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

Dynamics of cell proliferation in the adult dentate gyrus of two inbred strains of mice

NASA Technical Reports Server (NTRS)

Hayes, N. L.; Nowakowski, R. S.

2002-01-01

The output potential of proliferating populations in either the developing or the adult nervous system is critically dependent on the length of the cell cycle (T(c)) and the size of the proliferating population. We developed a new approach for analyzing the cell cycle, the 'Saturate and Survive Method' (SSM), that also reveals the dynamic behaviors in the proliferative population and estimates of the size of the proliferating population. We used this method to analyze the proliferating population of the adult dentate gyrus in 60 day old mice of two inbred strains, C57BL/6J and BALB/cByJ. The results show that the number of cells labeled by exposure to BUdR changes dramatically with time as a function of the number of proliferating cells in the population, the length of the S-phase, cell division, the length of the cell cycle, dilution of the S-phase label, and cell death. The major difference between C57BL/6J and BALB/cByJ mice is the size of the proliferating population, which differs by a factor of two; the lengths of the cell cycle and the S-phase and the probability that a newly produced cell will die within the first 10 days do not differ in these two strains. This indicates that genetic regulation of the size of the proliferating population is independent of the genetic regulation of cell death among those newly produced cells. The dynamic changes in the number of labeled cells as revealed by the SSM protocol also indicate that neither single nor repeated daily injections of BUdR accurately measure 'proliferation.'.

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.

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.

The Dynamics of HPV Infection and Cervical Cancer Cells.

PubMed

Asih, Tri Sri Noor; Lenhart, Suzanne; Wise, Steven; Aryati, Lina; Adi-Kusumo, F; Hardianti, Mardiah S; Forde, Jonathan

2016-01-01

The development of cervical cells from normal cells infected by human papillomavirus into invasive cancer cells can be modeled using population dynamics of the cells and free virus. The cell populations are separated into four compartments: susceptible cells, infected cells, precancerous cells and cancer cells. The model system of differential equations also has a free virus compartment in the system, which infect normal cells. We analyze the local stability of the equilibrium points of the model and investigate the parameters, which play an important role in the progression toward invasive cancer. By simulation, we investigate the boundary between initial conditions of solutions, which tend to stable equilibrium point, representing controlled infection, and those which tend to unbounded growth of the cancer cell population. Parameters affected by drug treatment are varied, and their effect on the risk of cancer progression is explored.

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.

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.

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.

Extinction rates in tumour public goods games.

PubMed

Gerlee, Philip; Altrock, Philipp M

2017-09-01

Cancer evolution and progression are shaped by cellular interactions and Darwinian selection. Evolutionary game theory incorporates both of these principles, and has been proposed as a framework to understand tumour cell population dynamics. A cornerstone of evolutionary dynamics is the replicator equation, which describes changes in the relative abundance of different cell types, and is able to predict evolutionary equilibria. Typically, the replicator equation focuses on differences in relative fitness. We here show that this framework might not be sufficient under all circumstances, as it neglects important aspects of population growth. Standard replicator dynamics might miss critical differences in the time it takes to reach an equilibrium, as this time also depends on cellular turnover in growing but bounded populations. As the system reaches a stable manifold, the time to reach equilibrium depends on cellular death and birth rates. These rates shape the time scales, in particular, in coevolutionary dynamics of growth factor producers and free-riders. Replicator dynamics might be an appropriate framework only when birth and death rates are of similar magnitude. Otherwise, population growth effects cannot be neglected when predicting the time to reach an equilibrium, and cell-type-specific rates have to be accounted for explicitly. © 2017 The Authors.

The dynamics of health in wild field vole populations: a haematological perspective

PubMed Central

Beldomenico, Pablo M.; Telfer, Sandra; Gebert, Stephanie; Lukomski, Lukasz; Bennett, Malcolm; Begon, Michael

2010-01-01

Summary Pathogens have been proposed as potentially important drivers of population dynamics, but while a few studies have investigated the impact of specific pathogens, the wealth of information provided by general indices of health has hardly been exploited. By evaluating haematological parameters in wild populations, our knowledge of the dynamics of health and infection may be better understood. Here, haematological dynamics in natural populations of field voles are investigated to determine environmental and host factors associated with indicators of inflammatory response (counts of monocytes and neutrophils) and of condition: measures of immunological investment (lymphocyte counts) and aerobic capacity (red blood cell counts). Individuals from three field vole populations were sampled monthly for 2 years. Comparisons with individuals kept under controlled conditions facilitated interpretation of field data. Mixed effects models were developed for each cell type to evaluate separately the effects of various factors on post-juvenile voles and mature breeding females. There were three well-characterized ‘physiological’ seasons. The immunological investment appeared lowest in winter (lowest lymphocyte counts), but red blood cells were at their highest levels and indices of inflammatory response at their lowest. Spring was characterized by a fall in red blood cell counts and peaks in indicators of inflammatory response. During the course of summer—autumn, red blood cell counts recovered, the immunological investment increased and the indicators of inflammatory response decreased. Poor body condition appeared to affect the inflammatory response (lower neutrophil and monocyte peaks) and the immunological investment (lower lymphocyte counts), providing evidence that the capacity to fight infection is dependent upon host condition. Breeding early in the year was most likely in females in better condition (high lymphocyte and red blood cell counts). All the haematological parameters were affected adversely by high population densities. PMID:18564292

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

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.

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

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.

Distinct retrosplenial cortex cell populations and their spike dynamics during ketamine-induced unconscious state

PubMed Central

Zhao, Fang; Tsien, Joe Z.

2017-01-01

Ketamine is known to induce psychotic-like symptoms, including delirium and visual hallucinations. It also causes neuronal damage and cell death in the retrosplenial cortex (RSC), an area that is thought to be a part of high visual cortical pathways and at least partially responsible for ketamine’s psychotomimetic activities. However, the basic physiological properties of RSC cells as well as their response to ketamine in vivo remained largely unexplored. Here, we combine a computational method, the Inter-Spike Interval Classification Analysis (ISICA), and in vivo recordings to uncover and profile excitatory cell subtypes within layers 2&3 and 5&6 of the RSC in mice within both conscious, sleep, and ketamine-induced unconscious states. We demonstrate two distinct excitatory principal cell sub-populations, namely, high-bursting excitatory principal cells and low-bursting excitatory principal cells, within layers 2&3, and show that this classification is robust over the conscious states, namely quiet awake, and natural unconscious sleep periods. Similarly, we provide evidence of high-bursting and low-bursting excitatory principal cell sub-populations within layers 5&6 that remained distinct during quiet awake and sleep states. We further examined how these subtypes are dynamically altered by ketamine. During ketamine-induced unconscious state, these distinct excitatory principal cell subtypes in both layer 2&3 and layer 5&6 exhibited distinct dynamics. We also uncovered different dynamics of local field potential under various brain states in layer 2&3 and layer 5&6. Interestingly, ketamine administration induced high gamma oscillations in layer 2&3 of the RSC, but not layer 5&6. Our results show that excitatory principal cells within RSC layers 2&3 and 5&6 contain multiple physiologically distinct sub-populations, and they are differentially affected by ketamine. PMID:29073221

Distinct retrosplenial cortex cell populations and their spike dynamics during ketamine-induced unconscious state.

PubMed

Fox, Grace E; Li, Meng; Zhao, Fang; Tsien, Joe Z

2017-01-01

Ketamine is known to induce psychotic-like symptoms, including delirium and visual hallucinations. It also causes neuronal damage and cell death in the retrosplenial cortex (RSC), an area that is thought to be a part of high visual cortical pathways and at least partially responsible for ketamine's psychotomimetic activities. However, the basic physiological properties of RSC cells as well as their response to ketamine in vivo remained largely unexplored. Here, we combine a computational method, the Inter-Spike Interval Classification Analysis (ISICA), and in vivo recordings to uncover and profile excitatory cell subtypes within layers 2&3 and 5&6 of the RSC in mice within both conscious, sleep, and ketamine-induced unconscious states. We demonstrate two distinct excitatory principal cell sub-populations, namely, high-bursting excitatory principal cells and low-bursting excitatory principal cells, within layers 2&3, and show that this classification is robust over the conscious states, namely quiet awake, and natural unconscious sleep periods. Similarly, we provide evidence of high-bursting and low-bursting excitatory principal cell sub-populations within layers 5&6 that remained distinct during quiet awake and sleep states. We further examined how these subtypes are dynamically altered by ketamine. During ketamine-induced unconscious state, these distinct excitatory principal cell subtypes in both layer 2&3 and layer 5&6 exhibited distinct dynamics. We also uncovered different dynamics of local field potential under various brain states in layer 2&3 and layer 5&6. Interestingly, ketamine administration induced high gamma oscillations in layer 2&3 of the RSC, but not layer 5&6. Our results show that excitatory principal cells within RSC layers 2&3 and 5&6 contain multiple physiologically distinct sub-populations, and they are differentially affected by ketamine.

