and can be used for screening drugs targeting CSC. Based on a hypothesis that the CSC proportion should decrease upon its differentiation into progenitors (population change), we tested HCC cell lines (HuH-7, Li-7, PLC/PRF/5, HLF, HLE) before and after 2 months culture for several markers (CD13, EpCAM, CD133, CD44, CD90, CD24, CD166). Tumorigenicity was tested using nude mice. To evaluate the CSC hierarchy, we investigated reconstructivity, proliferation, ALDH activity, spheroid formation, chemosensitivity and microarray analysis of the cell populations sorted by FACS. Only Li-7 cells showed a population change during culture: the proportion of CD13 positive cells decreased, while that of CD166 positive cells increased. The high tumorigenicity of the Li-7 was lost after the population change. CD13(+)/CD166(-) cells showed slow growth and reconstructed the bulk Li-7 populations composed of CD13(+)/CD166(-), CD13(-)/CD166(-) and CD13(-)/CD166(+) fractions, whereas CD13(-)/CD166(+) cells showed rapid growth but could not reproduce any other population. CD13(+)/CD166(-) cells showed high ALDH activity, spheroid forming ability and resistance to 5-fluorouracil. Microarray analysis demonstrated higher expression of stemness-related genes in CD166(-) than CD166(+) fraction. These results indicated a hierarchy in Li-7 cells, in which CD13(+)/CD166(-) and CD13(-)/CD166(+) cells serve as slow growing CSCs and rapid growing progenitors, respectively. Sorafenib selectively targeted the CD166(-) fraction, including CD13(+) CSCs, which exhibited higher mRNA expression for FGF3 and FGF4, candidate biomarkers for sorafenib. 5-fluorouracil followed by sorafenib inhibited the growth of bulk Li-7 cells more effectively than the reverse sequence or either alone. We identified a unique HCC line, Li-7, which not only shows heterogeneity for a CD13(+) CSC hierarchy, but also undergoes a "population change" upon CSC differentiation. Sorafenib targeted the CSC in vitro, supporting the use of this model for screening drugs targeting the CSC. This type of "heterogeneous, unstable" cell line may prove more useful in the CSC era than conventional "homogeneous, stable" cell lines.

Automated deconvolution of structured mixtures from heterogeneous tumor genomic data

PubMed Central

Roman, Theodore; Xie, Lu

2017-01-01

With increasing appreciation for the extent and importance of intratumor heterogeneity, much attention in cancer research has focused on profiling heterogeneity on a single patient level. Although true single-cell genomic technologies are rapidly improving, they remain too noisy and costly at present for population-level studies. Bulk sequencing remains the standard for population-scale tumor genomics, creating a need for computational tools to separate contributions of multiple tumor clones and assorted stromal and infiltrating cell populations to pooled genomic data. All such methods are limited to coarse approximations of only a few cell subpopulations, however. In prior work, we demonstrated the feasibility of improving cell type deconvolution by taking advantage of substructure in genomic mixtures via a strategy called simplicial complex unmixing. We improve on past work by introducing enhancements to automate learning of substructured genomic mixtures, with specific emphasis on genome-wide copy number variation (CNV) data, as well as the ability to process quantitative RNA expression data, and heterogeneous combinations of RNA and CNV data. We introduce methods for dimensionality estimation to better decompose mixture model substructure; fuzzy clustering to better identify substructure in sparse, noisy data; and automated model inference methods for other key model parameters. We further demonstrate their effectiveness in identifying mixture substructure in true breast cancer CNV data from the Cancer Genome Atlas (TCGA). Source code is available at https://github.com/tedroman/WSCUnmix PMID:29059177

A dynamic landscape model for fish in the Everglades and its application to restoration

USGS Publications Warehouse

Gaff, H.D.; DeAngelis, D.L.; Gross, L.J.; Salinas, R.; Shorrosh, M.

2000-01-01

A model (ALFISH) for fish functional groups in freshwater marshes of the greater Everglades area of southern Florida has been developed. Its main objective is to assess the spatial pattern of fish densities through time across freshwater marshes. This model has the capability of providing a dynamic measure of the spatially-explicit food resources available to wading birds. ALFISH simulates two functional groups, large and small fish, where the larger ones can prey on the small fish type. Both functional groups are size-structured. The marsh landscape is modeled as 500×500 m spatial cells on a grid across southern Florida. A hydrology model predicts water levels in the spatial cells on 5-day time steps. Fish populations spread across the marsh during flooded conditions and either retreat into refugia (alligator ponds), move to other spatial cells, or die if their cell dries out. ALFISH has been applied to the evaluation of alternative water regulation scenarios under the Central and South Florida Comprehensive Project Review Study. The objective of this Review Study is to compare alternative methods for restoring historical ecological conditions in southern Florida. ALFISH has provided information on which plans are most are likely to increase fish biomass and its availability to wading bird populations.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

PubMed

Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

2017-04-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

Local cellular neighborhood controls proliferation in cell competition

PubMed Central

Bove, Anna; Gradeci, Daniel; Fujita, Yasuyuki; Banerjee, Shiladitya; Charras, Guillaume; Lowe, Alan R.

2017-01-01

Cell competition is a quality-control mechanism through which tissues eliminate unfit cells. Cell competition can result from short-range biochemical inductions or long-range mechanical cues. However, little is known about how cell-scale interactions give rise to population shifts in tissues, due to the lack of experimental and computational tools to efficiently characterize interactions at the single-cell level. Here, we address these challenges by combining long-term automated microscopy with deep-learning image analysis to decipher how single-cell behavior determines tissue makeup during competition. Using our high-throughput analysis pipeline, we show that competitive interactions between MDCK wild-type cells and cells depleted of the polarity protein scribble are governed by differential sensitivity to local density and the cell type of each cell’s neighbors. We find that local density has a dramatic effect on the rate of division and apoptosis under competitive conditions. Strikingly, our analysis reveals that proliferation of the winner cells is up-regulated in neighborhoods mostly populated by loser cells. These data suggest that tissue-scale population shifts are strongly affected by cellular-scale tissue organization. We present a quantitative mathematical model that demonstrates the effect of neighbor cell–type dependence of apoptosis and division in determining the fitness of competing cell lines. PMID:28931601

The Case for Absolute Ligand Discrimination: Modeling Information Processing and Decision by Immune T Cells

NASA Astrophysics Data System (ADS)

François, Paul; Altan-Bonnet, Grégoire

2016-03-01

Some cells have to take decision based on the quality of surroundings ligands, almost irrespective of their quantity, a problem we name "absolute discrimination". An example of absolute discrimination is recognition of not-self by immune T Cells. We show how the problem of absolute discrimination can be solved by a process called "adaptive sorting". We review several implementations of adaptive sorting, as well as its generic properties such as antagonism. We show how kinetic proofreading with negative feedback implement an approximate version of adaptive sorting in the immune context. Finally, we revisit the decision problem at the cell population level, showing how phenotypic variability and feedbacks between population and single cells are crucial for proper decision.

Establishing neural crest identity: a gene regulatory recipe

PubMed Central

Simões-Costa, Marcos; Bronner, Marianne E.

2015-01-01

The neural crest is a stem/progenitor cell population that contributes to a wide variety of derivatives, including sensory and autonomic ganglia, cartilage and bone of the face and pigment cells of the skin. Unique to vertebrate embryos, it has served as an excellent model system for the study of cell behavior and identity owing to its multipotency, motility and ability to form a broad array of cell types. Neural crest development is thought to be controlled by a suite of transcriptional and epigenetic inputs arranged hierarchically in a gene regulatory network. Here, we examine neural crest development from a gene regulatory perspective and discuss how the underlying genetic circuitry results in the features that define this unique cell population. PMID:25564621

Six-color intravital two-photon imaging of brain tumors and their dynamic microenvironment.

PubMed

Ricard, Clément; Debarbieux, Franck Christian

2014-01-01

The majority of intravital studies on brain tumor in living animal so far rely on dual color imaging. We describe here a multiphoton imaging protocol to dynamically characterize the interactions between six cellular components in a living mouse. We applied this methodology to a clinically relevant glioblastoma multiforme (GBM) model designed in reporter mice with targeted cell populations labeled by fluorescent proteins of different colors. This model permitted us to make non-invasive longitudinal and multi-scale observations of cell-to-cell interactions. We provide examples of such 5D (x,y,z,t,color) images acquired on a daily basis from volumes of interest, covering most of the mouse parietal cortex at subcellular resolution. Spectral deconvolution allowed us to accurately separate each cell population as well as some components of the extracellular matrix. The technique represents a powerful tool for investigating how tumor progression is influenced by the interactions of tumor cells with host cells and the extracellular matrix micro-environment. It will be especially valuable for evaluating neuro-oncological drug efficacy and target specificity. The imaging protocol provided here can be easily translated to other mouse models of neuropathologies, and should also be of fundamental interest for investigations in other areas of systems biology.

A compound chimeric antigen receptor strategy for targeting multiple myeloma.

PubMed

Chen, K H; Wada, M; Pinz, K G; Liu, H; Shuai, X; Chen, X; Yan, L E; Petrov, J C; Salman, H; Senzel, L; Leung, E L H; Jiang, X; Ma, Y

2018-02-01

Current clinical outcomes using chimeric-antigen receptors (CARs) against multiple myeloma show promise in the eradication of bulk disease. However, these anti-BCMA (CD269) CARs observe relapse as a common phenomenon after treatment due to the reemergence of either antigen-positive or -negative cells. Hence, the development of improvements in CAR design to target antigen loss and increase effector cell persistency represents a critical need. Here, we report on the anti-tumor activity of a CAR T-cell possessing two complete and independent CAR receptors against the multiple myeloma antigens BCMA and CS1. We determined that the resulting compound CAR (cCAR) T-cell possesses consistent, potent and directed cytotoxicity against each target antigen population. Using multiple mouse models of myeloma and mixed cell populations, we are further able to show superior in vivo survival by directed cytotoxicity against multiple populations compared to a single-expressing CAR T-cell. These findings indicate that compound targeting of BCMA and CS1 on myeloma cells can potentially be an effective strategy for augmenting the response against myeloma bulk disease and for initiation of broader coverage CAR therapy.

The Effect of Initial Cell Concentration on Xylose Fermentation by Pichia stipitis

NASA Astrophysics Data System (ADS)

Agbogbo, Frank K.; Coward-Kelly, Guillermo; Torry-Smith, Mads; Wenger, Kevin; Jeffries, Thomas W.

Xylose was fermented using Pichia stipitis CBS 6054 at different initial cell concentrations. A high initial cell concentration increased the rate of xylose utilization, ethanol formation, and the ethanol yield. The highest ethanol concentration of 41.0 g/L and a yield of 0.38 g/g was obtained using an initial cell concentration of 6.5 g/L. Even though more xylitol was produced when the initial cell concentrations were high, cell density had no effect on the final ethanol yield. A two-parameter mathematical model was used to predict the cell population dynamics at the different initial cell concentrations. The model parameters, a and b correlate with the initial cell concentrations used with an R 2 of 0.99.

Temporal Characterization of Microglia/Macrophage Phenotypes in a Mouse Model of Neonatal Hypoxic-Ischemic Brain Injury

PubMed Central

Hellström Erkenstam, Nina; Smith, Peter L. P.; Fleiss, Bobbi; Nair, Syam; Svedin, Pernilla; Wang, Wei; Boström, Martina; Gressens, Pierre; Hagberg, Henrik; Brown, Kelly L.; Sävman, Karin; Mallard, Carina

2016-01-01

Immune cells display a high degree of phenotypic plasticity, which may facilitate their participation in both the progression and resolution of injury-induced inflammation. The purpose of this study was to investigate the temporal expression of genes associated with classical and alternative polarization phenotypes described for macrophages and to identify related cell populations in the brain following neonatal hypoxia-ischemia (HI). HI was induced in 9-day old mice and brain tissue was collected up to 7 days post-insult to investigate expression of genes associated with macrophage activation. Using cell-markers, CD86 (classic activation) and CD206 (alternative activation), we assessed temporal changes of CD11b+ cell populations in the brain and studied the protein expression of the immunomodulatory factor galectin-3 in these cells. HI induced a rapid regulation (6 h) of genes associated with both classical and alternative polarization phenotypes in the injured hemisphere. FACS analysis showed a marked increase in the number of CD11b+CD86+ cells at 24 h after HI (+3667%), which was coupled with a relative suppression of CD11b+CD206+ cells and cells that did not express neither CD86 nor CD206. The CD11b+CD206+ population was mixed with some cells also expressing CD86. Confocal microscopy confirmed that a subset of cells expressed both CD86 and CD206, particularly in injured gray and white matter. Protein concentration of galectin-3 was markedly increased mainly in the cell population lacking CD86 or CD206 in the injured hemisphere. These cells were predominantly resident microglia as very few galectin-3 positive cells co-localized with infiltrating myeloid cells in Lys-EGFP-ki mice after HI. In summary, HI was characterized by an early mixed gene response, but with a large expansion of mainly the CD86 positive population during the first day. However, the injured hemisphere also contained a subset of cells expressing both CD86 and CD206 and a large population that expressed neither activation marker CD86 nor CD206. Interestingly, these cells expressed the highest levels of galectin-3 and were found to be predominantly resident microglia. Galectin-3 is a protein involved in chemotaxis and macrophage polarization suggesting a novel role in cell infiltration and immunomodulation for this cell population after neonatal injury. PMID:28018179

Direct Conversion Provides Old Neurons from Aged Donor's Skin.

PubMed

Koch, Philipp

2015-12-03

Modeling human neuronal aging at a cellular level remains challenging. Human neurons are accessible from iPSCs, but during reprogramming age-associated traits of somatic cells get lost. In this issue of Cell Stem Cell, Mertens et al. (2015) demonstrate that neurons obtained by direct cell conversion retain age-associated transcriptional traits and functional deficits of the donor cell population. Copyright © 2015 Elsevier Inc. All rights reserved.

Evolutionary dynamics of adult stem cells: comparison of random and immortal-strand segregation mechanisms.

PubMed

Tannenbaum, Emmanuel; Sherley, James L; Shakhnovich, Eugene I

2005-04-01

This paper develops a point-mutation model describing the evolutionary dynamics of a population of adult stem cells. Such a model may prove useful for quantitative studies of tissue aging and the emergence of cancer. We consider two modes of chromosome segregation: (1) random segregation, where the daughter chromosomes of a given parent chromosome segregate randomly into the stem cell and its differentiating sister cell and (2) "immortal DNA strand" co-segregation, for which the stem cell retains the daughter chromosomes with the oldest parent strands. Immortal strand co-segregation is a mechanism, originally proposed by [Cairns Nature (London) 255, 197 (1975)], by which stem cells preserve the integrity of their genomes. For random segregation, we develop an ordered strand pair formulation of the dynamics, analogous to the ordered strand pair formalism developed for quasispecies dynamics involving semiconservative replication with imperfect lesion repair (in this context, lesion repair is taken to mean repair of postreplication base-pair mismatches). Interestingly, a similar formulation is possible with immortal strand co-segregation, despite the fact that this segregation mechanism is age dependent. From our model we are able to mathematically show that, when lesion repair is imperfect, then immortal strand co-segregation leads to better preservation of the stem cell lineage than random chromosome segregation. Furthermore, our model allows us to estimate the optimal lesion repair efficiency for preserving an adult stem cell population for a given period of time. For human stem cells, we obtain that mispaired bases still present after replication and cell division should be left untouched, to avoid potentially fixing a mutation in both DNA strands.

Evolutionary dynamics of adult stem cells: Comparison of random and immortal-strand segregation mechanisms

NASA Astrophysics Data System (ADS)

Tannenbaum, Emmanuel; Sherley, James L.; Shakhnovich, Eugene I.

2005-04-01

This paper develops a point-mutation model describing the evolutionary dynamics of a population of adult stem cells. Such a model may prove useful for quantitative studies of tissue aging and the emergence of cancer. We consider two modes of chromosome segregation: (1) random segregation, where the daughter chromosomes of a given parent chromosome segregate randomly into the stem cell and its differentiating sister cell and (2) “immortal DNA strand” co-segregation, for which the stem cell retains the daughter chromosomes with the oldest parent strands. Immortal strand co-segregation is a mechanism, originally proposed by [Cairns Nature (London) 255, 197 (1975)], by which stem cells preserve the integrity of their genomes. For random segregation, we develop an ordered strand pair formulation of the dynamics, analogous to the ordered strand pair formalism developed for quasispecies dynamics involving semiconservative replication with imperfect lesion repair (in this context, lesion repair is taken to mean repair of postreplication base-pair mismatches). Interestingly, a similar formulation is possible with immortal strand co-segregation, despite the fact that this segregation mechanism is age dependent. From our model we are able to mathematically show that, when lesion repair is imperfect, then immortal strand co-segregation leads to better preservation of the stem cell lineage than random chromosome segregation. Furthermore, our model allows us to estimate the optimal lesion repair efficiency for preserving an adult stem cell population for a given period of time. For human stem cells, we obtain that mispaired bases still present after replication and cell division should be left untouched, to avoid potentially fixing a mutation in both DNA strands.

Interrogation of inhibitor of nuclear factor κB α/nuclear factor κB (IκBα/NF-κB) negative feedback loop dynamics: from single cells to live animals in vivo.

PubMed

Moss, Britney L; Elhammali, Adnan; Fowlkes, Tiffanie; Gross, Shimon; Vinjamoori, Anant; Contag, Christopher H; Piwnica-Worms, David

2012-09-07

Full understanding of the biological significance of negative feedback processes requires interrogation at multiple scales as follows: in single cells, cell populations, and live animals in vivo. The transcriptionally coupled IκBα/NF-κB negative feedback loop, a pivotal regulatory node of innate immunity and inflammation, represents a model system for multiscalar reporters. Using a κB(5)→IκBα-FLuc bioluminescent reporter, we rigorously evaluated the dynamics of ΙκBα degradation and subsequent NF-κB transcriptional activity in response to diverse modes of TNFα stimulation. Modulating TNFα concentration or pulse duration yielded complex, reproducible, and differential ΙκBα dynamics in both cell populations and live single cells. Tremendous heterogeneity in the transcriptional amplitudes of individual responding cells was observed, which was greater than the heterogeneity in the transcriptional kinetics of responsive cells. Furthermore, administration of various TNFα doses in vivo generated ΙκBα dynamic profiles in the liver resembling those observed in single cells and populations of cells stimulated with TNFα pulses. This suggested that dose modulation of circulating TNFα was perceived by hepatocytes in vivo as pulses of increasing duration. Thus, a robust bioluminescent reporter strategy enabled rigorous quantitation of NF-κB/ΙκBα dynamics in both live single cells and cell populations and furthermore, revealed reproducible behaviors that informed interpretation of in vivo studies.

Estimation of Cell Proliferation Dynamics Using CFSE Data

PubMed Central

Banks, H.T.; Sutton, Karyn L.; Thompson, W. Clayton; Bocharov, Gennady; Roose, Dirk; Schenkel, Tim; Meyerhans, Andreas

2010-01-01

Advances in fluorescent labeling of cells as measured by flow cytometry have allowed for quantitative studies of proliferating populations of cells. The investigations (Luzyanina et al. in J. Math. Biol. 54:57–89, 2007; J. Math. Biol., 2009; Theor. Biol. Med. Model. 4:1–26, 2007) contain a mathematical model with fluorescence intensity as a structure variable to describe the evolution in time of proliferating cells labeled by carboxyfluorescein succinimidyl ester (CFSE). Here, this model and several extensions/modifications are discussed. Suggestions for improvements are presented and analyzed with respect to statistical significance for better agreement between model solutions and experimental data. These investigations suggest that the new decay/label loss and time dependent effective proliferation and death rates do indeed provide improved fits of the model to data. Statistical models for the observed variability/noise in the data are discussed with implications for uncertainty quantification. The resulting new cell dynamics model should prove useful in proliferation assay tracking and modeling, with numerous applications in the biomedical sciences. PMID:20195910

Three distinct cell populations express extracellular matrix proteins and increase in number during skeletal muscle fibrosis.

PubMed

Chapman, Mark A; Mukund, Kavitha; Subramaniam, Shankar; Brenner, David; Lieber, Richard L

2017-02-01

Tissue extracellular matrix (ECM) provides structural support and creates unique environments for resident cells (Bateman JF, Boot-Handford RP, Lamandé SR. Nat Rev Genet 10: 173-183, 2009; Kjaer M. Physiol Rev 84: 649-98, 2004). However, the identities of cells responsible for creating specific ECM components have not been determined. In striated muscle, the identity of these cells becomes important in disease when ECM changes result in fibrosis and subsequent increased tissue stiffness and dysfunction. Here we describe a novel approach to isolate and identify cells that maintain the ECM in both healthy and fibrotic muscle. Using a collagen I reporter mouse, we show that there are three distinct cell populations that express collagen I in both healthy and fibrotic skeletal muscle. Interestingly, the number of collagen I-expressing cells in all three cell populations increases proportionally in fibrotic muscle, indicating that all cell types participate in the fibrosis process. Furthermore, while some profibrotic ECM and ECM-associated genes are significantly upregulated in fibrotic muscle, the fibrillar collagen gene expression profile is not qualitatively altered. This suggests that muscle fibrosis in this model results from an increased number of collagen I-expressing cells and not the initiation of a specific fibrotic collagen gene expression program. Finally, in fibrotic muscle, we show that these collagen I-expressing cell populations differentially express distinct ECM proteins-fibroblasts express the fibrillar components of ECM, fibro/adipogenic progenitors cells differentially express basal laminar proteins, and skeletal muscle progenitor cells differentially express genes important for the satellite cell. Copyright © 2017 the American Physiological Society.