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.

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

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

Quantitative high-throughput population dynamics in continuous-culture by automated microscopy.

PubMed

Merritt, Jason; Kuehn, Seppe

2016-09-12

We present a high-throughput method to measure abundance dynamics in microbial communities sustained in continuous-culture. Our method uses custom epi-fluorescence microscopes to automatically image single cells drawn from a continuously-cultured population while precisely controlling culture conditions. For clonal populations of Escherichia coli our instrument reveals history-dependent resilience and growth rate dependent aggregation.

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.

Modeling oscillations and spiral waves in Dictyostelium populations

NASA Astrophysics Data System (ADS)

Noorbakhsh, Javad; Schwab, David J.; Sgro, Allyson E.; Gregor, Thomas; Mehta, Pankaj

2015-06-01

Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cells and coordinated through cell-to-cell communication. Describing these behaviors requires new mathematical models that can bridge scales—from biochemical networks within individual cells to spatially structured cellular populations. Here we present a family of "multiscale" models for the emergence of spiral waves in the social amoeba Dictyostelium discoideum. Our models exploit new experimental advances that allow for the direct measurement and manipulation of the small signaling molecule cyclic adenosine monophosphate (cAMP) used by Dictyostelium cells to coordinate behavior in cellular populations. Inspired by recent experiments, we model the Dictyostelium signaling network as an excitable system coupled to various preprocessing modules. We use this family of models to study spatially unstructured populations of "fixed" cells by constructing phase diagrams that relate the properties of population-level oscillations to parameters in the underlying biochemical network. We then briefly discuss an extension of our model that includes spatial structure and show how this naturally gives rise to spiral waves. Our models exhibit a wide range of novel phenomena. including a density-dependent frequency change, bistability, and dynamic death due to slow cAMP dynamics. Our modeling approach provides a powerful tool for bridging scales in modeling of Dictyostelium populations.

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

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.

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.

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

Macrophage and T cell dynamics during the development and disintegration of mycobacterial granulomas.

PubMed

Egen, Jackson G; Rothfuchs, Antonio Gigliotti; Feng, Carl G; Winter, Nathalie; Sher, Alan; Germain, Ronald N

2008-02-01

Granulomas play a key role in host protection against mycobacterial pathogens, with their breakdown contributing to exacerbated disease. To better understand the initiation and maintenance of these structures, we employed both high-resolution multiplex static imaging and intravital multiphoton microscopy of Mycobacterium bovis BCG-induced liver granulomas. We found that Kupffer cells directly capture blood-borne bacteria and subsequently nucleate formation of a nascent granuloma by recruiting both uninfected liver-resident macrophages and blood-derived monocytes. Within the mature granuloma, these myeloid cell populations formed a relatively immobile cellular matrix that interacted with a highly dynamic effector T cell population. The efficient recruitment of these T cells was highly dependent on TNF-alpha-derived signals, which also maintained the granuloma structure through preferential effects on uninfected macrophage populations. By characterizing the migration of both innate and adaptive immune cells throughout the process of granuloma development, these studies provide a new perspective on the cellular events involved in mycobacterial containment and escape.

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

PubMed Central

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-01-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays. PMID:27452732

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.

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

NASA Astrophysics Data System (ADS)

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-07-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays.

Cell population modelling of yeast glycolytic oscillations.

PubMed Central

Henson, Michael A; Müller, Dirk; Reuss, Matthias

2002-01-01

We investigated a cell-population modelling technique in which the population is constructed from an ensemble of individual cell models. The average value or the number distribution of any intracellular property captured by the individual cell model can be calculated by simulation of a sufficient number of individual cells. The proposed method is applied to a simple model of yeast glycolytic oscillations where synchronization of the cell population is mediated by the action of an excreted metabolite. We show that smooth one-dimensional distributions can be obtained with ensembles comprising 1000 individual cells. Random variations in the state and/or structure of individual cells are shown to produce complex dynamic behaviours which cannot be adequately captured by small ensembles. PMID:12206713

Collective dynamics of cell migration and cell rearrangements

NASA Astrophysics Data System (ADS)

Kabla, Alexandre

Understanding multicellular processes such as embryo development or cancer metastasis requires to decipher the contributions of local cell autonomous behaviours and long range interactions with the tissue environment. A key question in this context concerns the emergence of large scale coordination in cell behaviours, a requirement for collective cell migration or convergent extension. I will present a few examples where physical and mechanical aspects play a significant role in driving tissue scale dynamics.

Spatial heterogeneity in the carrying capacity of sika deer in Japan.

PubMed

Iijima, Hayato; Ueno, Mayumi

2016-06-09

Carrying capacity is 1 driver of wildlife population dynamics. Although in previous studies carrying capacity was considered to be a fixed entity, it may differ among locations due to environmental variation. The factors underlying variability in carrying capacity, however, have rarely been examined. Here, we investigated spatial heterogeneity in the carrying capacity of Japanese sika deer ( Cervus nippon ) from 2005 to 2014 in Yamanashi Prefecture, central Japan (mesh with grid cells of 5.5×4.6 km) by state-space modeling. Both carrying capacity and density dependence differed greatly among cells. Estimated carrying capacities ranged from 1.34 to 98.4 deer/km 2 . According to estimated population dynamics, grid cells with larger proportions of artificial grassland and deciduous forest were subject to lower density dependence and higher carrying capacity. We conclude that population dynamics of ungulates may vary spatially through spatial variation in carrying capacity and that the density level for controlling ungulate abundance should be based on the current density level relative to the carrying capacity for each area.

Wavelet Imaging on Multiple Scales (WIMS) reveals focal adhesion distributions, dynamics and coupling between actomyosin bundle stability

PubMed Central

Toplak, Tim; Palmieri, Benoit; Juanes-García, Alba; Vicente-Manzanares, Miguel; Grant, Martin; Wiseman, Paul W.

2017-01-01

We introduce and use Wavelet Imaging on Multiple Scales (WIMS) as an improvement to fluorescence correlation spectroscopy to measure physical processes and features that occur across multiple length scales. In this study, wavelet transforms of cell images are used to characterize molecular dynamics at the cellular and subcellular levels (i.e. focal adhesions). We show the usefulness of the technique by applying WIMS to an image time series of a migrating osteosarcoma cell expressing fluorescently labelled adhesion proteins, which allows us to characterize different components of the cell ranging from optical resolution scale through to focal adhesion and whole cell size scales. Using WIMS we measured focal adhesion numbers, orientation and cell boundary velocities for retraction and protrusion. We also determine the internal dynamics of individual focal adhesions undergoing assembly, disassembly or elongation. Thus confirming as previously shown, WIMS reveals that the number of adhesions and the area of the protruding region of the cell are strongly correlated, establishing a correlation between protrusion size and adhesion dynamics. We also apply this technique to characterize the behavior of adhesions, actin and myosin in Chinese hamster ovary cells expressing a mutant form of myosin IIB (1935D) that displays decreased filament stability and impairs front-back cell polarity. We find separate populations of actin and myosin at each adhesion pole for both the mutant and wild type form. However, we find these populations move rapidly inwards toward one another in the mutant case in contrast to the cells that express wild type myosin IIB where those populations remain stationary. Results obtained with these two systems demonstrate how WIMS has the potential to reveal novel correlations between chosen parameters that belong to different scales. PMID:29049414

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

Population dynamics during cell proliferation and neuronogenesis in the developing murine neocortex

NASA Technical Reports Server (NTRS)

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

2002-01-01

During the development of the neocortex, cell proliferation occurs in two specialized zones adjacent to the lateral ventricle. One of these zones, the ventricular zone, produces most of the neurons of the neocortex. The proliferating population that resides in the ventricular zone is a pseudostratified ventricular epithelium (PVE) that looks uniform in routine histological preparations, but is, in fact, an active and dynamically changing population. In the mouse, over the course of a 6-day period, the PVE produces approximately 95% of the neurons of the adult neocortex. During this time, the cell cycle of the PVE population lengthens from about 8 h to over 18 h and the progenitor population passes through a total of 11 cell cycles. This 6-day, 11-cell cycle period comprises the "neuronogenetic interval" (NI). At each passage through the cell cycle, the proportion of daughter cells that exit the cell cycle (Q cells) increases from 0 at the onset of the NI to 1 at the end of the NI. The proportion of daughter cells that re-enter the cell cycle (P cells) changes in a complementary fashion from 1 at the onset of the NI to 0 at the end of the NI. This set of systematic changes in the cell cycle and the output from the proliferative population of the PVE allows a quantitative and mathematical treatment of the expansion of the PVE and the growth of the cortical plate that nicely accounts for the observed expansion and growth of the developing neocortex. In addition, we show that the cells produced during a 2-h window of development during specific cell cycles reside in a specific set of laminae in the adult cortex, but that the distributions of the output from consecutive cell cycles overlap. These dynamic events occur in all areas of the PVE underlying the neocortex, but there is a gradient of maturation that begins in the rostrolateral neocortex near the striatotelencephalic junction and which spreads across the surface of the neocortex over a period of 24-36 h. The presence of the gradient across the hemisphere is a possible source of positional information that could be exploited during development to establish the areal borders that characterize the adult neocortex.

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.

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

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

Consumption, supply and transport: self-organization without direct communication

NASA Technical Reports Server (NTRS)

Kessler, J. O.

1996-01-01

Swimming bacteria of the species Bacillus subtilis require and consume oxygen. In static liquid cultures the cells' swimming behaviour leads them to accumulate up oxygen concentration gradients generated by consumption and supply. Since the density of bacterial cells exceeds that of the fluid in which they live, fluid regions where cells have accumulated are denser than depleted regions. These density variations cause convection. The fluid motion is dynamically maintained by the swimming of the cells toward regions of attraction: the air-fluid interface and the fluctuating advecting attractors, gradients of oxygen concentration that are embedded in the convecting fluid. Because of the fluid dynamical conservation laws, these complex physical and biological factors generate patterns ordered over distances > 10000 bacterial cell diameters. The convection enhances long-range transport and mixing of oxygen, cells and extracellular products by orders of magnitude. Thus, through the interplay of physical and biological factors, a population of undifferentiated selfish cells creates functional dynamic patterns. Populations of bacteria that have organised themselves into regularly patterned regions of vigorous convection and varying cell concentration interact with their environment as if they were one purposeful, coherent multicellular individual. The mathematical and experimental ingredients of these remarkable phenomena are presented here.

Flow cytometric cell cycle analysis of muscle precursor cells cultured within 3D scaffolds in a perfusion bioreactor.

PubMed

Flaibani, Marina; Luni, Camilla; Sbalchiero, Elisa; Elvassore, Nicola

2009-01-01

It has been widely demonstrated that perfusion bioreactors improve in vitro three-dimensional (3D) cultures in terms of high cell density and uniformity of cell distribution; however, the studies reported in literature were primarily based on qualitative analysis (histology, immunofluorescent staining) or on quantitative data averaged on the whole population (DNA assay, PCR). Studies on the behavior, in terms of cell cycle, of a cell population growing in 3D scaffolds in static or dynamic conditions are still absent. In this work, a perfusion bioreactor suitable to culture C(2)C(12) muscle precursor cells within 3D porous collagen scaffolds was designed and developed and a method based on flowcytometric analyses for analyzing the cell cycle in the cell population was established. Cells were extracted by enzymatic digestion of the collagen scaffolds after 4, 7, and 10 days of culture, and flow cytometric live/dead and cell cycle analyses were performed with Propidium Iodide. A live/dead assay was used for validating the method for cell extraction and staining. Moreover, to investigate spatial heterogeneity of the cell population under perfusion conditions, two stacked scaffolds in the 3D domain, of which only the upstream layer was seeded, were analyzed separately. All results were compared with those obtained from static 3D cultures. The live/dead assay revealed the presence of less than 20% of dead cells, which did not affect the cell cycle analysis. Cell cycle analyses highlighted the increment of cell fractions in proliferating phases (S/G(2)/M) owing to medium perfusion in long-term cultures. After 7-10 days, the percentage of proliferating cells was 8-12% for dynamic cultures and 3-5% for the static controls. A higher fraction of proliferating cells was detected in the downstream scaffold. From a general perspective, this method provided data with a small standard deviation and detected the differences between static and dynamic cultures and between upper and lower scaffolds. Our methodology can be extended to other cell types to investigate the influence of 3D culture conditions on the expression of other relevant cell markers.

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.

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

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.

Cholesterol Modulates CFTR Confinement in the Plasma Membrane of Primary Epithelial Cells

PubMed Central

Abu-Arish, Asmahan; Pandzic, Elvis; Goepp, Julie; Matthes, Elizabeth; Hanrahan, John W.; Wiseman, Paul W.

2015-01-01

The cystic fibrosis transmembrane conductance regulator (CFTR) is a plasma-membrane anion channel that, when mutated, causes the disease cystic fibrosis. Although CFTR has been detected in a detergent-resistant membrane fraction prepared from airway epithelial cells, suggesting that it may partition into cholesterol-rich membrane microdomains (lipid rafts), its compartmentalization has not been demonstrated in intact cells and the influence of microdomains on CFTR lateral mobility is unknown. We used live-cell imaging, spatial image correlation spectroscopy, and k-space image correlation spectroscopy to examine the aggregation state of CFTR and its dynamics both within and outside microdomains in the plasma membrane of primary human bronchial epithelial cells. These studies were also performed during treatments that augment or deplete membrane cholesterol. We found two populations of CFTR molecules that were distinguishable based on their dynamics at the cell surface. One population showed confinement and had slow dynamics that were highly cholesterol dependent. The other, more abundant population was less confined and diffused more rapidly. Treatments that deplete the membrane of cholesterol caused the confined fraction and average number of CFTR molecules per cluster to decrease. Elevating cholesterol had the opposite effect, increasing channel aggregation and the fraction of channels displaying confinement, consistent with CFTR recruitment into cholesterol-rich microdomains with dimensions below the optical resolution limit. Viral infection caused the nanoscale microdomains to fuse into large platforms and reduced CFTR mobility. To our knowledge, these results provide the first biophysical evidence for multiple CFTR populations and have implications for regulation of their surface expression and channel function. PMID:26153705

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 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.

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.

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.

Single Cell Proteolytic Assays to Investigate Cancer Clonal Heterogeneity and Cell Dynamics Using an Efficient Cell Loading Scheme

NASA Astrophysics Data System (ADS)

Chen, Yu-Chih; Cheng, Yu-Heng; Ingram, Patrick; Yoon, Euisik

2016-06-01

Proteolytic degradation of the extracellular matrix (ECM) is critical in cancer invasion, and recent work suggests that heterogeneous cancer populations cooperate in this process. Despite the importance of cell heterogeneity, conventional proteolytic assays measure average activity, requiring thousands of cells and providing limited information about heterogeneity and dynamics. Here, we developed a microfluidic platform that provides high-efficiency cell loading and simple valveless isolation, so the proteolytic activity of a small sample (10-100 cells) can be easily characterized. Combined with a single cell derived (clonal) sphere formation platform, we have successfully demonstrated the importance of microenvironmental cues for proteolytic activity and also investigated the difference between clones. Furthermore, the platform allows monitoring single cells at multiple time points, unveiling different cancer cell line dynamics in proteolytic activity. The presented tool facilitates single cell proteolytic analysis using small samples, and our findings illuminate the heterogeneous and dynamic nature of proteolytic activity.

Dynamic Pedagogy for Effective Training of Youths in Cell Phone Maintenance

ERIC Educational Resources Information Center

Ogbuanya, T. C.; Jimoh, Bakare

2015-01-01

The study determined dynamic pedagogies for effective training of youths in cell phone maintenance. The study was conducted in Enugu State of Nigeria. Four research questions were developed while four null hypotheses formulated were tested at 0.05 level of significance. A survey research design was adopted for the study. The population for the…

Spatial heterogeneity in the carrying capacity of sika deer in Japan

PubMed Central

Iijima, Hayato; Ueno, Mayumi

2016-01-01

Abstract Carrying capacity is 1 driver of wildlife population dynamics. Although in previous studies carrying capacity was considered to be a fixed entity, it may differ among locations due to environmental variation. The factors underlying variability in carrying capacity, however, have rarely been examined. Here, we investigated spatial heterogeneity in the carrying capacity of Japanese sika deer ( Cervus nippon ) from 2005 to 2014 in Yamanashi Prefecture, central Japan (mesh with grid cells of 5.5×4.6 km) by state-space modeling. Both carrying capacity and density dependence differed greatly among cells. Estimated carrying capacities ranged from 1.34 to 98.4 deer/km 2 . According to estimated population dynamics, grid cells with larger proportions of artificial grassland and deciduous forest were subject to lower density dependence and higher carrying capacity. We conclude that population dynamics of ungulates may vary spatially through spatial variation in carrying capacity and that the density level for controlling ungulate abundance should be based on the current density level relative to the carrying capacity for each area. PMID:29692470

Kupffer Cells Undergo Fundamental Changes during the Development of Experimental NASH and Are Critical in Initiating Liver Damage and Inflammation

PubMed Central

Reid, D. T.; Reyes, J. L.; McDonald, B. A.; Vo, T.; Reimer, R. A.; Eksteen, B.