A novel rat fibrosarcoma cell line from transformed bone marrow-derived mesenchymal stem cells with maintained in vitro and in vivo stemness properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Meng-Yu; Nestvold, Janne, E-mail: j.m.nestvold@medisin.uio.no; Rekdal, Øystein

Increasing evidence suggests a possible relationship between mesenchymal stem cells (MSCs) and sarcoma. MSCs are hypothesized to be the cells initiating sarcomagenesis, and cancer stem cells (CSCs) sharing features of MSCs have been identified in sarcomas. Here, we report on the characteristics of a bone marrow-derived rat mesenchymal stem cell line that spontaneously transformed in long-term culture. The rat transformed mesenchymal stem cells (rTMSCs) produced soft-tissue fibrosarcomas in immunocompromised mice and immunocompetent rats. In vitro, the rTMSCs displayed increased proliferation capacity compared to the untransformed cell line. The transformed MSCs maintained the mesenchymal phenotype by expression of the stem cellmore » marker CD 90 and the lack of hematopoietic and endothelial markers. Cytogenetic analysis detected trisomy 6 in the rTMSCs. Side population (SP) isolation and tumorsphere cultivation of the transformed cells confirmed the presence of CSCs among the rTMSCs. Importantly, the rTMSCs retained their differentiation capacity towards osteogenic and adipogenic lineages. This transformed MSC-based cell line may be valuable in examining the balance in a mixed cell population between cancer stem cell properties and the ability to differentiate to specific non-transformed cell populations. Moreover, it may also be a useful tool to evaluate the efficacy of novel targeted immunotherapies in vivo. - Highlights: • Spontaneously transformed rat MSCs (rTMSCs) share characteristics with normal MSCs. • rTMSCs possess a side population, enriched with tumorigenic cells. • rTMSCs model fibrosarcoma in vivo.« less

Three distinct cell populations express extracellular matrix proteins and increase in number during skeletal muscle fibrosis

PubMed Central

Chapman, Mark A.; Mukund, Kavitha; Subramaniam, Shankar; Brenner, David

2017-01-01

Tissue extracellular matrix (ECM) provides structural support and creates unique environments for resident cells (Bateman JF, Boot-Handford RP, Lamandé SR. Nat Rev Genet 10: 173–183, 2009; Kjaer M. Physiol Rev 84: 649–98, 2004). However, the identities of cells responsible for creating specific ECM components have not been determined. In striated muscle, the identity of these cells becomes important in disease when ECM changes result in fibrosis and subsequent increased tissue stiffness and dysfunction. Here we describe a novel approach to isolate and identify cells that maintain the ECM in both healthy and fibrotic muscle. Using a collagen I reporter mouse, we show that there are three distinct cell populations that express collagen I in both healthy and fibrotic skeletal muscle. Interestingly, the number of collagen I-expressing cells in all three cell populations increases proportionally in fibrotic muscle, indicating that all cell types participate in the fibrosis process. Furthermore, while some profibrotic ECM and ECM-associated genes are significantly upregulated in fibrotic muscle, the fibrillar collagen gene expression profile is not qualitatively altered. This suggests that muscle fibrosis in this model results from an increased number of collagen I-expressing cells and not the initiation of a specific fibrotic collagen gene expression program. Finally, in fibrotic muscle, we show that these collagen I-expressing cell populations differentially express distinct ECM proteins—fibroblasts express the fibrillar components of ECM, fibro/adipogenic progenitors cells differentially express basal laminar proteins, and skeletal muscle progenitor cells differentially express genes important for the satellite cell. PMID:27881411

Inverse problem of HIV cell dynamics using Genetic Algorithms

NASA Astrophysics Data System (ADS)

González, J. A.; Guzmán, F. S.

2017-01-01

In order to describe the cell dynamics of T-cells in a patient infected with HIV, we use a flavour of Perelson's model. This is a non-linear system of Ordinary Differential Equations that describes the evolution of healthy, latently infected, infected T-cell concentrations and the free viral cells. Different parameters in the equations give different dynamics. Considering the concentration of these types of cells is known for a particular patient, the inverse problem consists in estimating the parameters in the model. We solve this inverse problem using a Genetic Algorithm (GA) that minimizes the error between the solutions of the model and the data from the patient. These errors depend on the parameters of the GA, like mutation rate and population, although a detailed analysis of this dependence will be described elsewhere.

Mucosal BCG Vaccination Induces Protective Lung-Resident Memory T Cell Populations against Tuberculosis.

PubMed

Perdomo, Carolina; Zedler, Ulrike; Kühl, Anja A; Lozza, Laura; Saikali, Philippe; Sander, Leif E; Vogelzang, Alexis; Kaufmann, Stefan H E; Kupz, Andreas

2016-11-22

Mycobacterium bovis Bacille Calmette-Guérin (BCG) is the only licensed vaccine against tuberculosis (TB), yet its moderate efficacy against pulmonary TB calls for improved vaccination strategies. Mucosal BCG vaccination generates superior protection against TB in animal models; however, the mechanisms of protection remain elusive. Tissue-resident memory T (T RM ) cells have been implicated in protective immune responses against viral infections, but the role of T RM cells following mycobacterial infection is unknown. Using a mouse model of TB, we compared protection and lung cellular infiltrates of parenteral and mucosal BCG vaccination. Adoptive transfer and gene expression analyses of lung airway cells were performed to determine the protective capacities and phenotypes of different memory T cell subsets. In comparison to subcutaneous vaccination, intratracheal and intranasal BCG vaccination generated T effector memory and T RM cells in the lung, as defined by surface marker phenotype. Adoptive mucosal transfer of these airway-resident memory T cells into naive mice mediated protection against TB. Whereas airway-resident memory CD4 + T cells displayed a mixture of effector and regulatory phenotype, airway-resident memory CD8 + T cells displayed prototypical T RM features. Our data demonstrate a key role for mucosal vaccination-induced airway-resident T cells in the host defense against pulmonary TB. These results have direct implications for the design of refined vaccination strategies. BCG remains the only licensed vaccine against TB. Parenterally administered BCG has variable efficacy against pulmonary TB, and thus, improved prevention strategies and a more refined understanding of correlates of vaccine protection are required. Induction of memory T cells has been shown to be essential for protective TB vaccines. Mimicking the natural infection route by mucosal vaccination has been known to generate superior protection against TB in animal models; however, the mechanisms of protection have remained elusive. Here we performed an in-depth analysis to dissect the immunological mechanisms associated with superior mucosal protection in the mouse model of TB. We found that mucosal, and not subcutaneous, BCG vaccination generates lung-resident memory T cell populations that confer protection against pulmonary TB. We establish a comprehensive phenotypic characterization of these populations, providing a framework for future vaccine development. Copyright © 2016 Perdomo et al.

Characterization of aldehyde dehydrogenase 1 high ovarian cancer cells: Towards targeted stem cell therapy.

PubMed

Sharrow, Allison C; Perkins, Brandy; Collector, Michael I; Yu, Wayne; Simons, Brian W; Jones, Richard J

2016-08-01

The cancer stem cell (CSC) paradigm hypothesizes that successful clinical eradication of CSCs may lead to durable remission for patients with ovarian cancer. Despite mounting evidence in support of ovarian CSCs, their phenotype and clinical relevance remain unclear. We and others have found high aldehyde dehydrogenase 1 (ALDH(high)) expression in a variety of normal and malignant stem cells, and sought to better characterize ALDH(high) cells in ovarian cancer. We compared ALDH(high) to ALDH(low) cells in two ovarian cancer models representing distinct subtypes: FNAR-C1 cells, derived from a spontaneous rat endometrioid carcinoma, and the human SKOV3 cell line (described as both serous and clear cell subtypes). We assessed these populations for stem cell features then analyzed expression by microarray and qPCR. ALDH(high) cells displayed CSC properties, including: smaller size, quiescence, regenerating the phenotypic diversity of the cell lines in vitro, lack of contact inhibition, nonadherent growth, multi-drug resistance, and in vivo tumorigenicity. Microarray and qPCR analysis of the expression of markers reported by others to enrich for ovarian CSCs revealed that ALDH(high) cells of both models showed downregulation of CD24, but inconsistent expression of CD44, KIT and CD133. However, the following druggable targets were consistently expressed in the ALDH(high) cells from both models: mTOR signaling, her-2/neu, CD47 and FGF18/FGFR3. Based on functional characterization, ALDH(high) ovarian cancer cells represent an ovarian CSC population. Differential gene expression identified druggable targets that have the potential for therapeutic efficacy against ovarian CSCs from multiple subtypes. Copyright © 2016 Elsevier Inc. All rights reserved.

Evolution of resistance to anti-cancer therapy during general dosing schedules

PubMed Central

Foo, Jasmine; Michor, Franziska

2009-01-01

Anti-cancer drugs targeted to specific oncogenic pathways have shown promising therapeutic results in the past few years; however, drug resistance remains an important obstacle for these therapies. Resistance to these drugs can emerge due to a variety of reasons including genetic or epigenetic changes which alter the binding site of the drug target, cellular metabolism or export mechanisms. Obtaining a better understanding of the evolution of resistant populations during therapy may enable the design of more effective therapeutic regimens which prevent or delay progression of disease due to resistance. In this paper, we use stochastic mathematical models to study the evolutionary dynamics of resistance under time-varying dosing schedules and pharmacokinetic effects. The populations of sensitive and resistant cells are modeled as multi-type non-homogeneous birth-death processes in which the drug concentration affects the birth and death rates of both the sensitive and resistant cell populations in continuous time. This flexible model allows us to consider the effects of generalized treatment strategies as well as detailed pharmacokinetic phenomena such as drug elimination and accumulation over multiple doses. We develop estimates for the probability of developing resistance and moments of the size of the resistant cell population. With these estimates, we optimize treatment schedules over a subspace of tolerated schedules to minimize the risk of disease progression due to resistance as well as locate ideal schedules for controlling the population size of resistant clones in situations where resistance is inevitable. Our methodology can be used to describe dynamics of resistance arising due to a single (epi)genetic alteration in any tumor type. PMID:20004211

Hematopoietic Stem Cells as a Novel Source of Dental Tissue Cells.

PubMed

Wilson, Katie R; Kang, In-Hong; Baliga, Uday; Xiong, Ying; Chatterjee, Shilpak; Moore, Emily; Parthiban, Beneta; Thyagarajan, Krishnamurthy; Borke, James L; Mehrotra, Shikhar; Kirkwood, Keith L; LaRue, Amanda C; Ogawa, Makio; Mehrotra, Meenal

2018-05-23

While earlier studies have suggested that cells positive for hematopoietic markers can be found in dental tissues, it has yet to be confirmed. To conclusively demonstrate this, we utilized a unique transgenic model in which all hematopoietic cells are green fluorescent protein + (GFP + ). Pulp, periodontal ligament (PDL) and alveolar bone (AvB) cell culture analysis demonstrated numerous GFP + cells, which were also CD45 + (indicating hematopoietic origin) and co-expressed markers of cellular populations in pulp (dentin matrix protein-1, dentin sialophosphoprotein, alpha smooth muscle actin [ASMA], osteocalcin), in PDL (periostin, ASMA, vimentin, osteocalcin) and in AvB (Runx-2, bone sialoprotein, alkaline phosphatase, osteocalcin). Transplantation of clonal population derived from a single GFP + hematopoietic stem cell (HSC), into lethally irradiated recipient mice, demonstrated numerous GFP + cells within dental tissues of recipient mice, which also stained for markers of cell populations in pulp, PDL and AvB (used above), indicating that transplanted HSCs can differentiate into cells in dental tissues. These hematopoietic-derived cells deposited collagen and can differentiate in osteogenic media, indicating that they are functional. Thus, our studies demonstrate, for the first time, that cells in pulp, PDL and AvB can have a hematopoietic origin, thereby opening new avenues of therapy for dental diseases and injuries.

Identifying States along the Hematopoietic Stem Cell Differentiation Hierarchy with Single Cell Specificity via Raman Spectroscopy.

PubMed

Ilin, Yelena; Choi, Ji Sun; Harley, Brendan A C; Kraft, Mary L

2015-11-17

A major challenge for expanding specific types of hematopoietic cells ex vivo for the treatment of blood cell pathologies is identifying the combinations of cellular and matrix cues that direct hematopoietic stem cells (HSC) to self-renew or differentiate into cell populations ex vivo. Microscale screening platforms enable minimizing the number of rare HSCs required to screen the effects of numerous cues on HSC fate decisions. These platforms create a strong demand for label-free methods that accurately identify the fate decisions of individual hematopoietic cells at specific locations on the platform. We demonstrate the capacity to identify discrete cells along the HSC differentiation hierarchy via multivariate analysis of Raman spectra. Notably, cell state identification is accurate for individual cells and independent of the biophysical properties of the functionalized polyacrylamide gels upon which these cells are cultured. We report partial least-squares discriminant analysis (PLS-DA) models of single cell Raman spectra enable identifying four dissimilar hematopoietic cell populations across the HSC lineage specification. Successful discrimination was obtained for a population enriched for long-term repopulating HSCs (LT-HSCs) versus their more differentiated progeny, including closely related short-term repopulating HSCs (ST-HSCs) and fully differentiated lymphoid (B cells) and myeloid (granulocytes) cells. The lineage-specific differentiation states of cells from these four subpopulations were accurately identified independent of the stiffness of the underlying biomaterial substrate, indicating subtle spectral variations that discriminated these populations were not masked by features from the culture substrate. This approach enables identifying the lineage-specific differentiation stages of hematopoietic cells on biomaterial substrates of differing composition and may facilitate correlating hematopoietic cell fate decisions with the extrinsic cues that elicited them.

Daoy medulloblastoma cells that express CD133 are radioresistant relative to CD133- cells, and the CD133+ sector is enlarged by hypoxia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blazek, Ed R.; Foutch, Jennifer L.; Maki, Guitta

2007-01-01

Purpose: Primary medulloblastoma and glioblastoma multiforme tumor cells that express the surface marker CD133 are believed to be enriched for brain tumor stem cells because of their unique ability to initiate or reconstitute tumors in immunodeficient mice. This study sought to characterize the radiobiological properties and marker expression changes of CD133+ vs. CD133- cells of an established medulloblastoma cell line. Methods and Materials: Daoy and D283 Med cell lines were stained with fluorescently labeled anti-CD133 antibody and sorted into CD133+ and CD133- populations. The effect of oxygen (2% vs. 20%) on CD133 expression was measured. Both populations were analyzed formore » marker stability, cell cycle distribution, and radiosensitivity. Results: CD133+ Daoy cells restored nearly native CD133+ and CD133- populations within 18 days, whereas CD133- cells remained overwhelmingly CD133-. Culturing Daoy cells in 2% oxygen rather than the standard 20% oxygen increased their CD133 expression 1.6-fold. CD133+ Daoy cells were radioresistant via the {beta}-parameter of the linear-quadratic model relative to CD133- Daoy cells, although their {alpha}-parameters and cell cycle distributions were identical. Conclusions: Restoration of the original CD133+ and CD133- populations from CD133+ Daoy cells in serum is further evidence that CD133+ cells are functionally distinct from CD133- cells. The radioresistance of CD133+ compared with CD133- Daoy cells is consistent with better repair of sublethal damage. Enlargement of the CD133+ sector is a new feature of the hypoxic response.« less

Novel fusion proteins for the antigen-specific staining and elimination of B cell receptor-positive cell populations demonstrated by a tetanus toxoid fragment C (TTC) model antigen.

PubMed

Klose, Diana; Saunders, Ute; Barth, Stefan; Fischer, Rainer; Jacobi, Annett Marita; Nachreiner, Thomas

2016-02-17

In an earlier study we developed a unique strategy allowing us to specifically eliminate antigen-specific murine B cells via their distinct B cell receptors using a new class of fusion proteins. In the present work we elaborated our idea to demonstrate the feasibility of specifically addressing and eliminating human memory B cells. The present study reveals efficient adaptation of the general approach to selectively target and eradicate human memory B cells. In order to demonstrate the feasibility we engineered a fusion protein following the principle of recombinant immunotoxins by combining a model antigen (tetanus toxoid fragment C, TTC) for B cell receptor targeting and a truncated version of Pseudomonas aeruginosa exotoxin A (ETA') to induce apoptosis after cellular uptake. The TTC-ETA' fusion protein not only selectively bound to a TTC-reactive murine B cell hybridoma cell line in vitro but also to freshly isolated human memory B cells from immunized donors ex vivo. Specific toxicity was confirmed on an antigen-specific population of human CD27(+) memory B cells. This protein engineering strategy can be used as a generalized platform approach for the construction of therapeutic fusion proteins with disease-relevant antigens as B cell receptor-binding domains, offering a promising approach for the specific depletion of autoreactive B-lymphocytes in B cell-driven autoimmune diseases.

Src Family Kinases and p38 Mitogen-Activated Protein Kinases Regulate Pluripotent Cell Differentiation in Culture

PubMed Central

Tan, Boon Siang Nicholas; Kwek, Joly; Wong, Chong Kum Edwin; Saner, Nicholas J.; Yap, Charlotte; Felquer, Fernando; Morris, Michael B.; Gardner, David K.; Rathjen, Peter D.; Rathjen, Joy

2016-01-01

Multiple pluripotent cell populations, which together comprise the pluripotent cell lineage, have been identified. The mechanisms that control the progression between these populations are still poorly understood. The formation of early primitive ectoderm-like (EPL) cells from mouse embryonic stem (mES) cells provides a model to understand how one such transition is regulated. EPL cells form from mES cells in response to l-proline uptake through the transporter Slc38a2. Using inhibitors of cell signaling we have shown that Src family kinases, p38 MAPK, ERK1/2 and GSK3β are required for the transition between mES and EPL cells. ERK1/2, c-Src and GSK3β are likely to be enforcing a receptive, primed state in mES cells, while Src family kinases and p38 MAPK are involved in the establishment of EPL cells. Inhibition of these pathways prevented the acquisition of most, but not all, features of EPL cells, suggesting that other pathways are required. L-proline activation of differentiation is mediated through metabolism and changes to intracellular metabolite levels, specifically reactive oxygen species. The implication of multiple signaling pathways in the process suggests a model in which the context of Src family kinase activation determines the outcomes of pluripotent cell differentiation. PMID:27723793

Dynamic self-organisation of haematopoiesis and (a)symmetric cell division.

PubMed

Måløy, Marthe; Måløy, Frode; Jakobsen, Per; Olav Brandsdal, Bjørn

2017-02-07

A model of haematopoiesis that links self-organisation with symmetric and asymmetric cell division is presented in this paper. It is assumed that all cell divisions are completely random events, and that the daughter cells resulting from symmetric and asymmetric stem cell divisions are, in general, phenotypically identical, and still, the haematopoietic system has the flexibility to self-renew, produce mature cells by differentiation, and regenerate undifferentiated and differentiated cells when necessary, due to self-organisation. As far as we know, no previous model implements symmetric and asymmetric division as the result of self-organisation. The model presented in this paper is inspired by experiments on the Drosophila germline stem cell, which imply that under normal conditions, the stem cells typically divide asymmetrically, whereas during regeneration, the rate of symmetric division increases. Moreover, the model can reproduce several of the results from experiments on female Safari cats. In particular, the model can explain why significant fluctuation in the phenotypes of haematopoietic cells was observed in some cats, when the haematopoietic system had reached normal population level after regeneration. To our knowledge, no previous model of haematopoiesis in Safari cats has captured this phenomenon. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Biophysics Representation of the Two-Hit Model of Alzheimer's Disease for the Exploration of Late CNS Risks from Space Radiation

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem

2009-01-01

A concern for long-term space travel outside the Earth s magnetic field is the late effects to the central nervous system (CNS) from galactic cosmic ray (GCR) or solar particle events (SPE). Human epidemiology data is severely limited for making CNS risk estimates and it is not clear such effects occur following low LET exposures. We are developing systems biology models based on biological information on specific diseases, and experimental data for proton and heavy ion radiation. A two-hit model of Alzheimer s disease (AD) has been proposed by Zhu et al.(1), which is the framework of our model. Of importance is that over 50% of the US population over the age of 75-y have mild to severe forms of AD. Therefore we recommend that risk assessment for a potential AD risk from space radiation should focus on the projection of an earlier age of onset of AD and the prevention of this possible acceleration through countermeasures. In the two-hit model, oxidative stress and aberrant cell cycle-related abnormalities leading to amyloid-beta plaques and neurofibrillary tangles are necessary and invariant steps in AD. We have formulated a stochastic cell kinetics model of the two-hit AD model. In our model a population of neuronal cells is allowed to undergo renewal through neurogenesis and is susceptible to oxidative stress or cell cycle abnormalities with age-specific accumulation of damage. Baseline rates are fitted to AD population data for specific ages, gender, and for persons with an apolipoprotein 4 allele. We then explore how low LET or heavy ions may increase either of the two-hits or neurogenesis either through persistent oxidative stress, direct mutation, or through changes to the micro-environment, and suggest possible ways to develop accurate quantitative estimates of these processes for predicting AD risks following long-term space travel.