2016-01-01

Non-alcoholic fatty liver disease has become the leading liver disease in North America and is associated with the progressive inflammatory liver disease non-alcoholic steatohepatitis (NASH). Considerable effort has been made to understand the role of resident and recruited macrophage populations in NASH however numerous questions remain. Our goal was to characterize the dynamic changes in liver macrophages during the initiation of NASH in a murine model. Using the methionine-choline deficient diet we found that liver-resident macrophages, Kupffer cells were lost early in disease onset followed by a robust infiltration of Ly-6C+ monocyte-derived macrophages that retained a dynamic phenotype. Genetic profiling revealed distinct patterns of inflammatory gene expression between macrophage subsets. Only early depletion of liver macrophages using liposomal clodronate prevented the development of NASH in mice suggesting that Kupffer cells are critical for the orchestration of inflammation during experimental NASH. Increased understanding of these dynamics may allow us to target potentially harmful populations whilst promoting anti-inflammatory or restorative populations to ultimately guide the development of effective treatment strategies. PMID:27454866

Noise facilitates transcriptional control under dynamic inputs.

PubMed

Kellogg, Ryan A; Tay, Savaş

2015-01-29

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Infection Dynamics of Coexisting Beta- and Gammaproteobacteria in the Nested Endosymbiotic System of Mealybugs▿

PubMed Central

Kono, Marie; Koga, Ryuichi; Shimada, Masakazu; Fukatsu, Takema

2008-01-01

We investigated the infection dynamics of endosymbiotic bacteria in the developmental course of the mealybugs Planococcus kraunhiae and Pseudococcus comstocki. Molecular phylogenetic analyses identified a betaproteobacterium and a gammaproteobacterium from each of the mealybug species. The former bacterium was related to the β-endosymbionts of other mealybugs, i.e., “Candidatus Tremblaya princeps,” and formed a compact clade in the Betaproteobacteria. Meanwhile, the latter bacterium was related to the γ-endosymbionts of other mealybugs but belonged to distinct clades in the Gammaproteobacteria. Whole-mount in situ hybridization confirmed the peculiar nested formation in the endosymbiotic system of the mealybugs: the β-endosymbiont cells were present in the cytoplasm of the bacteriocytes, and the γ-endosymbiont cells were located in the β-endosymbiont cells. In nymphal and female development, a large oval bacteriome consisting of a number of bacteriocytes was present in the abdomen, wherein the endosymbionts were harbored. In male development, strikingly, the bacteriome progressively degenerated in prepupae and pupae and became almost unrecognizable in adult males. In the degeneration process, the γ-endosymbionts disappeared more rapidly than the β-endosymbionts did. Quantitative PCR analyses revealed that (i) the population dynamics of the endosymbionts in female development reflected the reproductive activity of the insects, (ii) the population dynamics of the endosymbionts were strikingly different between female development and male development, (iii) the endosymbiont populations drastically decreased in male development, and (iv) the γ-endosymbiont populations decreased more rapidly than the β-endosymbiont populations in male development. Possible mechanisms underlying the uncoupled regulation of the β- and γ-endosymbiont populations are discussed in relation to the establishment and evolution of this unique prokaryote-prokaryote endosymbiotic system. PMID:18469124

The Physics of Cancer

NASA Astrophysics Data System (ADS)

La Porta, Caterina A. M.; Zapperi, Stefano

2017-04-01

Preface; 1. Introduction to the cell; 2. The biology of cancer; 3. A modeling toolbox for cancer growth; 4. Vascular hydrodynamics and tumor angiogenesis; 5. Cancer stem cells and the population dynamics of tumors; 6. Biomechanics of cancer; 7. Cancer cell migration; 8. Chromosome and chromatin dynamics in cancer; 9. Control of tumor growth by the immune system; 10. Pharmacological approaches: old and new; 11. Outlook on the physics of cancer: a new interdisciplinary area; References; Index.

The unforeseen challenge: from genotype-to-phenotype in cell populations

NASA Astrophysics Data System (ADS)

Braun, Erez

2015-02-01

Biological cells present a paradox, in that they show simultaneous stability and flexibility, allowing them to adapt to new environments and to evolve over time. The emergence of stable cell states depends on genotype-to-phenotype associations, which essentially reflect the organization of gene regulatory modes. The view taken here is that cell-state organization is a dynamical process in which the molecular disorder manifests itself in a macroscopic order. The genome does not determine the ordered cell state; rather, it participates in this process by providing a set of constraints on the spectrum of regulatory modes, analogous to boundary conditions in physical dynamical systems. We have developed an experimental framework, in which cell populations are exposed to unforeseen challenges; novel perturbations they had not encountered before along their evolutionary history. This approach allows an unbiased view of cell dynamics, uncovering the potential of cells to evolve and develop adapted stable states. In the last decade, our experiments have revealed a coherent set of observations within this framework, painting a picture of the living cell that in many ways is not aligned with the conventional one. Of particular importance here, is our finding that adaptation of cell-state organization is essentially an efficient exploratory dynamical process rather than one founded on random mutations. Based on our framework, a set of concepts underlying cell-state organization—exploration evolving by global, non-specific, dynamics of gene activity—is presented here. These concepts have significant consequences for our understanding of the emergence and stabilization of a cell phenotype in diverse biological contexts. Their implications are discussed for three major areas of biological inquiry: evolution, cell differentiation and cancer. There is currently no unified theoretical framework encompassing the emergence of order, a stable state, in the living cell. Hopefully, the integrated picture described here will provide a modest contribution towards a physics theory of the cell.

The nature and nurture of cell heterogeneity: accounting for macrophage gene-environment interactions with single-cell RNA-Seq.

PubMed

Wills, Quin F; Mellado-Gomez, Esther; Nolan, Rory; Warner, Damien; Sharma, Eshita; Broxholme, John; Wright, Benjamin; Lockstone, Helen; James, William; Lynch, Mark; Gonzales, Michael; West, Jay; Leyrat, Anne; Padilla-Parra, Sergi; Filippi, Sarah; Holmes, Chris; Moore, Michael D; Bowden, Rory

2017-01-07

Single-cell RNA-Seq can be a valuable and unbiased tool to dissect cellular heterogeneity, despite the transcriptome's limitations in describing higher functional phenotypes and protein events. Perhaps the most important shortfall with transcriptomic 'snapshots' of cell populations is that they risk being descriptive, only cataloging heterogeneity at one point in time, and without microenvironmental context. Studying the genetic ('nature') and environmental ('nurture') modifiers of heterogeneity, and how cell population dynamics unfold over time in response to these modifiers is key when studying highly plastic cells such as macrophages. We introduce the programmable Polaris™ microfluidic lab-on-chip for single-cell sequencing, which performs live-cell imaging while controlling for the culture microenvironment of each cell. Using gene-edited macrophages we demonstrate how previously unappreciated knockout effects of SAMHD1, such as an altered oxidative stress response, have a large paracrine signaling component. Furthermore, we demonstrate single-cell pathway enrichments for cell cycle arrest and APOBEC3G degradation, both associated with the oxidative stress response and altered proteostasis. Interestingly, SAMHD1 and APOBEC3G are both HIV-1 inhibitors ('restriction factors'), with no known co-regulation. As single-cell methods continue to mature, so will the ability to move beyond simple 'snapshots' of cell populations towards studying the determinants of population dynamics. By combining single-cell culture, live-cell imaging, and single-cell sequencing, we have demonstrated the ability to study cell phenotypes and microenvironmental influences. It's these microenvironmental components - ignored by standard single-cell workflows - that likely determine how macrophages, for example, react to inflammation and form treatment resistant HIV reservoirs.

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.

Differential dynamics of spatial attention, position, and color coding within the parietofrontal network.

PubMed

Astrand, Elaine; Ibos, Guilhem; Duhamel, Jean-René; Ben Hamed, Suliann

2015-02-18

Despite an ever growing knowledge on how parietal and prefrontal neurons encode low-level spatial and color information or higher-level information, such as spatial attention, an understanding of how these cortical regions process neuronal information at the population level is still missing. A simple assumption would be that the function and temporal response profiles of these neuronal populations match that of its constituting individual cells. However, several recent studies suggest that this is not necessarily the case and that the single-cell approach overlooks dynamic changes in how information is distributed over the neuronal population. Here, we use a time-resolved population pattern analysis to explore how spatial position, spatial attention and color information are differentially encoded and maintained in the macaque monkey prefrontal (frontal eye fields) and parietal cortex (lateral intraparietal area). Overall, our work brings about three novel observations. First, we show that parietal and prefrontal populations operate in two distinct population regimens for the encoding of sensory and cognitive information: a stationary mode and a dynamic mode. Second, we show that the temporal dynamics of a heterogeneous neuronal population brings about complementary information to that of its functional subpopulations. Thus, both need to be investigated in parallel. Last, we show that identifying the neuronal configuration in which a neuronal population encodes given information can serve to reveal this same information in a different context. All together, this work challenges common views on neural coding in the parietofrontal network. Copyright © 2015 the authors 0270-6474/15/353174-16$15.00/0.

Dynamics of Bacterial Gene Regulatory Networks.

PubMed

Shis, David L; Bennett, Matthew R; Igoshin, Oleg A

2018-05-20

The ability of bacterial cells to adjust their gene expression program in response to environmental perturbation is often critical for their survival. Recent experimental advances allowing us to quantitatively record gene expression dynamics in single cells and in populations coupled with mathematical modeling enable mechanistic understanding on how these responses are shaped by the underlying regulatory networks. Here, we review how the combination of local and global factors affect dynamical responses of gene regulatory networks. Our goal is to discuss the general principles that allow extrapolation from a few model bacteria to less understood microbes. We emphasize that, in addition to well-studied effects of network architecture, network dynamics are shaped by global pleiotropic effects and cell physiology.

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

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.

Host–virus dynamics and subcellular controls of cell fate in a natural coccolithophore population

PubMed Central

Vardi, Assaf; Haramaty, Liti; Van Mooy, Benjamin A. S.; Fredricks, Helen F.; Kimmance, Susan A.; Larsen, Aud; Bidle, Kay D.

2012-01-01

Marine viruses are major evolutionary and biogeochemical drivers in marine microbial foodwebs. However, an in-depth understanding of the cellular mechanisms and the signal transduction pathways mediating host–virus interactions during natural bloom dynamics has remained elusive. We used field-based mesocosms to examine the “arms race” between natural populations of the coccolithophore Emiliania huxleyi and its double-stranded DNA-containing coccolithoviruses (EhVs). Specifically, we examined the dynamics of EhV infection and its regulation of cell fate over the course of bloom development and demise using a diverse suite of molecular tools and in situ fluorescent staining to target different levels of subcellular resolution. We demonstrate the concomitant induction of reactive oxygen species, caspase-specific activity, metacaspase expression, and programmed cell death in response to the accumulation of virus-derived glycosphingolipids upon infection of natural E. huxleyi populations. These subcellular responses to viral infection simultaneously resulted in the enhanced production of transparent exopolymer particles, which can facilitate aggregation and stimulate carbon flux. Our results not only corroborate the critical role for glycosphingolipids and programmed cell death in regulating E. huxleyi–EhV interactions, but also elucidate promising molecular biomarkers and lipid-based proxies for phytoplankton host–virus interactions in natural systems. PMID:23134731

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.

Cholesterol modulates CFTR confinement in the plasma membrane of primary epithelial cells.

PubMed

Abu-Arish, Asmahan; Pandzic, Elvis; Goepp, Julie; Matthes, Elizabeth; Hanrahan, John W; Wiseman, Paul W

2015-07-07

The cystic fibrosis transmembrane conductance regulator (CFTR) is a plasma-membrane anion channel that, when mutated, causes the disease cystic fibrosis. Although CFTR has been detected in a detergent-resistant membrane fraction prepared from airway epithelial cells, suggesting that it may partition into cholesterol-rich membrane microdomains (lipid rafts), its compartmentalization has not been demonstrated in intact cells and the influence of microdomains on CFTR lateral mobility is unknown. We used live-cell imaging, spatial image correlation spectroscopy, and k-space image correlation spectroscopy to examine the aggregation state of CFTR and its dynamics both within and outside microdomains in the plasma membrane of primary human bronchial epithelial cells. These studies were also performed during treatments that augment or deplete membrane cholesterol. We found two populations of CFTR molecules that were distinguishable based on their dynamics at the cell surface. One population showed confinement and had slow dynamics that were highly cholesterol dependent. The other, more abundant population was less confined and diffused more rapidly. Treatments that deplete the membrane of cholesterol caused the confined fraction and average number of CFTR molecules per cluster to decrease. Elevating cholesterol had the opposite effect, increasing channel aggregation and the fraction of channels displaying confinement, consistent with CFTR recruitment into cholesterol-rich microdomains with dimensions below the optical resolution limit. Viral infection caused the nanoscale microdomains to fuse into large platforms and reduced CFTR mobility. To our knowledge, these results provide the first biophysical evidence for multiple CFTR populations and have implications for regulation of their surface expression and channel function. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Analysis of allelic expression patterns in clonal somatic cells by single-cell RNA-seq.

PubMed

Reinius, Björn; Mold, Jeff E; Ramsköld, Daniel; Deng, Qiaolin; Johnsson, Per; Michaëlsson, Jakob; Frisén, Jonas; Sandberg, Rickard

2016-11-01

Cellular heterogeneity can emerge from the expression of only one parental allele. However, it has remained controversial whether, or to what degree, random monoallelic expression of autosomal genes (aRME) is mitotically inherited (clonal) or stochastic (dynamic) in somatic cells, particularly in vivo. Here we used allele-sensitive single-cell RNA-seq on clonal primary mouse fibroblasts and freshly isolated human CD8 + T cells to dissect clonal and dynamic monoallelic expression patterns. Dynamic aRME affected a considerable portion of the cells' transcriptomes, with levels dependent on the cells' transcriptional activity. Notably, clonal aRME was detected, but it was surprisingly scarce (<1% of genes) and mainly affected the most weakly expressed genes. Consequently, the overwhelming majority of aRME occurs transiently within individual cells, and patterns of aRME are thus primarily scattered throughout somatic cell populations rather than, as previously hypothesized, confined to patches of clonally related cells.

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.

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

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.

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.

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.

Spontaneous emergence of large-scale cell cycle synchronization in amoeba colonies

NASA Astrophysics Data System (ADS)

Segota, Igor; Boulet, Laurent; Franck, David; Franck, Carl

2014-06-01

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. Here we show that cell populations grown on a substrate 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.

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.

Games of multicellularity.

PubMed

Kaveh, Kamran; Veller, Carl; Nowak, Martin A

2016-08-21

Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of allelic expression patterns in clonal somatic cells by single-cell RNA-seq

PubMed Central

Ramsköld, Daniel; Deng, Qiaolin; Johnsson, Per; Michaëlsson, Jakob; Frisén, Jonas; Sandberg, Rickard

2016-01-01

Cellular heterogeneity can emerge from the expression of only one parental allele. However, it has remained controversial whether, or to what degree, random monoallelic expression of autosomal genes (aRME) is mitotically inherited (clonal) or stochastic (dynamic) in somatic cells, particularly in vivo. Here, we used allele-sensitive single-cell RNA-seq on clonal primary mouse fibroblasts and in vivo human CD8+ T-cells to dissect clonal and dynamic monoallelic expression patterns. Dynamic aRME affected a considerable portion of the cells’ transcriptomes, with levels dependent on the cells’ transcriptional activity. Importantly, clonal aRME was detected but was surprisingly scarce (<1% of genes) and affected mainly the most low-expressed genes. Consequently, the overwhelming portion of aRME occurs transiently within individual cells and patterns of aRME are thus primarily scattered throughout somatic cell populations rather than, as previously hypothesized, confined to patches of clonally related cells. PMID:27668657

Dynamic and social behaviors of human pluripotent stem cells.

PubMed

Phadnis, Smruti M; Loewke, Nathan O; Dimov, Ivan K; Pai, Sunil; Amwake, Christine E; Solgaard, Olav; Baer, Thomas M; Chen, Bertha; Reijo Pera, Renee A

2015-09-18

Human pluripotent stem cells (hPSCs) can self-renew or differentiate to diverse cell types, thus providing a platform for basic and clinical applications. However, pluripotent stem cell populations are heterogeneous and functional properties at the single cell level are poorly documented leading to inefficiencies in differentiation and concerns regarding reproducibility and safety. Here, we use non-invasive time-lapse imaging to continuously examine hPSC maintenance and differentiation and to predict cell viability and fate. We document dynamic behaviors and social interactions that prospectively distinguish hPSC survival, self-renewal, and differentiation. Results highlight the molecular role of E-cadherin not only for cell-cell contact but also for clonal propagation of hPSCs. Results indicate that use of continuous time-lapse imaging can distinguish cellular heterogeneity with respect to pluripotency as well as a subset of karyotypic abnormalities whose dynamic properties were monitored.

Dynamic and social behaviors of human pluripotent stem cells

PubMed Central

Phadnis, Smruti M.; Loewke, Nathan O.; Dimov, Ivan K.; Pai, Sunil; Amwake, Christine E.; Solgaard, Olav; Baer, Thomas M.; Chen, Bertha; Pera, Renee A. Reijo

2015-01-01

Human pluripotent stem cells (hPSCs) can self-renew or differentiate to diverse cell types, thus providing a platform for basic and clinical applications. However, pluripotent stem cell populations are heterogeneous and functional properties at the single cell level are poorly documented leading to inefficiencies in differentiation and concerns regarding reproducibility and safety. Here, we use non-invasive time-lapse imaging to continuously examine hPSC maintenance and differentiation and to predict cell viability and fate. We document dynamic behaviors and social interactions that prospectively distinguish hPSC survival, self-renewal, and differentiation. Results highlight the molecular role of E-cadherin not only for cell-cell contact but also for clonal propagation of hPSCs. Results indicate that use of continuous time-lapse imaging can distinguish cellular heterogeneity with respect to pluripotency as well as a subset of karyotypic abnormalities whose dynamic properties were monitored. PMID:26381699

Placental immune state shifts with gestational age.