Cancer treatment in childhood and testicular function: the importance of the somatic environment.

PubMed

Stukenborg, Jan-Bernd; Jahnukainen, Kirsi; Hutka, Marsida; Mitchell, Rod T

2018-02-01

Testicular function and future fertility may be affected by cancer treatment during childhood. Whilst survival of the germ (stem) cells is critical for ensuring the potential for fertility in these patients, the somatic cell populations also play a crucial role in providing a suitable environment to support germ cell maintenance and subsequent development. Regulation of the spermatogonial germ-stem cell niche involves many signalling pathways with hormonal influence from the hypothalamo-pituitary-gonadal axis. In this review, we describe the somatic cell populations that comprise the testicular germ-stem cell niche in humans and how they may be affected by cancer treatment during childhood. We also discuss the experimental models that may be utilized to manipulate the somatic environment and report the results of studies that investigate the potential role of somatic cells in the protection of the germ cells in the testis from cancer treatment. © 2018 The authors.

Cancer treatment in childhood and testicular function: the importance of the somatic environment

PubMed Central

Stukenborg, Jan-Bernd; Jahnukainen, Kirsi; Hutka, Marsida

2018-01-01

Testicular function and future fertility may be affected by cancer treatment during childhood. Whilst survival of the germ (stem) cells is critical for ensuring the potential for fertility in these patients, the somatic cell populations also play a crucial role in providing a suitable environment to support germ cell maintenance and subsequent development. Regulation of the spermatogonial germ-stem cell niche involves many signalling pathways with hormonal influence from the hypothalamo-pituitary-gonadal axis. In this review, we describe the somatic cell populations that comprise the testicular germ-stem cell niche in humans and how they may be affected by cancer treatment during childhood. We also discuss the experimental models that may be utilized to manipulate the somatic environment and report the results of studies that investigate the potential role of somatic cells in the protection of the germ cells in the testis from cancer treatment. PMID:29351905

A neuro-computational model of economic decisions.

PubMed

Rustichini, Aldo; Padoa-Schioppa, Camillo

2015-09-01

Neuronal recordings and lesion studies indicate that key aspects of economic decisions take place in the orbitofrontal cortex (OFC). Previous work identified in this area three groups of neurons encoding the offer value, the chosen value, and the identity of the chosen good. An important and open question is whether and how decisions could emerge from a neural circuit formed by these three populations. Here we adapted a biophysically realistic neural network previously proposed for perceptual decisions (Wang XJ. Neuron 36: 955-968, 2002; Wong KF, Wang XJ. J Neurosci 26: 1314-1328, 2006). The domain of economic decisions is significantly broader than that for which the model was originally designed, yet the model performed remarkably well. The input and output nodes of the network were naturally mapped onto two groups of cells in OFC. Surprisingly, the activity of interneurons in the network closely resembled that of the third group of cells, namely, chosen value cells. The model reproduced several phenomena related to the neuronal origins of choice variability. It also generated testable predictions on the excitatory/inhibitory nature of different neuronal populations and on their connectivity. Some aspects of the empirical data were not reproduced, but simple extensions of the model could overcome these limitations. These results render a biologically credible model for the neuronal mechanisms of economic decisions. They demonstrate that choices could emerge from the activity of cells in the OFC, suggesting that chosen value cells directly participate in the decision process. Importantly, Wang's model provides a platform to investigate the implications of neuroscience results for economic theory. Copyright © 2015 the American Physiological Society.

A New Model for the Estimation of Cell Proliferation Dynamics Using CFSE Data

PubMed Central

Banks, H.T.; Sutton, Karyn L.; Thompson, W. Clayton; Bocharov, Gennady; Doumic, Marie; Schenkel, Tim; Argilaguet, Jordi; Giest, Sandra; Peligero, Cristina; Meyerhans, Andreas

2011-01-01

CFSE analysis of a proliferating cell population is a popular tool for the study of cell division and division-linked changes in cell behavior. Recently [13, 43, 45], a partial differential equation (PDE) model to describe lymphocyte dynamics in a CFSE proliferation assay was proposed. We present a significant revision of this model which improves the physiological understanding of several parameters. Namely, the parameter γ used previously as a heuristic explanation for the dilution of CFSE dye by cell division is replaced with a more physical component, cellular autofluorescence. The rate at which label decays is also quantified using a Gompertz decay process. We then demonstrate a revised method of fitting the model to the commonly used histogram representation of the data. It is shown that these improvements result in a model with a strong physiological basis which is fully capable of replicating the behavior observed in the data. PMID:21889510

A requirement for the Vgamma1+ subset of peripheral gammadelta T cells in the control of the systemic growth of Toxoplasma gondii and infection-induced pathology.

PubMed

Egan, Charlotte E; Dalton, Jane E; Andrew, Elizabeth M; Smith, Judith E; Gubbels, Marc-Jan; Striepen, Boris; Carding, Simon R

2005-12-15

gammadelta T cells are a diverse population of T cells that are widely distributed and are a common feature of pathogen-induced immune responses. It is not clear, however, whether different populations of gammadelta T cells have specific functions, and what factors determine the functional properties of individual populations. A murine model of peroral Toxoplasma gondii infection was used to determine the contribution Vgamma1+ intestinal intraepithelial lymphocytes (IELs) vs systemic Vgamma1+ T cells make to the acute and chronic stages of the host immune response, and whether the macrophage cytocidal activity of Vgamma1+ T cells described in bacterial infections is seen in other, unrelated infectious disease models. In response to oral infection with virulent type 1 or avirulent type II strains of T. gondii, TCR-delta-/- mice rapidly developed severe ileitis. In contrast, in mice deficient in Vgamma1+ T cells and IELs and wild-type mice, inflammation was delayed in onset and less severe. The protective effect of (Vgamma1-) IELs to Toxoplasma infection was unrelated to their cytolytic and cytokine (Th1)-producing capabilities. Systemic Vgamma1+ T cells were shown to play an essential role in limiting parasite growth and inflammation in peripheral tissues and, in particular, in the CNS, that was associated with their ability to efficiently kill parasite-elicited and infected macrophages. These findings suggest that macrophage cytocidal activity of Vgamma1+ T cells may be a universal feature of pathogen-induced immune responses and that microenvironmental factors influence the involvement and function of gammadelta T cells in the host response to infection.

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

Clustering Single-Cell Expression Data Using Random Forest Graphs.

PubMed

Pouyan, Maziyar Baran; Nourani, Mehrdad

2017-07-01

Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.

Pluripotent stem cell-derived natural killer cells for cancer therapy

PubMed Central

Knorr, David A.; Kaufman, Dan S.

2010-01-01

Human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) provide an accessible, genetically tractable and homogenous starting cell populations to efficiently study human blood cell development. These cell populations provide platforms to develop new cell-based therapies to treat both malignant and non-malignant hematological diseases. Our group has previously demonstrated the ability of hESC-derived hematopoietic precursors to produce functional natural killer (NK) cells as well as an explanation of the underlying mechanism responsible for inefficient development of T and B cells from hESCs. hESCs and iPSCs, which can be reliably engineered in vitro, provide an important new model system to study human lymphocyte development and produce enhanced cell-based therapies with potential to serve as a “universal” source of anti-tumor lymphocytes for novel clinical therapies. This review will focus on the application of hESC-derived NK cells with currently used and novel therapeutics for clinical trials, current barriers to translation, and future applications through genetic engineering approaches. PMID:20801411

Adipogenic placenta-derived mesenchymal stem cells are not lineage restricted by withdrawing extrinsic factors: developing a novel visual angle in stem cell biology.

PubMed

Hu, C; Cao, H; Pan, X; Li, J; He, J; Pan, Q; Xin, J; Yu, X; Li, J; Wang, Y; Zhu, D; Li, L

2016-03-17

Current evidence implies that differentiated bone marrow mesenchymal stem cells (BMMSCs) can act as progenitor cells and transdifferentiate across lineage boundaries. However, whether this unrestricted lineage has specificities depending on the stem cell type is unknown. Placental-derived mesenchymal stem cells (PDMSCs), an easily accessible and less invasive source, are extremely useful materials in current stem cell therapies. No studies have comprehensively analyzed the transition in morphology, surface antigens, metabolism and multilineage potency of differentiated PDMSCs after their dedifferentiation. In this study, we showed that after withdrawing extrinsic factors, adipogenic PDMSCs reverted to a primitive cell population and retained stem cell characteristics. The mitochondrial network during differentiation and dedifferentiation may serve as a marker of absent or acquired pluripotency in various stem cell models. The new population proliferated faster than unmanipulated PDMSCs and could be differentiated into adipocytes, osteocytes and hepatocytes. The cell adhesion molecules (CAMs) signaling pathway and extracellular matrix (ECM) components modulate cell behavior and enable the cells to proliferate or differentiate during the differentiation, dedifferentiation and redifferentiation processes in our study. These observations indicate that the dedifferentiated PDMSCs are distinguishable from the original PDMSCs and may serve as a novel source in stem cell biology and cell-based therapeutic strategies. Furthermore, whether PDMSCs differentiated into other lineages can be dedifferentiated to a primitive cell population needs to be investigated.

Differential equations with applications in cancer diseases.

PubMed

Ilea, M; Turnea, M; Rotariu, M

2013-01-01

Mathematical modeling is a process by which a real world problem is described by a mathematical formulation. The cancer modeling is a highly challenging problem at the frontier of applied mathematics. A variety of modeling strategies have been developed, each focusing on one or more aspects of cancer. The vast majority of mathematical models in cancer diseases biology are formulated in terms of differential equations. We propose an original mathematical model with small parameter for the interactions between these two cancer cell sub-populations and the mathematical model of a vascular tumor. We work on the assumption that, the quiescent cells' nutrient consumption is long. One the equations system includes small parameter epsilon. The smallness of epsilon is relative to the size of the solution domain. MATLAB simulations obtained for transition rate from the quiescent cells' nutrient consumption is long, we show a similar asymptotic behavior for two solutions of the perturbed problem. In this system, the small parameter is an asymptotic variable, different from the independent variable. The graphical output for a mathematical model of a vascular tumor shows the differences in the evolution of the tumor populations of proliferating, quiescent and necrotic cells. The nutrient concentration decreases sharply through the viable rim and tends to a constant level in the core due to the nearly complete necrosis in this region. Many mathematical models can be quantitatively characterized by ordinary differential equations or partial differential equations. The use of MATLAB in this article illustrates the important role of informatics in research in mathematical modeling. The study of avascular tumor growth cells is an exciting and important topic in cancer research and will profit considerably from theoretical input. Interpret these results to be a permanent collaboration between math's and medical oncologists.

Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper.

PubMed

Kim, Ji-Hoon; Kang, Wee-Soo; Yun, Sung-Chul

2014-06-01

A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For successful infection, at least 5,000 cells/ml of the bacterial population were required. Also, wind and rain were necessary according to regression analyses of the monitored data. Bacterial spot on the model is initiated when the pathogen population exceeds 10(15) cells/g within the leaf. The developed model was validated using 94 assessed samples from 2000 to 2007 obtained from monitored fields. Based on the validation study, the predicted initial infection dates varied based on the year rather than the location. Differences in initial infection dates between the model predictions and the monitored data in the field were minimal. For example, predicted infection dates for 7 locations were within the same month as the actual infection dates, 11 locations were within 1 month of the actual infection, and only 3 locations were more than 2 months apart from the actual infection. The predicted infection dates were mapped from 2009 to 2012; 2011 was the most severe year. Although the model was not sensitive enough to predict disease severity of less than 0.1% in the field, our model predicted bacterial spot severity of 1% or more. Therefore, this model can be applied in the field to determine when bacterial spot control is required.

Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper

PubMed Central

Kim, Ji-Hoon; Kang, Wee-Soo; Yun, Sung-Chul

2014-01-01

A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For successful infection, at least 5,000 cells/ml of the bacterial population were required. Also, wind and rain were necessary according to regression analyses of the monitored data. Bacterial spot on the model is initiated when the pathogen population exceeds 1015 cells/g within the leaf. The developed model was validated using 94 assessed samples from 2000 to 2007 obtained from monitored fields. Based on the validation study, the predicted initial infection dates varied based on the year rather than the location. Differences in initial infection dates between the model predictions and the monitored data in the field were minimal. For example, predicted infection dates for 7 locations were within the same month as the actual infection dates, 11 locations were within 1 month of the actual infection, and only 3 locations were more than 2 months apart from the actual infection. The predicted infection dates were mapped from 2009 to 2012; 2011 was the most severe year. Although the model was not sensitive enough to predict disease severity of less than 0.1% in the field, our model predicted bacterial spot severity of 1% or more. Therefore, this model can be applied in the field to determine when bacterial spot control is required. PMID:25288995

Digital signaling decouples activation probability and population heterogeneity.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Lipniacki, Tomasz; Quake, Stephen R; Tay, Savaş

2015-10-21

Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.

Vortex Lattice UXO Mobility Model Integration

DTIC Science & Technology

2015-03-01

law , no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB...predictions of the fate and transport of a broad-field UXO population are extremely sensitive to the initial state of that population, specifically: the...limit the model’s computational domain. This revised model software was built on the concept of interconnected geomorphic control cells consisting of

Preclinical Corrective Gene Transfer in Xeroderma Pigmentosum Human Skin Stem Cells

PubMed Central

Warrick, Emilie; Garcia, Marta; Chagnoleau, Corinne; Chevallier, Odile; Bergoglio, Valérie; Sartori, Daniela; Mavilio, Fulvio; Angulo, Jaime F; Avril, Marie-Françoise; Sarasin, Alain; Larcher, Fernando; Del Rio, Marcela; Bernerd, Françoise; Magnaldo, Thierry

2012-01-01

Xeroderma pigmentosum (XP) is a devastating disease associated with dramatic skin cancer proneness. XP cells are deficient in nucleotide excision repair (NER) of bulky DNA adducts including ultraviolet (UV)-induced mutagenic lesions. Approaches of corrective gene transfer in NER-deficient keratinocyte stem cells hold great hope for the long-term treatment of XP patients. To face this challenge, we developed a retrovirus-based strategy to safely transduce the wild-type XPC gene into clonogenic human primary XP-C keratinocytes. De novo expression of XPC was maintained in both mass population and derived independent candidate stem cells (holoclones) after more than 130 population doublings (PD) in culture upon serial propagation (>1040 cells). Analyses of retrovirus integration sequences in isolated keratinocyte stem cells suggested the absence of adverse effects such as oncogenic activation or clonal expansion. Furthermore, corrected XP-C keratinocytes exhibited full NER capacity as well as normal features of epidermal differentiation in both organotypic skin cultures and in a preclinical murine model of human skin regeneration in vivo. The achievement of a long-term genetic correction of XP-C epidermal stem cells constitutes the first preclinical model of ex vivo gene therapy for XP-C patients. PMID:22068429

A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion.

PubMed

Anderson, Alexander R A

2005-06-01

In this paper we present a hybrid mathematical model of the invasion of healthy tissue by a solid tumour. In particular we consider early vascular growth, just after angiogenesis has occurred. We examine how the geometry of the growing tumour is affected by tumour cell heterogeneity caused by genetic mutations. As the tumour grows, mutations occur leading to a heterogeneous tumour cell population with some cells having a greater ability to migrate, proliferate or degrade the surrounding tissue. All of these cell properties are closely controlled by cell-cell and cell-matrix interactions and as such the physical geometry of the whole tumour will be dependent on these individual cell interactions. The hybrid model we develop focuses on four key variables implicated in the invasion process: tumour cells, host tissue (extracellular matrix), matrix-degradative enzymes and oxygen. The model is considered to be hybrid since the latter three variables are continuous (i.e. concentrations) and the tumour cells are discrete (i.e. individuals). With this hybrid model we examine how individual-based cell interactions (with one another and the matrix) can affect the tumour shape and discuss which of these interactions is perhaps most crucial in influencing the tumour's final structure.

Mathematical modelling of skeletal repair.

PubMed

MacArthur, B D; Please, C P; Taylor, M; Oreffo, R O C

2004-01-23

Tissue engineering offers significant promise as a viable alternative to current clinical strategies for replacement of damaged tissue as a consequence of disease or trauma. Since mathematical modelling is a valuable tool in the analysis of complex systems, appropriate use of mathematical models has tremendous potential for advancing the understanding of the physical processes involved in such tissue reconstruction. In this review, the potential benefits, and limitations, of theoretical modelling in tissue engineering applications are examined with specific emphasis on tissue engineering of bone. A central tissue engineering approach is the in vivo implantation of a biomimetic scaffold seeded with an appropriate population of stem or progenitor cells. This review will therefore consider the theory behind a number of key factors affecting the success of such a strategy including: stem cell or progenitor population expansion and differentiation ex vivo; cell adhesion and migration, and the effective design of scaffolds; and delivery of nutrient to avascular structures. The focus will be on current work in this area, as well as on highlighting limitations and suggesting possible directions for future work to advance health-care for all.

A generalised age- and phase-structured model of human tumour cell populations both unperturbed and exposed to a range of cancer therapies.

PubMed

Basse, Britta; Ubezio, Paolo

2007-07-01

We develop a general mathematical model for a population of cells differentiated by their position within the cell division cycle. A system of partial differential equations governs the kinetics of cell densities in certain phases of the cell division cycle dependent on time t (hours) and an age-like variable tau (hours) describing the time since arrival in a particular phase of the cell division cycle. Transition rate functions control the transfer of cells between phases. We first obtain a theoretical solution on the infinite domain -infinity < t < infinity. We then assume that age distributions at time t=0 are known and write our solution in terms of these age distributions on t=0. In practice, of course, these age distributions are unknown. All is not lost, however, because a cell line before treatment usually lies in a state of asynchronous balanced growth where the proportion of cells in each phase of the cell cycle remain constant. We assume that an unperturbed cell line has four distinct phases and that the rate of transition between phases is constant within a short period of observation ('short' relative to the whole history of the tumour growth) and we show that under certain conditions, this is equivalent to exponential growth or decline. We can then gain expressions for the age distributions. So, in short, our approach is to assume that we have an unperturbed cell line on t

Response of single bacterial cells to stress gives rise to complex history dependence at the population level

PubMed Central

Mathis, Roland; Ackermann, Martin

2016-01-01

Most bacteria live in ever-changing environments where periods of stress are common. One fundamental question is whether individual bacterial cells have an increased tolerance to stress if they recently have been exposed to lower levels of the same stressor. To address this question, we worked with the bacterium Caulobacter crescentus and asked whether exposure to a moderate concentration of sodium chloride would affect survival during later exposure to a higher concentration. We found that the effects measured at the population level depended in a surprising and complex way on the time interval between the two exposure events: The effect of the first exposure on survival of the second exposure was positive for some time intervals but negative for others. We hypothesized that the complex pattern of history dependence at the population level was a consequence of the responses of individual cells to sodium chloride that we observed: (i) exposure to moderate concentrations of sodium chloride caused delays in cell division and led to cell-cycle synchronization, and (ii) whether a bacterium would survive subsequent exposure to higher concentrations was dependent on the cell-cycle state. Using computational modeling, we demonstrated that indeed the combination of these two effects could explain the complex patterns of history dependence observed at the population level. Our insight into how the behavior of single cells scales up to processes at the population level provides a perspective on how organisms operate in dynamic environments with fluctuating stress exposure. PMID:26960998

The Role of Mechanical Variance and Spatial Clustering on the Likelihood of Tumor Incidence and Growth

NASA Astrophysics Data System (ADS)

Mirzakhel, Zibah

When considering factors that contribute to cancer progression, modifications to both the biological and mechanical pathways play significant roles. However, less attention is placed on how the mechanical pathways can specifically contribute to cancerous behavior. Experimental studies have found that malignant cells are significantly softer than healthy, normal cells. In a tissue environment where healthy or malignant cells exist, a distribution of cell stiffness values is observed, with the mean values used to differentiate between these two populations. Rather than focus on the mean values, emphasis will be placed on the distribution, where instances of soft and stiff cells exist in the healthy tissue environment. Since cell deformability is a trait associated with cancer, the question arises as to whether the mechanical variation observed in healthy tissue cell stiffness distributions can influence any instances of tumor growth. To approach this, a 3D discrete model of cells is used, able to monitor and predict the behavior of individual cells while determining any instances of tumor growth in a healthy tissue. In addition to the mechanical variance, the spatial arrangement of cells will also be modeled, as cell interaction could further implicate any incidences of tumor-like malignant populations within the tissue. Results have shown that the likelihood of tumor incidence is driven by both by the increases in the mechanical variation in the distributions as well as larger clustering of cells that are mechanically similar, quantified primarily through higher proliferation rates of tumor-like soft cells. This can be observed though prominent negative shifts in the mean of the distribution, as it begins to transition and show instances of earlystage tumor growth. The model reveals the impact that both the mechanical variation and spatial arrangement of cells has on tumor progression, suggesting the use of these parameters as potential novel biomarkers. With a patient-specific approach in mind, the model may be applied for early-stage cancer detection, useful to establish a timeline on tumor progression.