PubMed

Lewis, Emma L; Sierra, Luz-Jeannette; Barila, Guillermo O; Brown, Amy G; Porrett, Paige M; Elovitz, Michal A

2018-06-01

Placental immunologic functions are implicated in both the maintenance of a healthy pregnancy and the pathogenesis of obstetric complications. Immune populations at the maternal-fetal interface are hypothesized to support fetomaternal tolerance, defend the fetus from infection, and contribute to labor initiation. Despite the many potential roles of placental immune cells in normal and abnormal pregnancy, little is known about placental immune population dynamics over gestation, particularly near parturition. A daily placental immune cell census was established in a murine model by flow cytometry from mid to late gestation and compared to the maternal systemic immune census. Shifts in the placental immune state were further characterized through cytokine ELISAs. The placental immune census is distinct from the maternal systemic immune census, although the cells are primarily maternal in origin. Near term parturition, the placenta contains fewer CD11c-positive myeloid cells and regulatory T cells, and there is a concurrent decrease in placental IL-9 and IL-35. The immune profile of the placenta demonstrates a decrease in both regulatory immune cell types and cytokines late in gestation. Establishing the placental immune population dynamics over a healthy pregnancy will allow future investigation of placental immune cells during abnormal pregnancy. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

An Emerging Allee Effect Is Critical for Tumor Initiation and Persistence

PubMed Central

Böttger, Katrin; Hatzikirou, Haralambos; Voss-Böhme, Anja; Cavalcanti-Adam, Elisabetta Ada; Herrero, Miguel A.; Deutsch, Andreas

2015-01-01

Tumor cells develop different strategies to cope with changing microenvironmental conditions. A prominent example is the adaptive phenotypic switching between cell migration and proliferation. While it has been shown that the migration-proliferation plasticity influences tumor spread, it remains unclear how this particular phenotypic plasticity affects overall tumor growth, in particular initiation and persistence. To address this problem, we formulate and study a mathematical model of spatio-temporal tumor dynamics which incorporates the microenvironmental influence through a local cell density dependence. Our analysis reveals that two dynamic regimes can be distinguished. If cell motility is allowed to increase with local cell density, any tumor cell population will persist in time, irrespective of its initial size. On the contrary, if cell motility is assumed to decrease with respect to local cell density, any tumor population below a certain size threshold will eventually extinguish, a fact usually termed as Allee effect in ecology. These results suggest that strategies aimed at modulating migration are worth to be explored as alternatives to those mainly focused at keeping tumor proliferation under control. PMID:26335202

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.

Simulating Heterogeneous Tumor Cell Populations

PubMed Central

Bar-Sagi, Dafna; Mishra, Bud

2016-01-01

Certain tumor phenomena, like metabolic heterogeneity and local stable regions of chronic hypoxia, signify a tumor’s resistance to therapy. Although recent research has shed light on the intracellular mechanisms of cancer metabolic reprogramming, little is known about how tumors become metabolically heterogeneous or chronically hypoxic, namely the initial conditions and spatiotemporal dynamics that drive these cell population conditions. To study these aspects, we developed a minimal, spatially-resolved simulation framework for modeling tissue-scale mixed populations of cells based on diffusible particles the cells consume and release, the concentrations of which determine their behavior in arbitrarily complex ways, and on stochastic reproduction. We simulate cell populations that self-sort to facilitate metabolic symbiosis, that grow according to tumor-stroma signaling patterns, and that give rise to stable local regions of chronic hypoxia near blood vessels. We raise two novel questions in the context of these results: (1) How will two metabolically symbiotic cell subpopulations self-sort in the presence of glucose, oxygen, and lactate gradients? We observe a robust pattern of alternating striations. (2) What is the proper time scale to observe stable local regions of chronic hypoxia? We observe the stability is a function of the balance of three factors related to O2—diffusion rate, local vessel release rate, and viable and hypoxic tumor cell consumption rate. We anticipate our simulation framework will help researchers design better experiments and generate novel hypotheses to better understand dynamic, emergent whole-tumor behavior. PMID:28030620

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.

Dynamic equilibrium of reconstituting hematopoietic stem cell populations.

PubMed

O'Quigley, John

2010-12-01

Clonal dominance in hematopoietic stem cell populations is an important question of interest but not one we can directly answer. Any estimates are based on indirect measurement. For marked populations, we can equate empirical and theoretical moments for binomial sampling, in particular we can use the well-known formula for the sampling variation of a binomial proportion. The empirical variance itself cannot always be reliably estimated and some caution is needed. We describe the difficulties here and identify ready solutions which only require appropriate use of variance-stabilizing transformations. From these we obtain estimators for the steady state, or dynamic equilibrium, of the number of hematopoietic stem cells involved in repopulating the marrow. The calculations themselves are not too involved. We give the distribution theory for the estimator as well as simple approximations for practical application. As an illustration, we rework on data recently gathered to address the question as to whether or not reconstitution of marrow grafts in the clinical setting might be considered to be oligoclonal.

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

Dynamic acoustic field activated cell separation (DAFACS).

PubMed

Skotis, G D; Cumming, D R S; Roberts, J N; Riehle, M O; Bernassau, A L

2015-02-07

Advances in diagnostics, cell and stem cell technologies drive the development of application-specific tools for cell and particle separation. Acoustic micro-particle separation offers a promising avenue for high-throughput, label-free, high recovery, cell and particle separation and isolation in regenerative medicine. Here, we demonstrate a novel approach utilizing a dynamic acoustic field that is capable of separating an arbitrary size range of cells. We first demonstrate the method for the separation of particles with different diameters between 6 and 45 μm and secondly particles of different densities in a heterogeneous medium. The dynamic acoustic field is then used to separate dorsal root ganglion cells. The shearless, label-free and low damage characteristics make this method of manipulation particularly suited for biological applications. Advantages of using a dynamic acoustic field for the separation of cells include its inherent safety and biocompatibility, the possibility to operate over large distances (centimetres), high purity (ratio of particle population, up to 100%), and high efficiency (ratio of separated particles over total number of particles to separate, up to 100%).

Visualization and tracking of tumour extracellular vesicle delivery and RNA translation using multiplexed reporters

PubMed Central

Lai, Charles P.; Kim, Edward Y.; Badr, Christian E.; Weissleder, Ralph; Mempel, Thorsten R.; Tannous, Bakhos A.; Breakefield, Xandra O.

2015-01-01

Accurate spatiotemporal assessment of extracellular vesicle (EV) delivery and cargo RNA translation requires specific and robust live-cell imaging technologies. Here we engineer optical reporters to label multiple EV populations for visualization and tracking of tumour EV release, uptake and exchange between cell populations both in culture and in vivo. Enhanced green fluorescence protein (EGFP) and tandem dimer Tomato (tdTomato) were fused at NH2-termini with a palmitoylation signal (PalmGFP, PalmtdTomato) for EV membrane labelling. To monitor EV-RNA cargo, transcripts encoding PalmtdTomato were tagged with MS2 RNA binding sequences and detected by co-expression of bacteriophage MS2 coat protein fused with EGFP. By multiplexing fluorescent and bioluminescent EV membrane reporters, we reveal the rapid dynamics of both EV uptake and translation of EV-delivered cargo mRNAs in cancer cells that occurred within 1-hour post-horizontal transfer between cells. These studies confirm that EV-mediated communication is dynamic and multidirectional between cells with delivery of functional mRNA. PMID:25967391

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.

Comparative Analysis of Gender Differences in the HIV-1 Infection Dynamics

NASA Astrophysics Data System (ADS)

Ballesteros, P.; Estrada, J. L.; Barriga, G.; Molinar, F.; Hernández, M. C.; Huerta, L.; Cocho, G.; Villarreal, C.

2006-09-01

We have performed a retrospective study of the HIV-1 viral load and CD4 T-cell counts in blood plasma of more than 3000 Mexican patients. We found that women had consistently lower viral loads than men for CD4 T-cell counts higher than 50 cells/μL and higher viral loads when CD4 T-cell counts were at most 50 cells/μL. Our results show the same pattern as the one reported in studies performed in European and North American populations. We present theoretical predictions of viral load dynamics during highly active antiretroviral therapy taking into account gender differences.