Population pharmacokinetic-pharmacodynamic modeling and model-based prediction of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer.

PubMed

Fukae, Masato; Shiraishi, Yoshimasa; Hirota, Takeshi; Sasaki, Yuka; Yamahashi, Mika; Takayama, Koichi; Nakanishi, Yoichi; Ieiri, Ichiro

2016-11-01

Docetaxel is used to treat many cancers, and neutropenia is the dose-limiting factor for its clinical use. A population pharmacokinetic-pharmacodynamic (PK-PD) model was introduced to predict the development of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer (NSCLC). Forty-seven advanced or recurrent Japanese patients with NSCLC were enrolled. Patients received 50 or 60 mg/m 2 docetaxel as monotherapy, and blood samples for a PK analysis were collected up to 24 h after its infusion. Laboratory tests including absolute neutrophil count data and demographic information were used in population PK-PD modeling. The model was built by NONMEM 7.2 with a first-order conditional estimation using an interaction method. Based on the final model, a Monte Carlo simulation was performed to assess the impact of covariates on and the predictability of neutropenia. A three-compartment model was employed to describe PK data, and the PK model adequately described the docetaxel concentrations observed. Serum albumin (ALB) was detected as a covariate of clearance (CL): CL (L/h) = 32.5 × (ALB/3.6) 0.965  × (WGHT/70) 3/4 . In population PK-PD modeling, a modified semi-mechanistic myelosuppression model was applied, and characterization of the time course of neutrophil counts was adequate. The covariate selection indicated that α1-acid glycoprotein (AAG) was a predictor of neutropenia. The model-based simulation also showed that ALB and AAG negatively correlated with the development of neutropenia and that the time course of neutrophil counts was predictable. The developed model may facilitate the prediction and care of docetaxel-induced neutropenia.

Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

PubMed

Ponzi, Adam; Wickens, Jeff

2012-01-01

The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

Input Dependent Cell Assembly Dynamics in a Model of the Striatal Medium Spiny Neuron Network

PubMed Central

Ponzi, Adam; Wickens, Jeff

2012-01-01

The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior. PMID:22438838

Midkine and multiple sclerosis

PubMed Central

Takeuchi, Hideyuki

2014-01-01

Multiple sclerosis (MS) is an autoimmune neurological disease characterized by inflammatory demyelination with subsequent neuronal damage in the CNS. MS and its animal model, experimental autoimmune encephalomyelitis (EAE), have been thought as autoreactive Th1 and Th17 cell-mediated diseases. CD4+CD25+FoxP3+ regulatory T-cell (Treg) plays a pivotal role in autoimmune tolerance, and tolerogenic dendritic cells (DCreg) drive the development of inducible Treg cells. Thus, a dysfunction in the development of Treg and DCreg leads to the development of autoimmune diseases. However, the factors that regulate Treg and DCreg are largely unknown. We recently showed that removal of midkine (MK) suppressed EAE due to an expansion of the Treg cell population as well as a decrease in the numbers of autoreactive Th1 and Th17 cells. MK decreased the Treg cell population by suppressing the phosphorylation of STAT5, which is essential for the expression of Foxp3, the master transcriptional factor of Treg cell differentiation. Furthermore, MK reduces the DCreg cell population by inhibiting the phosphorylation of STAT3, which is critical for DCreg development. Blockade of MK signalling by a specific RNA aptamer significantly elevated the population of DCreg and Treg cells and ameliorated EAE without detectable adverse effects. Therefore, the inhibition of MK may provide an effective therapeutic strategy against autoimmune diseases including MS. Linked Articles This article is part of a themed section on Midkine. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2014.171.issue-4 PMID:24460675

Emergence of organized structure in co-culture spheroids: Experiments and Theory

NASA Astrophysics Data System (ADS)

Sanford, Roland; Kolbman, Dan; Song, Wei; Wu, Mingming; Ma, Minglin; Das, Moumita

During tissue morphogenesis, from formation of embryos to tumor progression, cells often live and migrate in a heterogeneous environment consisting of many types of cells. To understand how differences in cell mechanobiological properties impact cellular self-organization and migration, we study a co-culture model composed of two distinct cell types confined in a three-dimensional spherical capsule. The cells are modeled as deformable, interacting, self-propelled particles that proliferate at specified timescales. A disordered potential is introduced to mimic the effect of the extracellular matrix (ECM). By varying the mechano-adhesive properties of each type, we investigate how differences in cell stiffness, cell-cell adhesion, and cell-ECM interaction influence collective properties of the binary cell population, such as self-assembly and migration. The predictions of the model are compared to experimental results on co-cutures of breast cancer cells and non-tumorigenic breast epithelial cells. This work was partially supported by a Cottrell College Science Award from the Research Corporation for Science Advancement.

Human Perivascular Stem Cell-Based Bone Graft Substitute Induces Rat Spinal Fusion

PubMed Central

Chung, Choon G.; James, Aaron W.; Asatrian, Greg; Chang, Le; Nguyen, Alan; Le, Khoi; Bayani, Georgina; Lee, Robert; Stoker, David; Zhang, Xinli

2014-01-01

Adipose tissue is an attractive source of mesenchymal stem cells (MSCs) because of its abundance and accessibility. We have previously defined a population of native MSCs termed perivascular stem cells (PSCs), purified from diverse human tissues, including adipose tissue. Human PSCs (hPSCs) are a bipartite cell population composed of pericytes (CD146+CD34−CD45−) and adventitial cells (CD146−CD34+CD45−), isolated by fluorescence-activated cell sorting and with properties identical to those of culture identified MSCs. Our previous studies showed that hPSCs exhibit improved bone formation compared with a sample-matched unpurified population (termed stromal vascular fraction); however, it is not known whether hPSCs would be efficacious in a spinal fusion model. To investigate, we evaluated the osteogenic potential of freshly sorted hPSCs without culture expansion and differentiation in a rat model of posterolateral lumbar spinal fusion. We compared increasing dosages of implanted hPSCs to assess for dose-dependent efficacy. All hPSC treatment groups induced successful spinal fusion, assessed by manual palpation and microcomputed tomography. Computerized biomechanical simulation (finite element analysis) further demonstrated bone fusion with hPSC treatment. Histological analyses showed robust endochondral ossification in hPSC-treated samples. Finally, we confirmed that implanted hPSCs indeed differentiated into osteoblasts and osteocytes; however, the majority of the new bone formation was of host origin. These results suggest that implanted hPSCs positively regulate bone formation via direct and paracrine mechanisms. In summary, hPSCs are a readily available MSC population that effectively forms bone without requirements for culture or predifferentiation. Thus, hPSC-based products show promise for future efforts in clinical bone regeneration and repair. PMID:25154782

A Review of the Literature: Use of the Health Belief Model in Sickle Cell Research

ERIC Educational Resources Information Center

Mayo-Gamble, Tilicia L.

2014-01-01

Individuals with sickle cell disease experience a life-time of morbidity as well as a decreased lifespan. Since African Americans are disproportionately affected by the disease, sickle cell contributes to growing health disparities within this population. Thus, addressing issues related to the disease presents an increased need for health…

Human pluripotent stem cells on artificial microenvironments: a high content perspective

PubMed Central

Viswanathan, Priyalakshmi; Gaskell, Terri; Moens, Nathalie; Culley, Oliver J.; Hansen, Darrick; Gervasio, Mia K. R.; Yeap, Yee J.; Danovi, Davide

2014-01-01

Self-renewing stem cell populations are increasingly considered as resources for cell therapy and tools for drug discovery. Human pluripotent stem (hPS) cells in particular offer a virtually unlimited reservoir of homogeneous cells and can be differentiated toward diverse lineages. Many diseases show impairment in self-renewal or differentiation, abnormal lineage choice or other aberrant cell behavior in response to chemical or physical cues. To investigate these responses, there is a growing interest in the development of specific assays using hPS cells, artificial microenvironments and high content analysis. Several hurdles need to be overcome that can be grouped into three areas: (i) availability of robust, homogeneous, and consistent cell populations as a starting point; (ii) appropriate understanding and use of chemical and physical microenvironments; (iii) development of assays that dissect the complexity of cell populations in tissues while mirroring specific aspects of their behavior. Here we review recent progress in the culture of hPS cells and we detail the importance of the environment surrounding the cells with a focus on synthetic material and suitable high content analysis approaches. The technologies described, if properly combined, have the potential to create a paradigm shift in the way diseases are modeled and drug discovery is performed. PMID:25071572

Protocol for Isolation of Primary Human Hepatocytes and Corresponding Major Populations of Non-parenchymal Liver Cells

PubMed Central

Pfeiffer, Elisa; Zeilinger, Katrin; Seehofer, Daniel; Damm, Georg

2016-01-01

Beside parenchymal hepatocytes, the liver consists of non-parenchymal cells (NPC) namely Kupffer cells (KC), liver endothelial cells (LEC) and hepatic Stellate cells (HSC). Two-dimensional (2D) culture of primary human hepatocyte (PHH) is still considered as the "gold standard" for in vitro testing of drug metabolism and hepatotoxicity. It is well-known that the 2D monoculture of PHH suffers from dedifferentiation and loss of function. Recently it was shown that hepatic NPC play a central role in liver (patho-) physiology and the maintenance of PHH functions. Current research focuses on the reconstruction of in vivo tissue architecture by 3D- and co-culture models to overcome the limitations of 2D monocultures. Previously we published a method to isolate human liver cells and investigated the suitability of these cells for their use in cell cultures in Experimental Biology and Medicine1. Based on the broad interest in this technique the aim of this article was to provide a more detailed protocol for the liver cell isolation process including a video, which will allow an easy reproduction of this technique. Human liver cells were isolated from human liver tissue samples of surgical interventions by a two-step EGTA/collagenase P perfusion technique. PHH were separated from the NPC by an initial centrifugation at 50 x g. Density gradient centrifugation steps were used for removal of dead cells. Individual liver cell populations were isolated from the enriched NPC fraction using specific cell properties and cell sorting procedures. Beside the PHH isolation we were able to separate KC, LEC and HSC for further cultivation. Taken together, the presented protocol allows the isolation of PHH and NPC in high quality and quantity from one donor tissue sample. The access to purified liver cell populations could allow the creation of in vivo like human liver models. PMID:27077489

Protocol for Isolation of Primary Human Hepatocytes and Corresponding Major Populations of Non-parenchymal Liver Cells.

PubMed

Kegel, Victoria; Deharde, Daniela; Pfeiffer, Elisa; Zeilinger, Katrin; Seehofer, Daniel; Damm, Georg

2016-03-30

Beside parenchymal hepatocytes, the liver consists of non-parenchymal cells (NPC) namely Kupffer cells (KC), liver endothelial cells (LEC) and hepatic Stellate cells (HSC). Two-dimensional (2D) culture of primary human hepatocyte (PHH) is still considered as the "gold standard" for in vitro testing of drug metabolism and hepatotoxicity. It is well-known that the 2D monoculture of PHH suffers from dedifferentiation and loss of function. Recently it was shown that hepatic NPC play a central role in liver (patho-) physiology and the maintenance of PHH functions. Current research focuses on the reconstruction of in vivo tissue architecture by 3D- and co-culture models to overcome the limitations of 2D monocultures. Previously we published a method to isolate human liver cells and investigated the suitability of these cells for their use in cell cultures in Experimental Biology and Medicine(1). Based on the broad interest in this technique the aim of this article was to provide a more detailed protocol for the liver cell isolation process including a video, which will allow an easy reproduction of this technique. Human liver cells were isolated from human liver tissue samples of surgical interventions by a two-step EGTA/collagenase P perfusion technique. PHH were separated from the NPC by an initial centrifugation at 50 x g. Density gradient centrifugation steps were used for removal of dead cells. Individual liver cell populations were isolated from the enriched NPC fraction using specific cell properties and cell sorting procedures. Beside the PHH isolation we were able to separate KC, LEC and HSC for further cultivation. Taken together, the presented protocol allows the isolation of PHH and NPC in high quality and quantity from one donor tissue sample. The access to purified liver cell populations could allow the creation of in vivo like human liver models.

Population pharmacokinetics of hydroxyurea for children and adolescents with sickle cell disease.

PubMed

Wiczling, Paweł; Liem, Robert I; Panepinto, Julie A; Garg, Uttam; Abdel-Rahman, Susan M; Kearns, Gregory L; Neville, Kathleen A

2014-09-01

The objective of this study was to develop a population pharmacokinetic (PK) model sufficient to describe hydroxyurea (HU) concentrations in serum and urine following oral drug administration in pediatric patients with sickle cell disease. Additionally, the measured hydroxyurea concentrations for particular sampling time were correlated with exposure measures (AUC) to find the most predictive relationship. Hydroxyurea concentrations were determined in 21 subjects. Using a population nonlinear mixed-effect modeling, the HU PK was best described by a one-compartment model with two elimination pathways (metabolic and renal) and a transit compartment absorption. The typical mean absorption time was 0.222 hour. The typical apparent volume of distribution was 21.8 L and the apparent systemic clearance was 6.88 L/h for an average weight patient of 30.7 kg. The 50% of the HU dose was renally excreted. Linear correlations were apparent between the plasma HU concentration at 1, 1.5, 2, 4, and 6 hours post-dose and AUC with the most significant (R(2)  = 0.71) observed at 1.5 hours. A population PK model was successful in describing HU disposition in plasma and urine. Data from the model also demonstrated that HU plasma concentrations at 1.5 hours after an oral dose of the drug were highly predictive of systemic drug exposure. © 2014, The American College of Clinical Pharmacology.

Cell size control and homeostasis in bacteria

NASA Astrophysics Data System (ADS)

Bradde, Serena; Taheri, Sattar; Sauls, John; Hill, Nobert; Levine, Petra; Paulsson, Johan; Vergassola, Massimo; Jun, Suckjoon

2015-03-01

How cells control their size is a fundamental question in biology. The mechanisms for sensing size, time, or a combination of the two are not supported by experimental evidence. By analysing distributions of size at division at birth and generation time of hundreds of thousands of Gram-negative E. coli and Gram-positive B. subtilis cells under a wide range of tightly controlled steady-state growth conditions, we are now in the position to validate different theoretical models. In this talk I will present all possible models in details and present a general mechanism that quantitatively explains all measurable aspects of growth and cell division at both population and single-cell levels.

Adaptive non-linear control for cancer therapy through a Fokker-Planck observer.

PubMed

Shakeri, Ehsan; Latif-Shabgahi, Gholamreza; Esmaeili Abharian, Amir

2018-04-01

In recent years, many efforts have been made to present optimal strategies for cancer therapy through the mathematical modelling of tumour-cell population dynamics and optimal control theory. In many cases, therapy effect is included in the drift term of the stochastic Gompertz model. By fitting the model with empirical data, the parameters of therapy function are estimated. The reported research works have not presented any algorithm to determine the optimal parameters of therapy function. In this study, a logarithmic therapy function is entered in the drift term of the Gompertz model. Using the proposed control algorithm, the therapy function parameters are predicted and adaptively adjusted. To control the growth of tumour-cell population, its moments must be manipulated. This study employs the probability density function (PDF) control approach because of its ability to control all the process moments. A Fokker-Planck-based non-linear stochastic observer will be used to determine the PDF of the process. A cost function based on the difference between a predefined desired PDF and PDF of tumour-cell population is defined. Using the proposed algorithm, the therapy function parameters are adjusted in such a manner that the cost function is minimised. The existence of an optimal therapy function is also proved. The numerical results are finally given to demonstrate the effectiveness of the proposed method.

Hepatic Oval Cells Have the Side Population Phenotype Defined by Expression of ATP-Binding Cassette Transporter ABCG2/BCRP1

PubMed Central

Shimano, Koichi; Satake, Makoto; Okaya, Atsuhito; Kitanaka, Junichi; Kitanaka, Nobue; Takemura, Motohiko; Sakagami, Masafumi; Terada, Nobuyuki; Tsujimura, Tohru

2003-01-01

Organ-specific stem cells can be identified by the side population (SP) phenotype, which is defined by the property to effectively exclude the Hoechst 33342 dye. The ATP-binding cassette transporter ABCG2/BCRP1 mediates the SP phenotype. Because hepatic oval cells possess several characteristics of stem cells, we examined whether they have the SP phenotype using the 2-acetylaminofluorene/partial hepatectomy (PH) model. Fluorescence-activated cell sorting analysis showed that a population of non-parenchymal cells containing oval cells, prepared on day 7 after PH, carried a significant number of SP cells, whereas that of non-parenchymal cells without oval cells, prepared on day 0 after PH, did not. Northern blot analysis using total liver RNA obtained on various days after PH showed that the expression of ABCG2/BCRP1 mRNA increased after PH, reaching the highest level on day 7, and then gradually decreased. This pattern of changes in the ABCG2/BCRP1 mRNA level was well correlated to that in the number of oval cells. Furthermore, in situ hybridization revealed that oval cells were the sites of expression of ABCG2/BCRP1 mRNA. These results indicate that oval cells have the SP phenotype defined by expression of ABCG2/BCRP1, suggesting that oval cells may represent stem cells in the liver. PMID:12819005

A Population of Progenitor Cells in the Basal and Intermediate Layers of the Murine Bladder Urothelium Contributes to Urothelial Development and Regeneration

PubMed Central

Colopy, Sara A.; Bjorling, Dale E.; Mulligan, William A.; Bushman, Wade

2014-01-01

Background Homeostatic maintenance and repair of the bladder urothelium has been attributed to proliferation of keratin 5-expressing basal cells (K5-BC) with subsequent differentiation into superficial cells. Recent evidence, however, suggests that the intermediate cell layer harbors a population of progenitor cells. We use label-retaining cell (LRC) methodology in conjunction with a clinically relevant model of uropathogenic Escherichia coli (UPEC)-induced injury to characterize urothelial ontogeny during development and in response to diffuse urothelial injury. Results In the developing urothelium, proliferating cells were dispersed throughout the K5-BC and intermediate cells layers, becoming progressively concentrated in the K5-BC layer with age. When 5-bromo-2-deoxyuridine (BrdU) was administered during urothelial development, LRCs in the adult were found within the K5-BC, intermediate, and superficial cell layers, the location dependent upon time of labeling. UPEC inoculation resulted in loss of the superficial cell layer followed by robust proliferation of K5-BCs and intermediate cells. LRCs within the K5-BC and intermediate cell layers proliferated in response to injury. Conclusions Urothelial development and regeneration following injury relies on proliferation of K5-BC and intermediate cells. The existence and proliferation of LRCs within both the K5-BC and intermediate cell layers suggests the presence of two populations of urothelial progenitor cells. PMID:24796293

Modeling activity and target-dependent developmental cell death of mouse retinal ganglion cells ex vivo.

PubMed

Voyatzis, Sylvie; Muzerelle, Aude; Gaspar, Patricia; Nicol, Xavier

2012-01-01

Programmed cell death is widespread during the development of the central nervous system and serves multiple purposes including the establishment of neural connections. In the mouse retina a substantial reduction of retinal ganglion cells (RGCs) occurs during the first postnatal week, coinciding with the formation of retinotopic maps in the superior colliculus (SC). We previously established a retino-collicular culture preparation which recapitulates the progressive topographic ordering of RGC projections during early post-natal life. Here, we questioned whether this model could also be suitable to examine the mechanisms underlying developmental cell death of RGCs. Brn3a was used as a marker of the RGCs. A developmental decline in the number of Brn3a-immunolabelled neurons was found in the retinal explant with a timing that paralleled that observed in vivo. In contrast, the density of photoreceptors or of starburst amacrine cells increased, mimicking the evolution of these cell populations in vivo. Blockade of neural activity with tetrodotoxin increased the number of surviving Brn3a-labelled neurons in the retinal explant, as did the increase in target availability when one retinal explant was confronted with 2 or 4 collicular slices. Thus, this ex vivo model reproduces the developmental reduction of RGCs and recapitulates its regulation by neural activity and target availability. It therefore offers a simple way to analyze developmental cell death in this classic system. Using this model, we show that ephrin-A signaling does not participate to the regulation of the Brn3a population size in the retina, indicating that eprhin-A-mediated elimination of exuberant projections does not involve developmental cell death.

Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics

PubMed Central

Lythgoe, Katrina A.; Blanquart, François

2016-01-01

The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical, and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body’s viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load (SPVL) observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation. PMID:27706164

Modelling and finite-time stability analysis of psoriasis pathogenesis

NASA Astrophysics Data System (ADS)

Oza, Harshal B.; Pandey, Rakesh; Roper, Daniel; Al-Nuaimi, Yusur; Spurgeon, Sarah K.; Goodfellow, Marc

2017-08-01

A new systems model of psoriasis is presented and analysed from the perspective of control theory. Cytokines are treated as actuators to the plant model that govern the cell population under the reasonable assumption that cytokine dynamics are faster than the cell population dynamics. The analysis of various equilibria is undertaken based on singular perturbation theory. Finite-time stability and stabilisation have been studied in various engineering applications where the principal paradigm uses non-Lipschitz functions of the states. A comprehensive study of the finite-time stability properties of the proposed psoriasis dynamics is carried out. It is demonstrated that the dynamics are finite-time convergent to certain equilibrium points rather than asymptotically or exponentially convergent. This feature of finite-time convergence motivates the development of a modified version of the Michaelis-Menten function, frequently used in biology. This framework is used to model cytokines as fast finite-time actuators.

Axonal properties determine somatic firing in a model of in vitro CA1 hippocampal sharp wave/ripples and persistent gamma oscillations

PubMed Central

Traub, Roger D.; Schmitz, Dietmar; Maier, Nikolaus; Whittington, Miles A.; Draguhn, Andreas

2012-01-01

Evidence has been presented that CA1 pyramidal cells, during spontaneous in vitro sharp wave/ripple (SPW-R) complexes, generate somatic action potentials that originate in axons. ‘Participating’ (somatically firing) pyramidal cells fire (almost always) at most once during a particular SPW-R whereas non-participating cells virtually never fire during an SPW-R. Somatic spikelets were small or absent, while ripple-frequency EPSCs and IPSCs occurred during the SPW-R in pyramidal neurons. These experimental findings could be replicated with a network model in which electrical coupling was present between small pyramidal cell axonal branches. Here, we explore this model in more depth. Factors that influence somatic participation include: (i) the diameter of axonal branches that contain coupling sites to other axons, because firing in larger branches injects more current into the main axon, increasing antidromic firing probability; (ii) axonal K+ currents; and (iii) somatic hyperpolarization and shunting. We predict that portions of axons fire at high frequency during SPW-R, while somata fire much less. In the model, somatic firing can occur by occasional generation of full action potentials in proximal axonal branches, which are excited by high-frequency spikelets. When the network contains phasic synaptic inhibition, at the axonal gap junction site, gamma oscillations result, again with more frequent axonal firing than somatic firing. Combining the models, so as to generate gamma followed by sharp waves, leads to strong overlap between the population of cells firing during gamma the population of cells firing during a subsequent sharp wave, as observed in vivo. PMID:22697272

In vitro and in vivo approaches to study osteocyte biology.

PubMed

Kalajzic, Ivo; Matthews, Brya G; Torreggiani, Elena; Harris, Marie A; Divieti Pajevic, Paola; Harris, Stephen E

2013-06-01

Osteocytes, the most abundant cell population of the bone lineage, have been a major focus in the bone research field in recent years. This population of cells that resides within mineralized matrix is now thought to be the mechanosensory cell in bone and plays major roles in the regulation of bone formation and resorption. Studies of osteocytes had been impaired by their location, resulting in numerous attempts to isolate primary osteocytes and to generate cell lines representative of the osteocytic phenotype. Progress has been achieved in recent years by utilizing in vivo genetic technology and generation of osteocyte directed transgenic and gene deficiency mouse models. We will provide an overview of the current in vitro and in vivo models utilized to study osteocyte biology. We discuss generation of osteocyte-like cell lines and isolation of primary osteocytes and summarize studies that have utilized these cellular models to understand the functional role of osteocytes. Approaches that attempt to selectively identify and isolate osteocytes using fluorescent protein reporters driven by regulatory elements of genes that are highly expressed in osteocytes will be discussed. In addition, recent in vivo studies utilizing overexpression or conditional deletion of various genes using dentin matrix protein (Dmp1) directed Cre recombinase are outlined. In conclusion, evaluation of the benefits and deficiencies of currently used cell lines/genetic models in understanding osteocyte biology underlines the current progress in this field. The future efforts will be directed towards developing novel in vitro and in vivo models that would additionally facilitate in understanding the multiple roles of osteocytes. Copyright © 2012 Elsevier Inc. All rights reserved.

Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment

PubMed Central

Lorz, Alexander; Botesteanu, Dana-Adriana; Levy, Doron

2017-01-01

Investigating the role of intrinsic cell heterogeneity emerging from variations in cell-cycle parameters and apoptosis is a crucial step toward better informing drug administration. Antimitotic agents, widely used in chemotherapy, target exclusively proliferative cells and commonly induce a prolonged mitotic arrest followed by cell death via apoptosis. In this paper, we developed a physiologically motivated mathematical framework for describing cancer cell growth dynamics that incorporates the intrinsic heterogeneity in the time individual cells spend in the cell-cycle and apoptosis process. More precisely, our model comprises two age-structured partial differential equations for the proliferative and apoptotic cell compartments and one ordinary differential equation for the quiescent compartment. To reflect the intrinsic cell heterogeneity that governs the growth dynamics, proliferative and apoptotic cells are structured in “age,” i.e., the amount of time remaining to be spent in each respective compartment. In our model, we considered an antimitotic drug whose effect on the cellular dynamics is to induce mitotic arrest, extending the average cell-cycle length. The prolonged mitotic arrest induced by the drug can trigger apoptosis if the time a cell will spend in the cell cycle is greater than the mitotic arrest threshold. We studied the drug’s effect on the long-term cancer cell growth dynamics using different durations of prolonged mitotic arrest induced by the drug. Our numerical simulations suggest that at confluence and in the absence of the drug, quiescence is the long-term asymptotic behavior emerging from the cancer cell growth dynamics. This pattern is maintained in the presence of small increases in the average cell-cycle length. However, intermediate increases in cell-cycle length markedly decrease the total number of cells and can drive the cancer population to extinction. Intriguingly, a large “switch-on/switch-off” increase in the average cell-cycle length maintains an active cell population in the long term, with oscillating numbers of proliferative cells and a relatively constant quiescent cell number. PMID:28913178

Epidermal Homeostasis and Radiation Responses in a Multiscale Tissue Modeling Framework

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Cucinotta, Francis A.

2013-01-01

The surface of skin is lined with several thin layers of epithelial cells that are maintained throughout life time by a small population of stem cells. High dose radiation exposures could injure and deplete the underlying proliferative cells and induce cutaneous radiation syndrome. In this work we propose a multiscale computational model for skin epidermal dynamics that links phenomena occurring at the subcellular, cellular, and tissue levels of organization, to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis. Incorporating experimentally measured histological and cell kinetic parameters, we obtain results of population kinetics and proliferation indexes comparable to observations in unirradiated and acutely irradiated swine experiments. At the sub-cellular level, several recently published Wnt signaling controlled cell-cycle models are applied and the roles of key components and parameters are analyzed. Based on our simulation results, we demonstrate that a moderate increase of proliferation rate for the survival proliferative cells is sufficient to fully repopulate the area denuded by high dose radiation, as long as the integrity of underlying basement membrane is maintained. Our work highlights the importance of considering proliferation kinetics as well as the spatial organization of tissues when conducting in vivo investigations of radiation responses. This integrated model allow us to test the validity of several basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and enhance our understanding of the pathophysiological effects of ionizing radiation on skin.

A multiphase model for chemically- and mechanically- induced cell differentiation in a hollow fibre membrane bioreactor: minimising growth factor consumption.

PubMed

Pearson, Natalie C; Oliver, James M; Shipley, Rebecca J; Waters, Sarah L

2016-06-01

We present a simplified two-dimensional model of fluid flow, solute transport, and cell distribution in a hollow fibre membrane bioreactor. We consider two cell populations, one undifferentiated and one differentiated, with differentiation stimulated either by growth factor alone, or by both growth factor and fluid shear stress. Two experimental configurations are considered, a 3-layer model in which the cells are seeded in a scaffold throughout the extracapillary space (ECS), and a 4-layer model in which the cell-scaffold construct occupies a layer surrounding the outside of the hollow fibre, only partially filling the ECS. Above this is a region of free-flowing fluid, referred to as the upper fluid layer. Following previous models by the authors (Pearson et al. in Math Med Biol, 2013, Biomech Model Mechanbiol 1-16, 2014a, we employ porous mixture theory to model the dynamics of, and interactions between, the cells, scaffold, and fluid in the cell-scaffold construct. We use this model to determine operating conditions (experiment end time, growth factor inlet concentration, and inlet fluid fluxes) which result in a required percentage of differentiated cells, as well as maximising the differentiated cell yield and minimising the consumption of expensive growth factor.

Neutrophils Are Central to Antibody-Mediated Protection against Genital Chlamydia.

PubMed

Naglak, Elizabeth K; Morrison, Sandra G; Morrison, Richard P

2017-10-01

Determining the effector populations involved in humoral protection against genital chlamydia infection is crucial to development of an effective chlamydial vaccine. Antibody has been implicated in protection studies in multiple animal models, and we previously showed that the passive transfer of immune serum alone does not confer immunity in the mouse. Using the Chlamydia muridarum model of genital infection, we demonstrate a protective role for both Chlamydia -specific immunoglobulin G (IgG) and polymorphonuclear neutrophils and show the importance of an antibody/effector cell interaction in mediating humoral immunity. While neutrophils were found to contribute significantly to antibody-mediated protection in vivo , natural killer (NK) cells were dispensable for protective immunity. Furthermore, gamma interferon (IFN-γ)-stimulated primary peritoneal neutrophils (PPNs) killed chlamydiae in vitro in an antibody-dependent manner. The results from this study support the view that an IFN-γ-activated effector cell population cooperates with antibody to protect against genital chlamydia and establish neutrophils as a key effector cell in this response. Copyright © 2017 Naglak et al.

Accounting for randomness in measurement and sampling in studying cancer cell population dynamics.

PubMed

Ghavami, Siavash; Wolkenhauer, Olaf; Lahouti, Farshad; Ullah, Mukhtar; Linnebacher, Michael

2014-10-01

Knowing the expected temporal evolution of the proportion of different cell types in sample tissues gives an indication about the progression of the disease and its possible response to drugs. Such systems have been modelled using Markov processes. We here consider an experimentally realistic scenario in which transition probabilities are estimated from noisy cell population size measurements. Using aggregated data of FACS measurements, we develop MMSE and ML estimators and formulate two problems to find the minimum number of required samples and measurements to guarantee the accuracy of predicted population sizes. Our numerical results show that the convergence mechanism of transition probabilities and steady states differ widely from the real values if one uses the standard deterministic approach for noisy measurements. This provides support for our argument that for the analysis of FACS data one should consider the observed state as a random variable. The second problem we address is about the consequences of estimating the probability of a cell being in a particular state from measurements of small population of cells. We show how the uncertainty arising from small sample sizes can be captured by a distribution for the state probability.

Evidence for deterministic chaos in aperiodic oscillations of acute lymphoblastic leukemia cells in long-term culture

NASA Astrophysics Data System (ADS)

Lambrou, George I.; Chatziioannou, Aristotelis; Vlahopoulos, Spiros; Moschovi, Maria; Chrousos, George P.

Biological systems are dynamic and possess properties that depend on two key elements: initial conditions and the response of the system over time. Conceptualizing this on tumor models will influence conclusions drawn with regard to disease initiation and progression. Alterations in initial conditions dynamically reshape the properties of proliferating tumor cells. The present work aims to test the hypothesis of Wolfrom et al., that proliferation shows evidence for deterministic chaos in a manner such that subtle differences in the initial conditions give rise to non-linear response behavior of the system. Their hypothesis, tested on adherent Fao rat hepatoma cells, provides evidence that these cells manifest aperiodic oscillations in their proliferation rate. We have tested this hypothesis with some modifications to the proposed experimental setup. We have used the acute lymphoblastic leukemia cell line CCRF-CEM, as it provides an excellent substrate for modeling proliferation dynamics. Measurements were taken at time points varying from 24h to 48h, extending the assayed populations beyond that of previous published reports that dealt with the complex dynamic behavior of animal cell populations. We conducted flow cytometry studies to examine the apoptotic and necrotic rate of the system, as well as DNA content changes of the cells over time. The cells exhibited a proliferation rate of nonlinear nature, as this rate presented oscillatory behavior. The obtained data have been fit in known models of growth, such as logistic and Gompertzian growth.

Comprehensive Analysis of the Activation and Proliferation Kinetics and Effector Functions of Human Lymphocytes, and Antigen Presentation Capacity of Antigen-Presenting Cells in Xenogeneic Graft-Versus-Host Disease.

PubMed

Kawasaki, Yasufumi; Sato, Kazuya; Hayakawa, Hiroko; Takayama, Norihito; Nakano, Hirofumi; Ito, Ryoji; Mashima, Kiyomi; Oh, Iekuni; Minakata, Daisuke; Yamasaki, Ryoko; Morita, Kaoru; Ashizawa, Masahiro; Yamamoto, Chihiro; Hatano, Kaoru; Fujiwara, Shin-Ichiro; Ohmine, Ken; Muroi, Kazuo; Kanda, Yoshinobu

2018-04-17

Xenogeneic graft-versus-host disease (GVHD) models in highly immunodeficient mice are currently being used worldwide to investigate human immune responses against foreign antigens in vivo. However, the individual roles of CD4 + and CD8 + T cells, and donor/host hematopoietic and nonhematopoietic antigen-presenting cells (APCs) in the induction and development of GVHD have not been fully investigated. In the present study, we comprehensively investigated the immune responses of human T cells and the antigen presentation capacity of donor/host hematopoietic and nonhematopoietic APCs in xenogeneic GVHD models using nonobese diabetic/Shi-scid-IL2rg null mice. CD4 + T cells and, to a lesser extent, CD8 + T cells individually mediated potentially lethal GVHD. In addition to inflammatory cytokine production, CD4 + T cells also supported the activation and proliferation of CD8 + T cells. Using bone marrow chimeras, we demonstrated that host hematopoietic, but not nonhematopoietic, APCs play a critical role in the development of CD4 + T cell-mediated GVHD. During early GVHD, we detected 2 distinct populations in memory CD4 + T cells. One population was highly activated and proliferated in major histocompatibility complex antigen (MHC) +/+ mice but not in MHC -/- mice, indicating alloreactive T cells. The other population showed a less activated and slowly proliferative status regardless of host MHC expression, and was associated with higher susceptibility to apoptosis, indicating nonalloreactive T cells in homeostasis-driven proliferation. These observations are clinically relevant to donor T cell response after allogeneic hematopoietic stem cell transplantation. Our findings provide a better understanding of the immunobiology of humanized mice and support the development of novel options for the prevention and treatment for GVHD. Copyright © 2018. Published by Elsevier Inc.

The transition between immune and disease states in a cellular automaton model of clonal immune response

NASA Astrophysics Data System (ADS)

Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.

1997-02-01

In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infections virus and killer T cells (cellular response). The model represents molecules and cells with bitstrings. The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connected to spatial extension is lost, as is the oscillating feature. Thus the mean field approximation introduced with coupled maps destroys oscillations.

Kinetic modeling of multi-feed simultaneous saccharification and co-fermentation of pretreated birch to ethanol.

PubMed

Wang, Ruifei; Koppram, Rakesh; Olsson, Lisbeth; Franzén, Carl Johan

2014-11-01

Fed-batch simultaneous saccharification and fermentation (SSF) is a feasible option for bioethanol production from lignocellulosic raw materials at high substrate concentrations. In this work, a segregated kinetic model was developed for simulation of fed-batch simultaneous saccharification and co-fermentation (SSCF) of steam-pretreated birch, using substrate, enzymes and cell feeds. The model takes into account the dynamics of the cellulase-cellulose system and the cell population during SSCF, and the effects of pre-cultivation of yeast cells on fermentation performance. The model was cross-validated against experiments using different feed schemes. It could predict fermentation performance and explain observed differences between measured total yeast cells and dividing cells very well. The reproducibility of the experiments and the cell viability were significantly better in fed-batch than in batch SSCF at 15% and 20% total WIS contents. The model can be used for simulation of fed-batch SSCF and optimization of feed profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Human Oral Mucosa and Gingiva

PubMed Central

Zhang, Q.Z.; Nguyen, A.L.; Yu, W.H.; Le, A.D.

2012-01-01

Mesenchymal stem cells (MSCs) represent a heterogeneous population of progenitor cells with self-renewal and multipotent differentiation potential. Aside from their regenerative role, extensive in vitro and in vivo studies have demonstrated that MSCs are capable of potent immunomodulatory effects on a variety of innate and adaptive immune cells. In this article, we will review recent experimental studies on the characterization of a unique population of MSCs derived from human oral mucosa and gingiva, especially their immunomodulatory and anti-inflammatory functions and their application in the treatment of several in vivo models of inflammatory diseases. The ease of isolation, accessible tissue source, and rapid ex vivo expansion, with maintenance of stable stem-cell-like phenotypes, render oral mucosa- and gingiva-derived MSCs a promising alternative cell source for MSC-based therapies. PMID:22988012

Human Induced Pluripotent Stem Cell-Derived Cardiac Progenitor Cells in Phenotypic Screening: A Transforming Growth Factor-β Type 1 Receptor Kinase Inhibitor Induces Efficient Cardiac Differentiation.

PubMed

Drowley, Lauren; Koonce, Chad; Peel, Samantha; Jonebring, Anna; Plowright, Alleyn T; Kattman, Steven J; Andersson, Henrik; Anson, Blake; Swanson, Bradley J; Wang, Qing-Dong; Brolen, Gabriella

2016-02-01

Several progenitor cell populations have been reported to exist in hearts that play a role in cardiac turnover and/or repair. Despite the presence of cardiac stem and progenitor cells within the myocardium, functional repair of the heart after injury is inadequate. Identification of the signaling pathways involved in the expansion and differentiation of cardiac progenitor cells (CPCs) will broaden insight into the fundamental mechanisms playing a role in cardiac homeostasis and disease and might provide strategies for in vivo regenerative therapies. To understand and exploit cardiac ontogeny for drug discovery efforts, we developed an in vitro human induced pluripotent stem cell-derived CPC model system using a highly enriched population of KDR(pos)/CKIT(neg)/NKX2.5(pos) CPCs. Using this model system, these CPCs were capable of generating highly enriched cultures of cardiomyocytes under directed differentiation conditions. In order to facilitate the identification of pathways and targets involved in proliferation and differentiation of resident CPCs, we developed phenotypic screening assays. Screening paradigms for therapeutic applications require a robust, scalable, and consistent methodology. In the present study, we have demonstrated the suitability of these cells for medium to high-throughput screens to assess both proliferation and multilineage differentiation. Using this CPC model system and a small directed compound set, we identified activin-like kinase 5 (transforming growth factor-β type 1 receptor kinase) inhibitors as novel and potent inducers of human CPC differentiation to cardiomyocytes. Significance: Cardiac disease is a leading cause of morbidity and mortality, with no treatment available that can result in functional repair. This study demonstrates how differentiation of induced pluripotent stem cells can be used to identify and isolate cell populations of interest that can translate to the adult human heart. Two separate examples of phenotypic screens are discussed, demonstrating the value of this biologically relevant and reproducible technology. In addition, this assay system was able to identify novel and potent inducers of differentiation and proliferation of induced pluripotent stem cell-derived cardiac progenitor cells. ©AlphaMed Press.

Cardiac Stem Cell Hybrids Enhance Myocardial Repair

PubMed Central

Quijada, Pearl; Salunga, Hazel T.; Hariharan, Nirmala; Cubillo, Jonathan D.; El-Sayed, Farid G.; Moshref, Maryam; Bala, Kristin M.; Emathinger, Jacqueline M.; La Torre, Andrea De; Ormachea, Lucia; Alvarez, Roberto; Gude, Natalie A.; Sussman, Mark A.

2015-01-01

Rationale Dual cell transplantation of cardiac progenitor cells (CPCs) and mesenchymal stem cells (MSCs) after infarction improves myocardial repair and performance in large animal models relative to delivery of either cell population. Objective To demonstrate that CardioChimeras (CCs) formed by fusion between CPCs and MSCs have enhanced reparative potential in a mouse model of myocardial infarction relative to individual stem cells or combined cell delivery. Methods and Results Two distinct and clonally derived CCs, CC1 and CC2 were utilized for this study. CCs improved left ventricular anterior wall thickness (AWT) at 4 weeks post injury, but only CC1 treatment preserved AWT at 18 weeks. Ejection fraction was enhanced at 6 weeks in CCs, and functional improvements were maintained in CCs and CPC + MSC groups at 18 weeks. Infarct size was decreased in CCs, whereas CPC + MSC and CPC parent groups remained unchanged at 12 weeks. CCs exhibited increased persistence, engraftment, and expression of early commitment markers within the border zone relative to combinatorial and individual cell population-injected groups. CCs increased capillary density and preserved cardiomyocyte size in the infarcted regions suggesting CCs role in protective paracrine secretion. Conclusions CCs merge the application of distinct cells into a single entity for cellular therapeutic intervention in the progression of heart failure. CCs are a novel cell therapy that improves upon combinatorial cell approaches to support myocardial regeneration. PMID:26228030

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Domanskyi, Sergii; Schilling, Joshua E.; Privman, Vladimir, E-mail: privman@clarkson.edu

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model wemore » describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of “stiff” equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.« less

HDAC inhibitors: modulating leukocyte differentiation, survival, proliferation and inflammation.

PubMed

Sweet, Matthew J; Shakespear, Melanie R; Kamal, Nabilah A; Fairlie, David P

2012-01-01

Therapeutic effects of histone deacetylase (HDAC) inhibitors in cancer models were first linked to their ability to cause growth arrest and apoptosis of tumor cells. It is now clear that these agents also have pleiotropic effects on angiogenesis and the immune system, and some of these properties are likely to contribute to their anti-cancer activities. It is also emerging that inhibitors of specific HDACs affect the differentiation, survival and/or proliferation of distinct immune cell populations. This is true for innate immune cells such as macrophages, as well as cells of the acquired immune system, for example, T-regulatory cells. These effects may contribute to therapeutic profiles in some autoimmune and chronic inflammatory disease models. Here, we review our current understanding of how classical HDACs (HDACs 1-11) and their inhibitors impact on differentiation, survival and proliferation of distinct leukocyte populations, as well as the likely relevance of these effects to autoimmune and inflammatory disease processes. The ability of HDAC inhibitors to modulate leukocyte survival may have implications for the rationale of developing selective inhibitors as anti-inflammatory drugs.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

PubMed Central

Gerstner, Wulfram

2017-01-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50–2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations. PMID:28422957

Haemopoietic stem cells.

PubMed

Bellantuono, Ilaria

2004-04-01

Considerable effort has been made in recent years in understanding the mechanisms that govern stem cell generation, proliferation, self-renewal, commitment and lately plasticity. In the development of the haemopoietic system during embryonic and fetal life the notion of different pools of stem cells arising from the endothelium is gaining consensus. Gene expression profiling of populations of stem cells is bringing to light categories of genes important for self-renewal or commitment. Besides the role of transcription factors in lineage decision, the role of soluble factors and transmembrane proteins, very active at the time of embryo development, are taking central stage in the maintenance and in vitro expansion of haemopoietic stem cells (HSCs). The hierarchical model of haemopoietic development is being questioned with reports of lineage switching and plasticity of haemopoietic stem cells to non-haemopoietic cells. Yet the understanding of the overall process is still very fragmented and hypothetical. This is mainly due to the absence of appropriate markers to enable selection of homogeneous stem cell populations and the need to rely on retrospective functional assays, able only to determine the overall behaviour of a population of cells. This review is intended to be an overview of the haemopoietic system and a critical re-visitation of issues such as plasticity and self-renewal important for therapeutic applications of haemopoietic stem cells.

Identification of two novel glial-restricted cell populations in the embryonic telencephalon arising from unique origins

PubMed Central

Strathmann, Frederick G; Wang, Xi; Mayer-Pröschel, Margot

2007-01-01

Background Considerably less attention has been given to understanding the cellular components of gliogenesis in the telencephalon when compared to neuronogenesis, despite the necessity of normal glial cell formation for neurological function. Early proposals of exclusive ventral oligodendrocyte precursor cell (OPC) generation have been challenged recently with studies revealing the potential of the dorsal telencephalon to also generate oligodendrocytes. The identification of OPCs generated from multiple regions of the developing telencephalon, together with the need of the embryonic telencephalon to provide precursor cells for oligodendrocytes as well as astrocytes in ventral and dorsal areas, raises questions concerning the identity of the precursor cell populations capable of generating macroglial subtypes during multiple developmental windows and in differing locations. Results We have identified progenitor populations in the ventral and dorsal telencephalon restricted to the generation of astrocytes and oligodendrocytes. We further demonstrate that the dorsal glial progenitor cells can be generated de novo from the dorsal telencephalon and we demonstrate their capacity for in vivo production of both myelin-forming oligodendrocytes and astrocytes upon transplantation. Conclusion Based on our results we offer a unifying model of telencephalic gliogenesis, with the generation of both oligodendrocytes and astrocytes from spatially separate, but functionally similar, glial restricted populations at different developmental times in the dorsal and ventral CNS. PMID:17439658

Macromolecular Crowding Regulates the Gene Expression Profile by Limiting Diffusion

DOE PAGES

Golkaram, Mahdi; Hellander, Stefan; Drawert, Brian; ...

2016-11-28

We seek to elucidate the role of macromolecular crowding in transcription and translation. It is well known that stochasticity in gene expression can lead to differential gene expression and heterogeneity in a cell population. Recent experimental observations by Tan et al. have improved our understanding of the functional role of macromolecular crowding. It can be inferred from their observations that macromolecular crowding can lead to robustness in gene expression, resulting in a more homogeneous cell population. We introduce a spatial stochastic model to provide insight into this process. Our results show that macromolecular crowding reduces noise (as measured by themore » kurtosis of the mRNA distribution) in a cell population by limiting the diffusion of transcription factors (i.e. removing the unstable intermediate states), and that crowding by large molecules reduces noise more efficiently than crowding by small molecules. Finally, our simulation results provide evidence that the local variation in chromatin density as well as the total volume exclusion of the chromatin in the nucleus can induce a homogenous cell population« less

A primary cell model of HIV-1 latency that uses activation through the T cell receptor and return to quiescence to establish latent infection

PubMed Central

Kim, Michelle; Hosmane, Nina N.; Bullen, C. Korin; Capoferri, Adam; Yang, Hung-Chih; Siliciano, Janet D.; Siliciano, Robert F.

2015-01-01

A mechanistic understanding of HIV-1 latency depends upon a model system that recapitulates the in vivo condition of latently infected, resting CD4+ T lymphocytes. Latency appears to be established after activated CD4+ T cells, the principal targets of HIV-1 infection, become productively infected and survive long enough to return to a resting memory state in which viral expression is inhibited by changes in the cellular environment. This protocol describes an ex vivo primary cell system that is generated under conditions that reflect the in vivo establishment of latency. Creation of these latency model cells takes 12 weeks and, once established, the cells can be maintained and used for several months. The resulting cell population contains both uninfected and latently infected cells. This primary cell model can be used to perform drug screens, study CTL responses to HIV-1, compare viral alleles, or to expand the ex vivo lifespan of cells from HIV-1 infected individuals for extended study. PMID:25375990

Multidisciplinary approaches to understanding collective cell migration in developmental biology.

PubMed

Schumacher, Linus J; Kulesa, Paul M; McLennan, Rebecca; Baker, Ruth E; Maini, Philip K

2016-06-01

Mathematical models are becoming increasingly integrated with experimental efforts in the study of biological systems. Collective cell migration in developmental biology is a particularly fruitful application area for the development of theoretical models to predict the behaviour of complex multicellular systems with many interacting parts. In this context, mathematical models provide a tool to assess the consistency of experimental observations with testable mechanistic hypotheses. In this review, we showcase examples from recent years of multidisciplinary investigations of neural crest cell migration. The neural crest model system has been used to study how collective migration of cell populations is shaped by cell-cell interactions, cell-environmental interactions and heterogeneity between cells. The wide range of emergent behaviours exhibited by neural crest cells in different embryonal locations and in different organisms helps us chart out the spectrum of collective cell migration. At the same time, this diversity in migratory characteristics highlights the need to reconcile or unify the array of currently hypothesized mechanisms through the next generation of experimental data and generalized theoretical descriptions. © 2016 The Authors.

A two-scale model for correlation between B cell VDJ usage in zebrafish

NASA Astrophysics Data System (ADS)

Pan, Keyao; Deem, Michael

2011-03-01

The zebrafish (Danio rerio) is one of the model animals for study of immunology. The dynamics of the adaptive immune system in zebrafish is similar to that in higher animals. In this work, we built a two-scale model to simulate the dynamics of B cells in primary and secondary immune reactions in zebrafish and to explain the reported correlation between VDJ usage of B cell repertoires in distinct zebrafish. The first scale of the model consists of a generalized NK model to simulate the B cell maturation process in the 10-day primary immune response. The second scale uses a delay ordinary differential equation system to model the immune responses in the 6-month lifespan of zebrafish. The generalized NK model shows that mature B cells specific to one antigen mostly possess a single VDJ recombination. The probability that mature B cells in two zebrafish have the same VDJ recombination increases with the B cell population size or the B cell selection intensity and decreases with the B cell hypermutation rate. The ODE model shows a distribution of correlation in the VDJ usage of the B cell repertoires in two six-month-old zebrafish that is highly similar to that from experiment. This work presents a simple theory to explain the experimentally observed correlation in VDJ usage of distinct zebrafish B cell repertoires after an immune response.

Projection specificity in heterogeneous locus coeruleus cell populations: implications for learning and memory

PubMed Central

Uematsu, Akira; Tan, Bao Zhen

2015-01-01

Noradrenergic neurons in the locus coeruleus (LC) play a critical role in many functions including learning and memory. This relatively small population of cells sends widespread projections throughout the brain including to a number of regions such as the amygdala which is involved in emotional associative learning and the medial prefrontal cortex which is important for facilitating flexibility when learning rules change. LC noradrenergic cells participate in both of these functions, but it is not clear how this small population of neurons modulates these partially distinct processes. Here we review anatomical, behavioral, and electrophysiological studies to assess how LC noradrenergic neurons regulate these different aspects of learning and memory. Previous work has demonstrated that subpopulations of LC noradrenergic cells innervate specific brain regions suggesting heterogeneity of function in LC neurons. Furthermore, noradrenaline in mPFC and amygdala has distinct effects on emotional learning and cognitive flexibility. Finally, neural recording data show that LC neurons respond during associative learning and when previously learned task contingencies change. Together, these studies suggest a working model in which distinct and potentially opposing subsets of LC neurons modulate particular learning functions through restricted efferent connectivity with amygdala or mPFC. This type of model may provide a general framework for understanding other neuromodulatory systems, which also exhibit cell type heterogeneity and projection specificity. PMID:26330494

Image-guided genomics of phenotypically heterogeneous populations reveals vascular signalling during symbiotic collective cancer invasion

PubMed Central

Konen, J.; Summerbell, E.; Dwivedi, B.; Galior, K.; Hou, Y.; Rusnak, L.; Chen, A.; Saltz, J.; Zhou, W.; Boise, L. H.; Vertino, P.; Cooper, L.; Salaita, K.; Kowalski, J.; Marcus, A. I.

2017-01-01

Phenotypic heterogeneity is widely observed in cancer cell populations. Here, to probe this heterogeneity, we developed an image-guided genomics technique termed spatiotemporal genomic and cellular analysis (SaGA) that allows for precise selection and amplification of living and rare cells. SaGA was used on collectively invading 3D cancer cell packs to create purified leader and follower cell lines. The leader cell cultures are phenotypically stable and highly invasive in contrast to follower cultures, which show phenotypic plasticity over time and minimally invade in a sheet-like pattern. Genomic and molecular interrogation reveals an atypical VEGF-based vasculogenesis signalling that facilitates recruitment of follower cells but not for leader cell motility itself, which instead utilizes focal adhesion kinase-fibronectin signalling. While leader cells provide an escape mechanism for followers, follower cells in turn provide leaders with increased growth and survival. These data support a symbiotic model of collective invasion where phenotypically distinct cell types cooperate to promote their escape. PMID:28497793

A clinical data validated mathematical model of prostate cancer growth under intermittent androgen suppression therapy

NASA Astrophysics Data System (ADS)

Portz, Travis; Kuang, Yang; Nagy, John D.

2012-03-01

Prostate cancer is commonly treated by a form of hormone therapy called androgen suppression. This form of treatment, while successful at reducing the cancer cell population, adversely affects quality of life and typically leads to a recurrence of the cancer in an androgen-independent form. Intermittent androgen suppression aims to alleviate some of these adverse affects by cycling the patient on and off treatment. Clinical studies have suggested that intermittent therapy is capable of maintaining androgen dependence over multiple treatment cycles while increasing quality of life during off-treatment periods. This paper presents a mathematical model of prostate cancer to study the dynamics of androgen suppression therapy and the production of prostate-specific antigen (PSA), a clinical marker for prostate cancer. Preliminary models were based on the assumption of an androgen-independent (AI) cell population with constant net growth rate. These models gave poor accuracy when fitting clinical data during simulation. The final model presented hypothesizes an AI population with increased sensitivity to low levels of androgen. It also hypothesizes that PSA production is heavily dependent on androgen. The high level of accuracy in fitting clinical data with this model appears to confirm these hypotheses, which are also consistent with biological evidence.

Hydration dynamics promote bacterial coexistence on rough surfaces

PubMed Central

Wang, Gang; Or, Dani

2013-01-01

Identification of mechanisms that promote and maintain the immense microbial diversity found in soil is a central challenge for contemporary microbial ecology. Quantitative tools for systematic integration of complex biophysical and trophic processes at spatial scales, relevant for individual cell interactions, are essential for making progress. We report a modeling study of competing bacterial populations cohabiting soil surfaces subjected to highly dynamic hydration conditions. The model explicitly tracks growth, motion and life histories of individual bacterial cells on surfaces spanning dynamic aqueous networks that shape heterogeneous nutrient fields. The range of hydration conditions that confer physical advantages for rapidly growing species and support competitive exclusion is surprisingly narrow. The rapid fragmentation of soil aqueous phase under most natural conditions suppresses bacterial growth and cell dispersion, thereby balancing conditions experienced by competing populations with diverse physiological traits. In addition, hydration fluctuations intensify localized interactions that promote coexistence through disproportional effects within densely populated regions during dry periods. Consequently, bacterial population dynamics is affected well beyond responses predicted from equivalent and uniform hydration conditions. New insights on hydration dynamics could be considered in future designs of soil bioremediation activities, affect longevity of dry food products, and advance basic understanding of bacterial diversity dynamics and its role in global biogeochemical cycles. PMID:23051694

Allosteric regulation of phosphofructokinase controls the emergence of glycolytic oscillations in isolated yeast cells.

PubMed

Gustavsson, Anna-Karin; van Niekerk, David D; Adiels, Caroline B; Kooi, Bob; Goksör, Mattias; Snoep, Jacky L

2014-06-01

Oscillations are widely distributed in nature and synchronization of oscillators has been described at the cellular level (e.g. heart cells) and at the population level (e.g. fireflies). Yeast glycolysis is the best known oscillatory system, although it has been studied almost exclusively at the population level (i.e. limited to observations of average behaviour in synchronized cultures). We studied individual yeast cells that were positioned with optical tweezers in a microfluidic chamber to determine the precise conditions for autonomous glycolytic oscillations. Hopf bifurcation points were determined experimentally in individual cells as a function of glucose and cyanide concentrations. The experiments were analyzed in a detailed mathematical model and could be interpreted in terms of an oscillatory manifold in a three-dimensional state-space; crossing the boundaries of the manifold coincides with the onset of oscillations and positioning along the longitudinal axis of the volume sets the period. The oscillatory manifold could be approximated by allosteric control values of phosphofructokinase for ATP and AMP. The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.mib.ac.uk/webMathematica/UItester.jsp?modelName=gustavsson5. [Database section added 14 May 2014 after original online publication]. © 2014 FEBS.

Analytic derivation of bacterial growth laws from a simple model of intracellular chemical dynamics.

PubMed

Pandey, Parth Pratim; Jain, Sanjay

2016-09-01

Experiments have found that the growth rate and certain other macroscopic properties of bacterial cells in steady-state cultures depend upon the medium in a surprisingly simple manner; these dependencies are referred to as 'growth laws'. Here we construct a dynamical model of interacting intracellular populations to understand some of the growth laws. The model has only three population variables: an amino acid pool, a pool of enzymes that transport an external nutrient and produce the amino acids, and ribosomes that catalyze their own and the enzymes' production from the amino acids. We assume that the cell allocates its resources between the enzyme sector and the ribosomal sector to maximize its growth rate. We show that the empirical growth laws follow from this assumption and derive analytic expressions for the phenomenological parameters in terms of the more basic model parameters. Interestingly, the maximization of the growth rate of the cell as a whole implies that the cell allocates resources to the enzyme and ribosomal sectors in inverse proportion to their respective 'efficiencies'. The work introduces a mathematical scheme in which the cellular growth rate can be explicitly determined and shows that two large parameters, the number of amino acid residues per enzyme and per ribosome, are useful for making approximations.

Dynamical modelling of haematopoiesis: an integrated view over the system in homeostasis and under perturbation.

PubMed

Manesso, Erica; Teles, José; Bryder, David; Peterson, Carsten

2013-03-06

A very high number of different types of blood cells must be generated daily through a process called haematopoiesis in order to meet the physiological requirements of the organism. All blood cells originate from a population of relatively few haematopoietic stem cells residing in the bone marrow, which give rise to specific progenitors through different lineages. Steady-state dynamics are governed by cell division and commitment rates as well as by population sizes, while feedback components guarantee the restoration of steady-state conditions. In this study, all parameters governing these processes were estimated in a computational model to describe the haematopoietic hierarchy in adult mice. The model consisted of ordinary differential equations and included negative feedback regulation. A combination of literature data, a novel divide et impera approach for steady-state calculations and stochastic optimization allowed one to reduce possible configurations of the system. The model was able to recapitulate the fundamental steady-state features of haematopoiesis and simulate the re-establishment of steady-state conditions after haemorrhage and bone marrow transplantation. This computational approach to the haematopoietic system is novel and provides insight into the dynamics and the nature of possible solutions, with potential applications in both fundamental and clinical research.

Characterization of New Zealand White Rabbit Gut-Associated Lymphoid Tissues and Use as Viral Oncology Animal Model.

PubMed

Haines, Robyn A; Urbiztondo, Rebeccah A; Haynes, Rashade A H; Simpson, Elaine; Niewiesk, Stefan; Lairmore, Michael D

2016-01-01

Rabbits have served as a valuable animal model for the pathogenesis of various human diseases, including those related to agents that gain entry through the gastrointestinal tract such as human T cell leukemia virus type 1. However, limited information is available regarding the spatial distribution and phenotypic characterization of major rabbit leukocyte populations in mucosa-associated lymphoid tissues. Herein, we describe the spatial distribution and phenotypic characterization of leukocytes from gut-associated lymphoid tissues (GALT) from 12-week-old New Zealand White rabbits. Our data indicate that rabbits have similar distribution of leukocyte subsets as humans, both in the GALT inductive and effector sites and in mesenteric lymph nodes, spleen, and peripheral blood. GALT inductive sites, including appendix, cecal tonsil, Peyer's patches, and ileocecal plaque, had variable B cell/T cell ratios (ranging from 4.0 to 0.8) with a predominance of CD4 T cells within the T cell population in all four tissues. Intraepithelial and lamina propria compartments contained mostly T cells, with CD4 T cells predominating in the lamina propria compartment and CD8 T cells predominating in the intraepithelial compartment. Mesenteric lymph node, peripheral blood, and splenic samples contained approximately equal percentages of B cells and T cells, with a high proportion of CD4 T cells compared with CD8 T cells. Collectively, our data indicate that New Zealand White rabbits are comparable with humans throughout their GALT and support future studies that use the rabbit model to study human gut-associated disease or infectious agents that gain entry by the oral route. © The Author 2016. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Single-cell RNA-seq and computational analysis using temporal mixture modelling resolves Th1/Tfh fate bifurcation in malaria

PubMed Central

Lönnberg, Tapio; Svensson, Valentine; James, Kylie R.; Fernandez-Ruiz, Daniel; Sebina, Ismail; Montandon, Ruddy; Soon, Megan S. F.; Fogg, Lily G.; Nair, Arya Sheela; Liligeto, Urijah; Stubbington, Michael J. T.; Ly, Lam-Ha; Bagger, Frederik Otzen; Zwiessele, Max; Lawrence, Neil D.; Souza-Fonseca-Guimaraes, Fernando; Bunn, Patrick T.; Engwerda, Christian R.; Heath, William R.; Billker, Oliver; Stegle, Oliver; Haque, Ashraful; Teichmann, Sarah A.

2017-01-01

Differentiation of naïve CD4+ T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to extensive heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo. By using single-cell transcriptomics and computational analysis using a temporal mixtures of Gaussian processes model, termed GPfates, we reconstructed the developmental trajectories of Th1 and Tfh cells during blood-stage Plasmodium infection in mice. By tracking clonality using endogenous TCR sequences, we first demonstrated that Th1/Tfh bifurcation had occurred at both population and single-clone levels. Next, we identified genes whose expression was associated with Th1 or Tfh fates, and demonstrated a T-cell intrinsic role for Galectin-1 in supporting a Th1 differentiation. We also revealed the close molecular relationship between Th1 and IL-10-producing Tr1 cells in this infection. Th1 and Tfh fates emerged from a highly proliferative precursor that upregulated aerobic glycolysis and accelerated cell cycling as cytokine expression began. Dynamic gene expression of chemokine receptors around bifurcation predicted roles for cell-cell in driving Th1/Tfh fates. In particular, we found that precursor Th cells were coached towards a Th1 but not a Tfh fate by inflammatory monocytes. Thus, by integrating genomic and computational approaches, our study has provided two unique resources, a database www.PlasmoTH.org, which facilitates discovery of novel factors controlling Th1/Tfh fate commitment, and more generally, GPfates, a modelling framework for characterizing cell differentiation towards multiple fates. PMID:28345074

Isolation and characterisation of mesenchymal stem/stromal cells in the ovine endometrium.