Phenotypically heterogeneous populations in spatially heterogeneous environments

NASA Astrophysics Data System (ADS)

Patra, Pintu; Klumpp, Stefan

2014-03-01

The spatial expansion of a population in a nonuniform environment may benefit from phenotypic heterogeneity with interconverting subpopulations using different survival strategies. We analyze the crossing of an antibiotic-containing environment by a bacterial population consisting of rapidly growing normal cells and slow-growing, but antibiotic-tolerant persister cells. The dynamics of crossing is characterized by mean first arrival times and is found to be surprisingly complex. It displays three distinct regimes with different scaling behavior that can be understood based on an analytical approximation. Our results suggest that a phenotypically heterogeneous population has a fitness advantage in nonuniform environments and can spread more rapidly than a homogeneous population.

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

Social interaction in synthetic and natural microbial communities.

PubMed

Xavier, Joao B

2011-04-12

Social interaction among cells is essential for multicellular complexity. But how do molecular networks within individual cells confer the ability to interact? And how do those same networks evolve from the evolutionary conflict between individual- and population-level interests? Recent studies have dissected social interaction at the molecular level by analyzing both synthetic and natural microbial populations. These studies shed new light on the role of population structure for the evolution of cooperative interactions and revealed novel molecular mechanisms that stabilize cooperation among cells. New understanding of populations is changing our view of microbial processes, such as pathogenesis and antibiotic resistance, and suggests new ways to fight infection by exploiting social interaction. The study of social interaction is also challenging established paradigms in cancer evolution and immune system dynamics. Finding similar patterns in such diverse systems suggests that the same 'social interaction motifs' may be general to many cell populations.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

A Molecular Census of Arcuate Hypothalamus and Median Eminence Cell Types

PubMed Central

Campbell, John N.; Macosko, Evan Z.; Fenselau, Henning; Pers, Tune H.; Lyubetskaya, Anna; Tenen, Danielle; Goldman, Melissa; Verstegen, Anne M.J.; Resch, Jon M.; McCarroll, Steven A.; Rosen, Evan D.; Lowell, Bradford B.; Tsai, Linus

2017-01-01

The hypothalamic arcuate-median eminence complex (Arc-ME) controls energy balance, fertility, and growth through molecularly distinct cell types, many of which remain unknown. To catalog cell types in an unbiased way, we profiled gene expression in 20,921 individual cells in and around the adult mouse Arc-ME using Drop-seq. We identify 50 transcriptionally distinct Arc-ME cell populations, including a rare tanycyte population at the Arc-ME diffusion barrier, a novel leptin-sensing neuronal population, multiple AgRP and POMC subtypes, and an orexigenic somatostatin neuronal population. We extended Drop-seq to detect dynamic expression changes across relevant physiological perturbations, revealing cell type-specific responses to energy status, including distinctly responsive subtypes of AgRP and POMC neurons. Finally, integrating our data with human GWAS data implicates two previously unknown neuronal subtypes in the genetic control of obesity. This resource will accelerate biological discovery by providing insights into molecular and cell type diversity from which function can be inferred. PMID:28166221

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.

Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics.

PubMed

Farlik, Matthias; Sheffield, Nathan C; Nuzzo, Angelo; Datlinger, Paul; Schönegger, Andreas; Klughammer, Johanna; Bock, Christoph

2015-03-03

Methods for single-cell genome and transcriptome sequencing have contributed to our understanding of cellular heterogeneity, whereas methods for single-cell epigenomics are much less established. Here, we describe a whole-genome bisulfite sequencing (WGBS) assay that enables DNA methylation mapping in very small cell populations (μWGBS) and single cells (scWGBS). Our assay is optimized for profiling many samples at low coverage, and we describe a bioinformatic method that analyzes collections of single-cell methylomes to infer cell-state dynamics. Using these technological advances, we studied epigenomic cell-state dynamics in three in vitro models of cellular differentiation and pluripotency, where we observed characteristic patterns of epigenome remodeling and cell-to-cell heterogeneity. The described method enables single-cell analysis of DNA methylation in a broad range of biological systems, including embryonic development, stem cell differentiation, and cancer. It can also be used to establish composite methylomes that account for cell-to-cell heterogeneity in complex tissue samples. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing.

PubMed

Lee, Mei-Chong Wendy; Lopez-Diaz, Fernando J; Khan, Shahid Yar; Tariq, Muhammad Akram; Dayn, Yelena; Vaske, Charles Joseph; Radenbaugh, Amie J; Kim, Hyunsung John; Emerson, Beverly M; Pourmand, Nader

2014-11-04

The acute cellular response to stress generates a subpopulation of reversibly stress-tolerant cells under conditions that are lethal to the majority of the population. Stress tolerance is attributed to heterogeneity of gene expression within the population to ensure survival of a minority. We performed whole transcriptome sequencing analyses of metastatic human breast cancer cells subjected to the chemotherapeutic agent paclitaxel at the single-cell and population levels. Here we show that specific transcriptional programs are enacted within untreated, stressed, and drug-tolerant cell groups while generating high heterogeneity between single cells within and between groups. We further demonstrate that drug-tolerant cells contain specific RNA variants residing in genes involved in microtubule organization and stabilization, as well as cell adhesion and cell surface signaling. In addition, the gene expression profile of drug-tolerant cells is similar to that of untreated cells within a few doublings. Thus, single-cell analyses reveal the dynamics of the stress response in terms of cell-specific RNA variants driving heterogeneity, the survival of a minority population through generation of specific RNA variants, and the efficient reconversion of stress-tolerant cells back to normalcy.

Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing

PubMed Central

Lee, Mei-Chong Wendy; Lopez-Diaz, Fernando J.; Khan, Shahid Yar; Tariq, Muhammad Akram; Dayn, Yelena; Vaske, Charles Joseph; Radenbaugh, Amie J.; Kim, Hyunsung John; Emerson, Beverly M.; Pourmand, Nader

2014-01-01

The acute cellular response to stress generates a subpopulation of reversibly stress-tolerant cells under conditions that are lethal to the majority of the population. Stress tolerance is attributed to heterogeneity of gene expression within the population to ensure survival of a minority. We performed whole transcriptome sequencing analyses of metastatic human breast cancer cells subjected to the chemotherapeutic agent paclitaxel at the single-cell and population levels. Here we show that specific transcriptional programs are enacted within untreated, stressed, and drug-tolerant cell groups while generating high heterogeneity between single cells within and between groups. We further demonstrate that drug-tolerant cells contain specific RNA variants residing in genes involved in microtubule organization and stabilization, as well as cell adhesion and cell surface signaling. In addition, the gene expression profile of drug-tolerant cells is similar to that of untreated cells within a few doublings. Thus, single-cell analyses reveal the dynamics of the stress response in terms of cell-specific RNA variants driving heterogeneity, the survival of a minority population through generation of specific RNA variants, and the efficient reconversion of stress-tolerant cells back to normalcy. PMID:25339441

Dynamic Properties of the Alkaline Vesicle Population at Hippocampal Synapses

PubMed Central

Röther, Mareike; Brauner, Jan M.; Ebert, Katrin; Welzel, Oliver; Jung, Jasmin; Bauereiss, Anna; Kornhuber, Johannes; Groemer, Teja W.

2014-01-01

In compensatory endocytosis, scission of vesicles from the plasma membrane to the cytoplasm is a prerequisite for intravesicular reacidification and accumulation of neurotransmitter molecules. Here, we provide time-resolved measurements of the dynamics of the alkaline vesicle population which appears upon endocytic retrieval. Using fast perfusion pH-cycling in live-cell microscopy, synapto-pHluorin expressing rat hippocampal neurons were electrically stimulated. We found that the relative size of the alkaline vesicle population depended significantly on the electrical stimulus size: With increasing number of action potentials the relative size of the alkaline vesicle population expanded. In contrast to that, increasing the stimulus frequency reduced the relative size of the population of alkaline vesicles. Measurement of the time constant for reacification and calculation of the time constant for endocytosis revealed that both time constants were variable with regard to the stimulus condition. Furthermore, we show that the dynamics of the alkaline vesicle population can be predicted by a simple mathematical model. In conclusion, here a novel methodical approach to analyze dynamic properties of alkaline vesicles is presented and validated as a convenient method for the detection of intracellular events. Using this method we show that the population of alkaline vesicles is highly dynamic and depends both on stimulus strength and frequency. Our results implicate that determination of the alkaline vesicle population size may provide new insights into the kinetics of endocytic retrieval. PMID:25079223

Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process

PubMed Central

Boullu, Loïs; Morin, Valérie; Vallin, Elodie; Guillemin, Anissa; Papili Gao, Nan; Cosette, Jérémie; Arnaud, Ophélie; Kupiec, Jean-Jacques; Espinasse, Thibault

2016-01-01

In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker (DNB) theory. In addition, we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation. In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time, we used Shannon entropy as a measure of the heterogeneity. Entropy values showed a significant increase in the first 8 h of the differentiation process, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. Moreover, we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a “simple” program that all cells execute identically but results from the dynamical behavior of the underlying molecular network. PMID:28027290

Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process.