PubMed

Letouzey, Vincent; Tan, Ker Sin; Deane, James A; Ulrich, Daniela; Gurung, Shanti; Ong, Y Rue; Gargett, Caroline E

2015-01-01

Mesenchymal stem/stromal cells (MSC) were recently discovered in the human endometrium. These cells possess key stem cell properties and show promising results in small animal models when used for preclinical tissue engineering studies. A small number of surface markers have been identified that enrich for MSC from bone marrow and human endometrium, including the Sushi Domain-containing 2 (SUSD2; W5C5) and CD271 markers. In preparation for developing a large animal preclinical model for urological and gynecological tissue engineering applications we aimed to identify and characterise MSC in ovine endometrium and determine surface markers to enable their prospective isolation. Ovine endometrium was obtained from hysterectomised ewes following progesterone synchronisation, dissociated into single cell suspensions and tested for MSC surface markers and key stem cell properties. Purified stromal cells were obtained by flow cytometry sorting with CD49f and CD45 to remove epithelial cells and leukocytes respectively, and MSC properties investigated. There was a small population CD271+ stromal cells (4.5 ± 2.3%) in the ovine endometrium. Double labelling with CD271 and CD49f showed that the sorted CD271+CD49f- stromal cell population possessed significantly higher cloning efficiency, serial cloning capacity and a qualitative increased ability to differentiate into 4 mesodermal lineages (adipocytic, smooth muscle, chondrocytic and osteoblastic) than CD271-CD49f- cells. Immunolabelling studies identified an adventitial perivascular location for ovine endometrial CD271+ cells. This is the first study to characterise MSC in the ovine endometrium and identify a surface marker profile identifying their location and enabling their prospective isolation. This knowledge will allow future preclinical studies with a large animal model that is well established for pelvic organ prolapse research.

Systematic dissection of phenotypic, functional, and tumorigenic heterogeneity of human prostate cancer cells

PubMed Central

Chao, Hsueh-Ping; Deng, Qu; Jeter, Collene; Liu, Can; Honorio, Sofia; Li, Hangwen; Davis, Tammy; Suraneni, Mahipal; Laffin, Brian; Qin, Jichao; Li, Qiuhui; Yang, Tao; Whitney, Pamela; Shen, Jianjun; Huang, Jiaoti; Tang, Dean G.

2015-01-01

Human cancers are heterogeneous containing stem-like cancer cells operationally defined as cancer stem cells (CSCs) that possess great tumor-initiating and long-term tumor-propagating properties. In this study, we systematically dissect the phenotypic, functional and tumorigenic heterogeneity in human prostate cancer (PCa) using xenograft models and >70 patient tumor samples. In the first part, we further investigate the PSA−/lo PCa cell population, which we have recently shown to harbor self-renewing long-term tumor-propagating cells and present several novel findings. We show that discordant AR and PSA expression in both untreated and castration-resistant PCa (CRPC) results in AR+PSA+, AR+PSA−, AR−PSA−, and AR−PSA+ subtypes of PCa cells that manifest differential sensitivities to therapeutics. We further demonstrate that castration leads to a great enrichment of PSA−/lo PCa cells in both xenograft tumors and CRPC samples and systemic androgen levels dynamically regulate the relative abundance of PSA+ versus PSA−/lo PCa cells that impacts the kinetics of tumor growth. We also present evidence that the PSA−/lo PCa cells possess distinct epigenetic profiles. As the PSA−/lo PCa cell population is heterogeneous, in the second part, we employ two PSA− (Du145 and PC3) and two PSA+ (LAPC9 and LAPC4) PCa models as well as patient tumor cells to further dissect the clonogenic and tumorigenic subsets. We report that different PCa models possess distinct tumorigenic subpopulations that both commonly and uniquely express important signaling pathways that could represent therapeutic targets. Our results have important implications in understanding PCa cell heterogeneity, response to clinical therapeutics, and cellular mechanisms underlying CRPC. PMID:26246472

A size-structured model of bacterial growth and reproduction.

PubMed

Ellermeyer, S F; Pilyugin, S S

2012-01-01

We consider a size-structured bacterial population model in which the rate of cell growth is both size- and time-dependent and the average per capita reproduction rate is specified as a model parameter. It is shown that the model admits classical solutions. The population-level and distribution-level behaviours of these solutions are then determined in terms of the model parameters. The distribution-level behaviour is found to be different from that found in similar models of bacterial population dynamics. Rather than convergence to a stable size distribution, we find that size distributions repeat in cycles. This phenomenon is observed in similar models only under special assumptions on the functional form of the size-dependent growth rate factor. Our main results are illustrated with examples, and we also provide an introductory study of the bacterial growth in a chemostat within the framework of our model.

PRMT5 as a druggable target for glioblastoma therapy.

PubMed

Banasavadi-Siddegowda, Yeshavanth Kumar; Welker, Alessandra M; An, Min; Yang, Xiaozhi; Zhou, Wei; Shi, Guqin; Imitola, Jaime; Li, Chenglong; Hsu, Sigmund; Wang, Jiang; Phelps, Mitch; Zhang, Jianying; Beattie, Christine E; Baiocchi, Robert; Kaur, Balveen

2018-05-18

In spite of standard multimodal therapy consisting of surgical resection followed by radiation and concurrent chemotherapy, prognosis for glioblastoma (GBM) patients remains poor. The identification of both differentiated and undifferentiated "stem cell like" populations in the tumor highlights the significance of finding novel targets that affect the heterogeneous tumor cell population. Protein arginine methyltransferase 5 (PRMT5) is one such candidate gene whose nuclear expression correlates with poor survival and has been reported to be required for survival of differentiated GBM cells and self-renewal of undifferentiated GBM cells. In the current study we screened the specificity and efficacy of 4 novel PRMT5 inhibitors in the treatment of GBM. Efficacies of these inhibitors were screened using an in vitro GBM neurosphere model and an in vivo intracranial zebrafish model of glioma. Standard molecular biology methods were employed to investigate changes in cell cycle, growth, and senescence. In vitro and in vivo studies revealed that among the 4 PRMT5 inhibitors, treatment of GBM cells with compound 5 (CMP5) mirrored the effects of PRMT5 knockdown wherein it led to apoptosis of differentiated GBM cells and drove undifferentiated primary patient derived GBM cells into a nonreplicative senescent state. In vivo antitumor efficacy combined with the specificity of CMP5 underscores the importance of developing it for translation.

Cell of Origin and Cancer Stem Cells in Tumor Suppressor Mouse Models of Glioblastoma.

PubMed

Alcantara Llaguno, Sheila R; Xie, Xuanhua; Parada, Luis F

2016-01-01

The cellular origins and the mechanisms of progression, maintenance of tumorigenicity, and therapeutic resistance are central questions in the glioblastoma multiforme (GBM) field. Using tumor suppressor mouse models, our group recently reported two independent populations of adult GBM-initiating central nervous system progenitors. We found different functional and molecular subtypes depending on the tumor-initiating cell lineage, indicating that the cell of origin is a driver of GBM subtype diversity. Using an in vivo model, we also showed that GBM cancer stem cells (CSCs) or glioma stem cells (GSCs) contribute to resistance to chemotherapeutic agents and that genetic ablation of GSCs leads to a delay in tumor progression. These studies are consistent with the cell of origin and CSCs as critical regulators of the pathogenesis of GBM. © 2016 Alcantara Llaguno et al; Published by Cold Spring Harbor Laboratory Press.

The population dynamics of cancer: a Darwinian perspective.

PubMed

Vineis, Paolo; Berwick, Marianne

2006-10-01

Carcinogenesis, at least for some types of cancer, can be interpreted as the consequence of selection of mutated cells similar to what, in the theory of evolution, occurs at the population level. Instead of considering a population of organisms, we can refer to a population of cells belonging to multicellular organisms. Many carcinogens are mutagens, and the observed geographic distribution of cancer is, at least in part, attributable to environmental mutagens. However, the rapid change in risk for some cancers after migration suggests that carcinogenesis involves--in addition to mutations--some late event that most probably consists of the selection of cells already carrying mutations. We review a few examples of such selective pressures: finasteride in prostate cancer, vitamin supplementation in smokers, acquired resistance to chemotherapy, peripheral resistance to insulin, and sunlight and mutations in melanoma. A disease model for such a hypothesis is represented by Paroxysmal Nocturnal Hemoglobinuria (PNH). Mutations can be present at birth, as in the case of PNH, and can have a frequency much higher than the occurrence of the corresponding disease (PNH or lymphocytic leukaemia in children). However, PNH does not require a mutator phenotype, only a mutant phenotype followed by selection. A characteristic feature of cancer, instead, is likely to be the development of the mutator phenotype. We propose a 'Darwinian' model of carcinogenesis. If the model is correct, it suggests that prevention is more complex than avoiding exposure to mutagens. Mutations and genetic instability can be already present at birth. Mutations can be selected in the course of life if they increase survival advantage of the cell under certain environmental circumstances. In addition, gene-environment interactions cannot be interpreted according to a simplified linear model (based on the 'analysis of variance' concept); experimental work suggests that a more comprehensive non-linear interpretation based on the idea of 'norm of reaction' is needed.

MULTISCALE MODELS OF TAXIS-DRIVEN PATTERNING IN BACTERIAL POPULATIONS

PubMed Central

XUE, CHUAN; OTHMER, HANS G.

2009-01-01

Spatially-distributed populations of various types of bacteria often display intricate spatial patterns that are thought to result from the cellular response to gradients of nutrients or other attractants. In the past decade a great deal has been learned about signal transduction, metabolism and movement in E. coli and other bacteria, but translating the individual-level behavior into population-level dynamics is still a challenging problem. However, this is a necessary step because it is computationally impractical to use a strictly cell-based model to understand patterning in growing populations, since the total number of cells may reach 1012 - 1014 in some experiments. In the past phenomenological equations such as the Patlak-Keller-Segel equations have been used in modeling the cell movement that is involved in the formation of such patterns, but the question remains as to how the microscopic behavior can be correctly described by a macroscopic equation. Significant progress has been made for bacterial species that employ a “run-and-tumble” strategy of movement, in that macroscopic equations based on simplified schemes for signal transduction and turning behavior have been derived [14, 15]. Here we extend previous work in a number of directions: (i) we allow for time-dependent signals, which extends the applicability of the equations to natural environments, (ii) we use a more general turning rate function that better describes the biological behavior, and (iii) we incorporate the effect of hydrodynamic forces that arise when cells swim in close proximity to a surface. We also develop a new approach to solving the moment equations derived from the transport equation that does not involve closure assumptions. Numerical examples show that the solution of the lowest-order macroscopic equation agrees well with the solution obtained from a Monte Carlo simulation of cell movement under a variety of temporal protocols for the signal. We also apply the method to derive equations of chemotactic movement that are governed by multiple chemotactic signals. PMID:19784399

RUNX1B Expression Is Highly Heterogeneous and Distinguishes Megakaryocytic and Erythroid Lineage Fate in Adult Mouse Hematopoiesis

PubMed Central

Draper, Julia E.; Sroczynska, Patrycja; Tsoulaki, Olga; Leong, Hui Sun; Fadlullah, Muhammad Z. H.; Miller, Crispin; Kouskoff, Valerie; Lacaud, Georges

2016-01-01

The Core Binding Factor (CBF) protein RUNX1 is a master regulator of definitive hematopoiesis, crucial for hematopoietic stem cell (HSC) emergence during ontogeny. RUNX1 also plays vital roles in adult mice, in regulating the correct specification of numerous blood lineages. Akin to the other mammalian Runx genes, Runx1 has two promoters P1 (distal) and P2 (proximal) which generate distinct protein isoforms. The activities and specific relevance of these two promoters in adult hematopoiesis remain to be fully elucidated. Utilizing a dual reporter mouse model we demonstrate that the distal P1 promoter is broadly active in adult hematopoietic stem and progenitor cell (HSPC) populations. By contrast the activity of the proximal P2 promoter is more restricted and its upregulation, in both the immature Lineage- Sca1high cKithigh (LSK) and bipotential Pre-Megakaryocytic/Erythroid Progenitor (PreMegE) populations, coincides with a loss of erythroid (Ery) specification. Accordingly the PreMegE population can be prospectively separated into “pro-erythroid” and “pro-megakaryocyte” populations based on Runx1 P2 activity. Comparative gene expression analyses between Runx1 P2+ and P2- populations indicated that levels of CD34 expression could substitute for P2 activity to distinguish these two cell populations in wild type (WT) bone marrow (BM). Prospective isolation of these two populations will enable the further investigation of molecular mechanisms involved in megakaryocytic/erythroid (Mk/Ery) cell fate decisions. Having characterized the extensive activity of P1, we utilized a P1-GFP homozygous mouse model to analyze the impact of the complete absence of Runx1 P1 expression in adult mice and observed strong defects in the T cell lineage. Finally, we investigated how the leukemic fusion protein AML1-ETO9a might influence Runx1 promoter usage. Short-term AML1-ETO9a induction in BM resulted in preferential P2 upregulation, suggesting its expression may be important to establish a pre-leukemic environment. PMID:26808730

Stochastic models for regulatory networks of the genetic toggle switch.

PubMed

Tian, Tianhai; Burrage, Kevin

2006-05-30

Bistability arises within a wide range of biological systems from the lambda phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

Stochastic models for regulatory networks of the genetic toggle switch

PubMed Central

Tian, Tianhai; Burrage, Kevin

2006-01-01

Bistability arises within a wide range of biological systems from the λ phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks. PMID:16714385

Deciphering DNA replication dynamics in eukaryotic cell populations in relation with their averaged chromatin conformations

NASA Astrophysics Data System (ADS)

Goldar, A.; Arneodo, A.; Audit, B.; Argoul, F.; Rappailles, A.; Guilbaud, G.; Petryk, N.; Kahli, M.; Hyrien, O.

2016-03-01

We propose a non-local model of DNA replication that takes into account the observed uncertainty on the position and time of replication initiation in eukaryote cell populations. By picturing replication initiation as a two-state system and considering all possible transition configurations, and by taking into account the chromatin’s fractal dimension, we derive an analytical expression for the rate of replication initiation. This model predicts with no free parameter the temporal profiles of initiation rate, replication fork density and fraction of replicated DNA, in quantitative agreement with corresponding experimental data from both S. cerevisiae and human cells and provides a quantitative estimate of initiation site redundancy. This study shows that, to a large extent, the program that regulates the dynamics of eukaryotic DNA replication is a collective phenomenon that emerges from the stochastic nature of replication origins initiation.

Population Pharmacokinetic and Pharmacodynamic Model-Based Comparability Assessment of a Recombinant Human Epoetin Alfa and the Biosimilar HX575

PubMed Central

Yan, Xiaoyu; Lowe, Philip J.; Fink, Martin; Berghout, Alexander; Balser, Sigrid; Krzyzanski, Wojciech

2012-01-01

The aim of this study was to develop an integrated pharmacokinetic and pharmacodynamic (PK/PD) model and assess the comparability between epoetin alfa HEXAL/Binocrit (HX575) and a comparator epoetin alfa by a model-based approach. PK/PD data—including serum drug concentrations, reticulocyte counts, red blood cells, and hemoglobin levels—were obtained from 2 clinical studies. In sum, 149 healthy men received multiple intravenous or subcutaneous doses of HX575 (100 IU/kg) and the comparator 3 times a week for 4 weeks. A population model based on pharmacodynamics-mediated drug disposition and cell maturation processes was used to characterize the PK/PD data for the 2 drugs. Simulations showed that due to target amount changes, total clearance may increase up to 2.4-fold as compared with the baseline. Further simulations suggested that once-weekly and thrice-weekly subcutaneous dosing regimens would result in similar efficacy. The findings from the model-based analysis were consistent with previous results using the standard noncompartmental approach demonstrating PK/PD comparability between HX575 and comparator. However, due to complexity of the PK/PD model, control of random effects was not straightforward. Whereas population PK/PD model-based analyses are suited for studying complex biological systems, such models have their limitations (statistical), and their comparability results should be interpreted carefully. PMID:22162538

Innate lymphoid cells in the initiation, regulation and resolution of inflammation

PubMed Central

Sonnenberg, Gregory F.; Artis, David

2016-01-01

A previously unappreciated cell type of the innate immune system, termed innate lymphoid cells (ILCs), has been characterized in mice and humans, and found to profoundly influence the induction, regulation and resolution of inflammation. ILCs play an important role in these processes in murine models of infection, inflammatory disease and tissue repair. Further, disease association studies in defined patient populations have identified significant alterations in ILC responses, suggesting a potential role for these cell populations in human health and disease. In this review, we discuss the emerging family of ILCs, the role of ILCs in inflammation, and how current or novel therapeutic strategies could be employed to selectively modulate ILC responses and limit chronic inflammatory diseases in patients. PMID:26121198

Analysis and IbM simulation of the stages in bacterial lag phase: basis for an updated definition.

PubMed

Prats, Clara; Giró, Antoni; Ferrer, Jordi; López, Daniel; Vives-Rego, Josep

2008-05-07

The lag phase is the initial phase of a culture that precedes exponential growth and occurs when the conditions of the culture medium differ from the pre-inoculation conditions. It is usually defined by means of cell density because the number of individuals remains approximately constant or slowly increases, and it is quantified with the lag parameter lambda. The lag phase has been studied through mathematical modelling and by means of specific experiments. In recent years, Individual-based Modelling (IbM) has provided helpful insights into lag phase studies. In this paper, the definition of lag phase is thoroughly examined. Evolution of the total biomass and the total number of bacteria during lag phase is tackled separately. The lag phase lasts until the culture reaches a maximum growth rate both in biomass and cell density. Once in the exponential phase, both rates are constant over time and equal to each other. Both evolutions are split into an initial phase and a transition phase, according to their growth rates. A population-level mathematical model is presented to describe the transitional phase in cell density. INDividual DIScrete SIMulation (INDISIM) is used to check the outcomes of this analysis. Simulations allow the separate study of the evolution of cell density and total biomass in a batch culture, they provide a depiction of different observed cases in lag evolution at the individual-cell level, and are used to test the population-level model. The results show that the geometrical lag parameter lambda is not appropriate as a universal definition for the lag phase. Moreover, the lag phase cannot be characterized by a single parameter. For the studied cases, the lag phases of both the total biomass and the population are required to fully characterize the evolution of bacterial cultures. The results presented prove once more that the lag phase is a complex process that requires a more complete definition. This will be possible only after the phenomena governing the population dynamics at an individual level of description, and occurring during the lag and exponential growth phases, are well understood.

Distribution of Interleukin-22-secreting Immune Cells in Conjunctival Associated Lymphoid Tissue.

PubMed

Yoon, Chang Ho; Lee, Daeseung; Jeong, Hyun Jeong; Ryu, Jin Suk; Kim, Mee Kum

2018-04-01

Interleukin (IL)-22 is a cytokine involved in epithelial cell regeneration. Currently, no research studies have analyzed the distribution of the three distinct IL-22-secreting cell populations in human or mouse conjunctiva. This study investigated the distribution of the three main populations of IL-22-secreting immune cells, αβ Th cells, γδ T cells, or innate cells (innate lymphoid cells [ILCs] or natural killer cells), in conjunctival associated lymphoid tissues (CALTs) in human and mouse models. We collected discarded cadaveric bulbar conjunctival tissue specimens after preservation of the corneo-limbal tissue for keratoplasty from four enucleated eyes of the domestic donor. The bulbar conjunctiva tissue, including the cornea from normal (n = 27) or abraded (n = 4) B6 mice, were excised and pooled in RPMI 1640 media. After the lymphoid cells were gated in forward and side scattering, the αβ Th cells, γδ T cells, or innate lymphoid cells were positively or negatively gated using anti-CD3, anti-γδ TCR, and anti-IL-22 antibodies, with a FACSCanto flow cytometer. In normal human conjunctiva, the percentage and number of cells were highest in αβ Th cells, followed by γδ T cells and CD3- γδ TCR- IL-22+ innate cells (presumed ILCs, pILCs) (Kruskal-Wallis test, p = 0.012). In normal mice keratoconjunctiva, the percentage and total number were highest in γδ T cells, followed by αβ Th cells and pILCs (Kruskal-Wallis test, p = 0.0004); in corneal abraded mice, the population of αβ Th cells and pILCs tended to increase. This study suggests that three distinctive populations of IL-22-secreting immune cells are present in CALTs of both humans and mice, and the proportions of IL-22+αβ Th cells, γδ T cells, and pILCs in CALTs in humans might be differently distributed from those in normal mice. © 2018 The Korean Ophthalmological Society.

Chronic Dry Eye Disease is Principally Mediated by Effector Memory Th17 Cells

PubMed Central

Chen, Yihe; Chauhan, Sunil K.; Lee, Hyun Soo; Saban, Daniel R.; Dana, Reza

2013-01-01

Recent experimental and clinical data suggest that there is a link between dry eye disease (DED) and T cell-mediated immunity. However, whether these immune responses are a consequence or cause of ocular surface inflammation remains to be determined. Thus far, only models of acute DED have been used to derive experimental data. This is in contrast to clinical DED which usually presents as a chronic disease. In the present study, using a murine model of chronic DED, it was established that the chronic phase of the disease is accompanied by Th17 responses at the ocular surface, and that a significant memory T cell population can be recovered from chronic DED. This memory response is predominantly mediated by Th17 cells. Moreover, adoptive transfer of this memory T cell population was shown to induce more severe and rapidly progressing DED than did the adoptive transfer of its effector or naïve counterparts. Not only do these results clearly demonstrate that effector memory Th17 cells are primarily responsible for maintaining the chronic and relapsing course of DED, but they also highlight a potentially novel therapeutic strategy for targeting memory immune responses in patients with DED. PMID:23571503

Genetic models in applied physiology: selected contribution: effects of spaceflight on immunity in the C57BL/6 mouse. I. Immune population distributions

NASA Technical Reports Server (NTRS)

Pecaut, Michael J.; Nelson, Gregory A.; Peters, Luanne L.; Kostenuik, Paul J.; Bateman, Ted A.; Morony, Sean; Stodieck, Louis S.; Lacey, David L.; Simske, Steven J.; Gridley, Daila S.

2003-01-01

There are several aspects of the spaceflight environment that may lead to changes in immunity: mission-related psychological stress, radiation, and changes in gravity. On December 5, 2001, the space shuttle Endeavor launched for a 12-day mission to examine these effects on C57BL/6 mice for the first time. On their return, assays were performed on the spleen, blood, and bone marrow. In response to flight, there were no significant differences in the general circulating leukocyte proportions. In contrast, there was an increase in splenic lymphocyte percentages, with a corresponding decrease in granulocytes. There was an overall shift in splenic lymphocytes away from T cells toward B cells, and a decrease in the CD4-to-CD8 ratios due to a decrease in T helpers. In contrast, there were proportional increases in bone marrow T cells, with decreases in B cells. Although the blast percentage and count were decreased in flight mice, the CD34(+) population was increased. The data were more consistent with a shift in bone marrow populations rather than a response to changes in the periphery. Many of the results are similar to those using other models. Clearly, spaceflight can influence immune parameters ranging from hematopoiesis to mature leukocyte mechanisms.

Virus dynamics in the presence of synaptic transmission

PubMed Central

Komarova, Natalia L.; Wodarz, Dominik

2014-01-01

Traditionally, virus dynamics models consider populations of infected and target cells, and a population of free virus that can infect susceptible cells. In recent years, however, it has become clear that direct cell-to-cell transmission can also play an important role for the in vivo spread of viruses, especially retroviruses such as human T lymphotropic virus-1 (HTLV-1) and Human immundeficeincy virus (HIV). Such cell-to-cell transmission is thought to occur through the formation of virological synapses that are formed between an infected source cell and a susceptible target cell. Here we formulate and analyze a class of virus dynamics models that include such cell-cell synaptic transmission. We explore different ”strategies” of the virus defined by the number of viruses passed per synapse, and determine how the choice of strategy influences the basic reproductive ratio, R0, of the virus and thus its ability to establish a persistent infection. We show that depending on specific assumptions about the viral kinetics, strategies with low or intermediate numbers of viruses transferred may correspond to the highest values of R0. We also explore the evolutionary competition of viruses of different strains, which differ by their synaptic strategy, and show that viruses characterized by synaptic strategies with the highest R0 win the evolutionary competition and exclude other, inferior, strains. PMID:23357287

Computational design optimization for microfluidic magnetophoresis

PubMed Central

Plouffe, Brian D.; Lewis, Laura H.; Murthy, Shashi K.

2011-01-01

Current macro- and microfluidic approaches for the isolation of mammalian cells are limited in both efficiency and purity. In order to design a robust platform for the enumeration of a target cell population, high collection efficiencies are required. Additionally, the ability to isolate pure populations with minimal biological perturbation and efficient off-chip recovery will enable subcellular analyses of these cells for applications in personalized medicine. Here, a rational design approach for a simple and efficient device that isolates target cell populations via magnetic tagging is presented. In this work, two magnetophoretic microfluidic device designs are described, with optimized dimensions and operating conditions determined from a force balance equation that considers two dominant and opposing driving forces exerted on a magnetic-particle-tagged cell, namely, magnetic and viscous drag. Quantitative design criteria for an electromagnetic field displacement-based approach are presented, wherein target cells labeled with commercial magnetic microparticles flowing in a central sample stream are shifted laterally into a collection stream. Furthermore, the final device design is constrained to fit on standard rectangular glass coverslip (60 (L)×24 (W)×0.15 (H) mm3) to accommodate small sample volume and point-of-care design considerations. The anticipated performance of the device is examined via a parametric analysis of several key variables within the model. It is observed that minimal currents (<500 mA) are required to generate magnetic fields sufficient to separate cells from the sample streams flowing at rate as high as 7 ml∕h, comparable to the performance of current state-of-the-art magnet-activated cell sorting systems currently used in clinical settings. Experimental validation of the presented model illustrates that a device designed according to the derived rational optimization can effectively isolate (∼100%) a magnetic-particle-tagged cell population from a homogeneous suspension even in a low abundance. Overall, this design analysis provides a rational basis to select the operating conditions, including chamber and wire geometry, flow rates, and applied currents, for a magnetic-microfluidic cell separation device. PMID:21526007

Heteroresistance at the single-cell level: adapting to antibiotic stress through a population-based strategy and growth-controlled interphenotypic coordination.

PubMed

Wang, Xiaorong; Kang, Yu; Luo, Chunxiong; Zhao, Tong; Liu, Lin; Jiang, Xiangdan; Fu, Rongrong; An, Shuchang; Chen, Jichao; Jiang, Ning; Ren, Lufeng; Wang, Qi; Baillie, J Kenneth; Gao, Zhancheng; Yu, Jun

2014-02-11

Heteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of "resistant" cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population "hedges" its "bet" on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a blaCTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger "resistance"). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance--the gradually decreased colony-forming capability in the presence of antibiotic--was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses. Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of "resistant" cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.

Fish in a Dish: Drug Discovery for Hearing Habilitation.

PubMed

Esterberg, Robert; Coffin, Allison B; Ou, Henry; Simon, Julian A; Raible, David W; Rubel, Edwin W

2013-01-01

The majority of hearing loss is caused by the permanent loss of inner ear hair cells. The identification of drugs that modulate the susceptibility to hair cell loss or spur their regeneration is often hampered by the difficulties of assaying for such complex phenomena in mammalian models. The zebrafish has emerged as a powerful animal model for chemical screening in many contexts. Several characteristics of the zebrafish, such as its small size and external location of sensory hair cells, uniquely position it as an ideal model organism for the study of hair cell toxicity, protection, and regeneration. We have used this model to screen for drugs that affect each of these aspects of hair cell biology and have identified compounds that affect each of these processes. The identification of such drugs and drug-like compounds holds promise in the future ability to stem hearing loss in the human population.

A Catalytic Role for Proangiogenic Marrow-Derived Cells in Tumor Neovascularization

PubMed Central

Seandel, Marco; Butler, Jason; Lyden, David; Rafii, Shahin

2010-01-01

Small numbers of proangiogenic bone marrow-derived cells (BMDCs) can play pivotal roles in tumor progression. In this issue of Cancer Cell, two papers, utilizing different tumor angiogenesis models, both find that activated MMP-9 delivered by BMDCs modulates neovessel remodeling, thereby promoting tumor growth. The changes in microvascular anatomy induced by MMP-9-expressing BMDCs are strikingly different between the preirradiated tumor vascular bed model employed by Ahn and Brown and the invasive glioblastoma model utilized by Du et al., likely mirroring the complexity of the real tumor microenvironment and the intricacy of roles of different BMDC populations in mediating tumor neoangiogenesis. PMID:18328420

Chemotaxing and haptotaxing random walkers having directional persistence

NASA Astrophysics Data System (ADS)

Kwon, Tae Goo; Kyoungjin Lee Team; Taeseok Daniel Yang Team

2015-03-01

Biological cell crawling is a rather complex process involving various bio-chemical and bio-mechanical processes, many of which are still not well understood. The difficulties in understanding the crawling are originating not just from cell-intrinsic factors but from their complex social interactions, cell-to-substrate interactions and nonlinear responses toward extrinsic factors. Here, in this report we investigate chemotactic behavior of mathematical model cells that naturally have directional persistence. A cell density is measured as a function of time and space, then the resulting steady state is compared with that of the well-known Keller-Segal model, which describes a population of chemotactic random walker. Then, we add a cell-to-cell interaction, mimicking a ``haptotaxis'' mediated interaction, to the model and access its role as for altering the steady-state cell density profile. This mathematical model system, which we have developed and considered in this work, can be quite relevant to the chemotactic responses of interacting immune cells, like microglia, moving toward and around a site of wound, as for an example. We conclude by discussing some relevant recent experimental findings.

Retrospective population pharmacokinetic/pharmacodynamic analysis of pyridostigmine, a cholinesterase inhibitor, in Chinese males.

PubMed

Seng, Kok-Yong; Loke, Weng-Keong; Moochhala, Shabbir; Zhao, Bin; Lee, Jon-Deoon Edmund

2009-09-01

We have characterised the population pharmacokinetics-pharmacodynamics of pyridostigmine given as pyridostigmine bromide. Over three days 50 healthy Chinese male subjects each received seven doses of 30 mg pyridostigmine bromide orally (3 x 10 mg every 8 h). Plasma concentrations of pyridostigmine and red blood cell acetylcholinesterase (AChE) activity were determined at various times within the eight hours after the first and the seventh doses. The resulting pharmacokinetic data were fitted to a single compartment open model with first-order absorption and elimination. The pharmacodynamics were modelled using an inhibitory E(max) model. The potential influence of demographic and biological covariates on the model parameters was investigated. Nonlinear mixed effects modelling was performed using NONMEM. The apparent clearance and volume of distribution as well as absorption rate constant of plasma pyridostigmine were estimated to be 136 l/h, 130 l and 0.68 1/h, respectively. The maximum red blood cell AChE activity decrease (E(max)) and plasma pyridostigmine concentration producing 50% of this reduction (EC50) were estimated to be 9.32 AChE units per gram haemoglobin and 51.9 ng/ml, respectively. None of the tested covariates were found to be correlated with any of the model parameters. Dosing simulations suggested that 30 mg repeated every six hours might be needed to achieve steady-state trough percentage inhibition above the recommended 10% in healthy Chinese males. The pharmacokinetics and the effects of pyridostigmine on red blood cell AChE activity were described using a mixed effects model. For Chinese males, the dosing interval may have been shorter than that recommended for the Caucasian population. Additional studies are needed to confirm these findings.

Functional genomic characterization of neoblast-like stem cells in larval Schistosoma mansoni

PubMed Central

Wang, Bo; Collins, James J; Newmark, Phillip A

2013-01-01

Schistosomes infect hundreds of millions of people in the developing world. Transmission of these parasites relies on a stem cell-driven, clonal expansion of larvae inside a molluscan intermediate host. How this novel asexual reproductive strategy relates to current models of stem cell maintenance and germline specification is unclear. Here, we demonstrate that this proliferative larval cell population (germinal cells) shares some molecular signatures with stem cells from diverse organisms, in particular neoblasts of planarians (free-living relatives of schistosomes). We identify two distinct germinal cell lineages that differ in their proliferation kinetics and expression of a nanos ortholog. We show that a vasa/PL10 homolog is required for proliferation and maintenance of both populations, whereas argonaute2 and a fibroblast growth factor receptor-encoding gene are required only for nanos-negative cells. Our results suggest that an ancient stem cell-based developmental program may have enabled the evolution of the complex life cycle of parasitic flatworms. DOI: http://dx.doi.org/10.7554/eLife.00768.001 PMID:23908765

Robust and Accurate Discrimination of Self/Non-Self Antigen Presentations by Regulatory T Cell Suppression.

PubMed

Furusawa, Chikara; Yamaguchi, Tomoyuki

The immune response by T cells usually discriminates self and non-self antigens, even though the negative selection of self-reactive T cells is imperfect and a certain fraction of T cells can respond to self-antigens. In this study, we construct a simple mathematical model of T cell populations to analyze how such self/non-self discrimination is possible. The results demonstrate that the control of the immune response by regulatory T cells enables a robust and accurate discrimination of self and non-self antigens, even when there is a significant overlap between the affinity distribution of T cells to self and non-self antigens. Here, the number of regulatory T cells in the system acts as a global variable controlling the T cell population dynamics. The present study provides a basis for the development of a quantitative theory for self and non-self discrimination in the immune system and a possible strategy for its experimental verification.

Robust and Accurate Discrimination of Self/Non-Self Antigen Presentations by Regulatory T Cell Suppression

PubMed Central

Furusawa, Chikara; Yamaguchi, Tomoyuki

2016-01-01

The immune response by T cells usually discriminates self and non-self antigens, even though the negative selection of self-reactive T cells is imperfect and a certain fraction of T cells can respond to self-antigens. In this study, we construct a simple mathematical model of T cell populations to analyze how such self/non-self discrimination is possible. The results demonstrate that the control of the immune response by regulatory T cells enables a robust and accurate discrimination of self and non-self antigens, even when there is a significant overlap between the affinity distribution of T cells to self and non-self antigens. Here, the number of regulatory T cells in the system acts as a global variable controlling the T cell population dynamics. The present study provides a basis for the development of a quantitative theory for self and non-self discrimination in the immune system and a possible strategy for its experimental verification. PMID:27668873

[TNF-α, diabetes type 1 and regulatory T cells].

PubMed

Ryba, Monika; Myśliwska, Jolanta

2010-01-01

Recent studies on animal models of diabetes as well as human regulatory T cells have shown that α impairs the ability of these cells to prevent the disease. NOD mice treated with α had decreased frequency of regulatory T cells, whereas anti-TNF administration induced the increase in the number of these cells and disease prevention. The action of α also influenced the suppressive potential of Tregs. Increased susceptibility of Tregs to the modulatory effects of α involves signaling through TNFR2 that is expressed on the surface of this cell population. It seems that α neutralization may rescue regulatory T cells and restore their function in several autoimmune and inflammatory diseases. This review describes recent data concerning regulatory T cells in the context of inflammation that is present during diabetes type 1. It describes how TNF contributes to the pathogenesis of type 1 diabetes, what is the impact of this cytokine on regulatory T cell population and therapeutic effects that result from its neutralization in several inflammatory and autoimmune diseases.

Developmental Origin Governs CD8+ T Cell Fate Decisions during Infection.

PubMed

Smith, Norah L; Patel, Ravi K; Reynaldi, Arnold; Grenier, Jennifer K; Wang, Jocelyn; Watson, Neva B; Nzingha, Kito; Yee Mon, Kristel J; Peng, Seth A; Grimson, Andrew; Davenport, Miles P; Rudd, Brian D

2018-06-06

Heterogeneity is a hallmark feature of the adaptive immune system in vertebrates. Following infection, naive T cells differentiate into various subsets of effector and memory T cells, which help to eliminate pathogens and maintain long-term immunity. The current model suggests there is a single lineage of naive T cells that give rise to different populations of effector and memory T cells depending on the type and amounts of stimulation they encounter during infection. Here, we have discovered that multiple sub-populations of cells exist in the naive CD8 + T cell pool that are distinguished by their developmental origin, unique transcriptional profiles, distinct chromatin landscapes, and different kinetics and phenotypes after microbial challenge. These data demonstrate that the naive CD8 + T cell pool is not as homogeneous as previously thought and offers a new framework for explaining the remarkable heterogeneity in the effector and memory T cell subsets that arise after infection. Copyright © 2018 Elsevier Inc. All rights reserved.

Identification of Newly Committed Pancreatic Cells in the Adult Mouse Pancreas.

PubMed

Socorro, Mairobys; Criscimanna, Angela; Riva, Patricia; Tandon, Manuj; Prasadan, Krishna; Guo, Ping; Humar, Abhinav; Husain, Sohail Z; Leach, Steven D; Gittes, George K; Esni, Farzad

2017-12-13

Multipotent epithelial cells with high Aldehyde dehydrogenase activity have been previously reported to exist in the adult pancreas. However, whether they represent true progenitor cells remains controversial. In this study, we isolated and characterized cells with ALDH activity in the adult mouse or human pancreas during physiological conditions or injury. We found that cells with ALDH activity are abundant in the mouse pancreas during early postnatal growth, pregnancy, and in mouse models of pancreatitis and type 1 diabetes (T1D). Importantly, a similar population of cells is found abundantly in healthy children, or in patients with pancreatitis or T1D. We further demonstrate that cells with ALDH activity can commit to either endocrine or acinar lineages, and can be divided into four sub-populations based on CD90 and Ecadherin expression. Finally, our in vitro and in vivo studies show that the progeny of ALDH1 + /CD90 - /Ecad - cells residing in the adult mouse pancreas have the ability to initiate Pancreatic and duodenal homeobox (Pdx1) expression for the first time. In summary, we provide evidence for the existence of a sortable population of multipotent non-epithelial cells in the adult pancreas that can commit to the pancreatic lineage following proliferation and mesenchymal to epithelial transition (MET).

Dispersal, density dependence, and population dynamics of a fungal microbe on leaf surfaces.

PubMed

Woody, Scott T; Ives, Anthony R; Nordheim, Erik V; Andrews, John H

2007-06-01

Despite the ubiquity and importance of microbes in nature, little is known about their natural population dynamics, especially for those that occupy terrestrial habitats. Here we investigate the dynamics of the yeast-like fungus Aureobasidium pullulans (Ap) on apple leaves in an orchard. We asked three questions. (1) Is variation in fungal population density among leaves caused by variation in leaf carrying capacities and strong density-dependent population growth that maintains densities near carrying capacity? (2) Do resident populations have competitive advantages over immigrant cells? (3) Do Ap dynamics differ at different times during the growing season? To address these questions, we performed two experiments at different times in the growing season. Both experiments used a 2 x 2 factorial design: treatment 1 removed fungal cells from leaves to reveal density-dependent population growth, and treatment 2 inoculated leaves with an Ap strain engineered to express green fluorescent protein (GFP), which made it possible to track the fate of immigrant cells. The experiments showed that natural populations of Ap vary greatly in density due to sustained differences in carrying capacities among leaves. The maintenance of populations close to carrying capacities indicates strong density-dependent processes. Furthermore, resident populations are strongly competitive against immigrants, while immigrants have little impact on residents. Finally, statistical models showed high population growth rates of resident cells in one experiment but not in the other, suggesting that Ap experiences relatively "good" and "bad" periods for population growth. This picture of Ap dynamics conforms to commonly held, but rarely demonstrated, expectations of microbe dynamics in nature. It also highlights the importance of local processes, as opposed to immigration, in determining the abundance and dynamics of microbes on surfaces in terrestrial systems.

Highly efficient methods to obtain homogeneous dorsal neural progenitor cells from human and mouse embryonic stem cells and induced pluripotent stem cells.

PubMed

Zhang, Meixiang; Ngo, Justine; Pirozzi, Filomena; Sun, Ying-Pu; Wynshaw-Boris, Anthony

2018-03-15

Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) have been widely used to generate cellular models harboring specific disease-related genotypes. Of particular importance are ESC and iPSC applications capable of producing dorsal telencephalic neural progenitor cells (NPCs) that are representative of the cerebral cortex and overcome the challenges of maintaining a homogeneous population of cortical progenitors over several passages in vitro. While previous studies were able to derive NPCs from pluripotent cell types, the fraction of dorsal NPCs in this population is small and decreases over several passages. Here, we present three protocols that are highly efficient in differentiating mouse and human ESCs, as well as human iPSCs, into a homogeneous and stable population of dorsal NPCs. These protocols will be useful for modeling cerebral cortical neurological and neurodegenerative disorders in both mouse and human as well as for high-throughput drug screening for therapeutic development. We optimized three different strategies for generating dorsal telencephalic NPCs from mouse and human pluripotent cell types through single or double inhibition of bone morphogenetic protein (BMP) and/or SMAD pathways. Mouse and human pluripotent cells were aggregated to form embryoid bodies in suspension and were treated with dorsomorphin alone (BMP inhibition) or combined with SB431542 (double BMP/SMAD inhibition) during neural induction. Neural rosettes were then selected from plated embryoid bodies to purify the population of dorsal NPCs. We tested the expression of key dorsal NPC markers as well as nonectodermal markers to confirm the efficiency of our three methods in comparison to published and commercial protocols. Single and double inhibition of BMP and/or SMAD during neural induction led to the efficient differentiation of dorsal NPCs, based on the high percentage of PAX6-positive cells and the NPC gene expression profile. There were no statistically significant differences in the variation of PAX6 and SOX1-positive NPCs between the two human pluripotent cell-derived methods; therefore, both methods are suitable for producing stable dorsal NPCs. When further differentiated into mature neurons, NPCs gave rise to a population of almost exclusively forebrain cortical neurons, confirming the dorsal fate commitment of the progenitors. The methods described in this study show improvements over previously published studies and are highly efficient at differentiating human and mouse pluripotent cell types into dorsal PAX6-positive NPCs and eventually into forebrain cortical neurons.