PubMed

Richard, Angélique; Boullu, Loïs; Herbach, Ulysse; Bonnafoux, Arnaud; Morin, Valérie; Vallin, Elodie; Guillemin, Anissa; Papili Gao, Nan; Gunawan, Rudiyanto; Cosette, Jérémie; Arnaud, Ophélie; Kupiec, Jean-Jacques; Espinasse, Thibault; Gonin-Giraud, Sandrine; Gandrillon, Olivier

2016-12-01

In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker (DNB) theory. In addition, we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation. In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time, we used Shannon entropy as a measure of the heterogeneity. Entropy values showed a significant increase in the first 8 h of the differentiation process, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. Moreover, we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a "simple" program that all cells execute identically but results from the dynamical behavior of the underlying molecular network.

Analyzing the dynamics of cell cycle processes from fixed samples through ergodic principles

PubMed Central

Wheeler, Richard John

2015-01-01

Tools to analyze cyclical cellular processes, particularly the cell cycle, are of broad value for cell biology. Cell cycle synchronization and live-cell time-lapse observation are widely used to analyze these processes but are not available for many systems. Simple mathematical methods built on the ergodic principle are a well-established, widely applicable, and powerful alternative analysis approach, although they are less widely used. These methods extract data about the dynamics of a cyclical process from a single time-point “snapshot” of a population of cells progressing through the cycle asynchronously. Here, I demonstrate application of these simple mathematical methods to analysis of basic cyclical processes—cycles including a division event, cell populations undergoing unicellular aging, and cell cycles with multiple fission (schizogony)—as well as recent advances that allow detailed mapping of the cell cycle from continuously changing properties of the cell such as size and DNA content. This includes examples using existing data from mammalian, yeast, and unicellular eukaryotic parasite cell biology. Through the ongoing advances in high-throughput cell analysis by light microscopy, electron microscopy, and flow cytometry, these mathematical methods are becoming ever more important and are a powerful complementary method to traditional synchronization and time-lapse cell cycle analysis methods. PMID:26543196

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.

Competition-colonization dynamics: An ecology approach to quasispecies dynamics and virulence evolution in RNA viruses.

PubMed

Ojosnegros, Samuel; Beerenwinkel, Niko; Domingo, Esteban

2010-07-01

A single and purified clone of foot-and-mouth disease virus diversified in cell culture into two subpopulations that were genetically distinct. The subpopulation with higher virulence was a minority and was suppressed by the dominant but less virulent one. These two populations follow the competitioncolonization dynamics described in ecology. Virulent viruses can be regarded as colonizers because they killed the cells faster and they spread faster. The attenuated subpopulation resembles competitors because of its higher replication efficiency in coinfected cells. Our results suggest a new model for the evolution of virulence which is based on interactions between components of the quasispecies. Competition between viral mutants takes place at two levels, intracellular competition and competition for new cells. The two strategies are subjected to densitydependent selection.

Self-organization in Balanced State Networks by STDP and Homeostatic Plasticity

PubMed Central

Effenberger, Felix; Jost, Jürgen; Levina, Anna

2015-01-01

Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network. PMID:26335425

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.

Flow cytometric immunofluorescence of rat anterior pituitary cells

NASA Technical Reports Server (NTRS)

Hatfield, J. Michael; Hymer, W. C.

1985-01-01

A flow cytometric immunofluorescence technique was developed for the quantification of growth hormone, prolactin, and luteinizing hormone producing cells. The procedure is based on indirect-immunofluorescence of intracellular hormone using an EPICS V cell sorter and can objectively count 50,000 cells in about 3 minutes. It can be used to study the dynamics of pituitary cell populations under various physiological and pharmacological conditions.

[Dynamics of the population structure of the Escherichia coli recombinant strain during continuous culture].

PubMed

Popova, L Iu; Lutskaia, N I; Bogucharov, A A; Bril'kov, A V; Pechurkin, N S

1992-01-01

The populational structure of the Escherichia coli strain Z905 containing the recombinant plasmid with the phenotype AprLux+ was studied in chemostat. It was shown that the stability of the ratio of plasmid containing cells and cells without plasmids depends in the first place on the presence of the selective factor (ampicillin) in the medium and on the sources of carbon and energy limiting growth.

Bacterial Cheating Limits the Evolution of Antibiotic Resistance

NASA Astrophysics Data System (ADS)

Yurtsev, Eugene; Xiao Chao, Hui; Datta, Manoshi; Artemova, Tatiana; Gore, Jeff

2012-02-01

The emergence of antibiotic resistance in bacteria is a significant health concern. Bacteria can gain resistance to the antibiotic ampicillin by acquiring a plasmid carrying the gene beta-lactamase, which inactivates the antibiotic. This inactivation may represent a cooperative behavior, as the entire bacterial population benefits from removal of the antibiotic. The presence of a cooperative mechanism of resistance suggests that a cheater strain - which does not contribute to breaking down the antibiotic - may be able to take advantage of resistant cells. We find experimentally that a ``sensitive'' bacterial strain lacking the plasmid conferring resistance can invade a population of resistant bacteria, even in antibiotic concentrations that should kill the sensitive strain. We use a simple model in conjunction with difference equations to explain the observed population dynamics as a function of cell density and antibiotic concentration. Our experimental difference equations resemble the logistic map, raising the possibility of oscillations or even chaotic dynamics.

Microglial Dynamics During Human Brain Development

PubMed Central

Menassa, David A.; Gomez-Nicola, Diego

2018-01-01

Microglial cells are thought to colonize the human cerebrum between the 4th and 24th gestational weeks. Rodent studies have demonstrated that these cells originate from yolk sac progenitors though it is not clear whether this directly pertains to human development. Our understanding of microglial cell dynamics in the developing human brain comes mostly from postmortem studies demonstrating that the beginning of microglial colonization precedes the appearance of the vasculature, the blood–brain barrier, astrogliogenesis, oligodendrogenesis, neurogenesis, migration, and myelination of the various brain areas. Furthermore, migrating microglial populations cluster by morphology and express differential markers within the developing brain and according to developmental age. With the advent of novel technologies such as RNA-sequencing in fresh human tissue, we are beginning to identify the molecular features of the adult microglial signature. However, this is may not extend to the much more dynamic and rapidly changing antenatal microglial population and this is further complicated by the scarcity of tissue resources. In this brief review, we first describe the various historic schools of thought that had debated the origin of microglial cells while examining the evidence supporting the various theories. We then proceed to examine the evidence we have accumulated on microglial dynamics in the developing human brain, present evidence from rodent studies on the functional role of microglia during development and finally identify limitations for the used approaches in human studies and highlight under investigated questions. PMID:29881376

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 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.

Switch-like reprogramming of gene expression after fusion of multinucleate plasmodial cells of two Physarum polycephalum sporulation mutants

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

Walter, Pauline; Hoffmann, Xenia-Katharina; Ebeling, Britta

2013-05-24

Highlights: •We investigate reprogramming of gene expression in multinucleate single cells. •Cells of two differentiation control mutants are fused. •Fused cells proceed to alternative gene expression patterns. •The population of nuclei damps stochastic fluctuations in gene expression. •Dynamic processes of cellular reprogramming can be observed by repeated sampling of a cell. -- Abstract: Nonlinear dynamic processes involving the differential regulation of transcription factors are considered to impact the reprogramming of stem cells, germ cells, and somatic cells. Here, we fused two multinucleate plasmodial cells of Physarum polycephalum mutants defective in different sporulation control genes while being in different physiological states.more » The resulting heterokaryons established one of two significantly different expression patterns of marker genes while the plasmodial halves that were fused to each other synchronized spontaneously. Spontaneous synchronization suggests that switch-like control mechanisms spread over and finally control the entire plasmodium as a result of cytoplasmic mixing. Regulatory molecules due to the large volume of the vigorously streaming cytoplasm will define concentrations in acting on the population of nuclei and in the global setting of switches. Mixing of a large cytoplasmic volume is expected to damp stochasticity when individual nuclei deliver certain RNAs at low copy number into the cytoplasm. We conclude that spontaneous synchronization, the damping of molecular noise in gene expression by the large cytoplasmic volume, and the option to take multiple macroscopic samples from the same plasmodium provide unique options for studying the dynamics of cellular reprogramming at the single cell level.« less

Microfluidic co-culture platform for investigating osteocyte-osteoclast signalling during fluid shear stress mechanostimulation.

PubMed

Middleton, K; Al-Dujaili, S; Mei, X; Günther, A; You, L

2017-07-05

Bone cells exist in a complex environment where they are constantly exposed to numerous dynamic biochemical and mechanical stimuli. These stimuli regulate bone cells that are involved in various bone disorders, such as osteoporosis. Knowledge of how these stimuli affect bone cells have been utilised to develop various treatments, such as pharmaceuticals, hormone therapy, and exercise. To investigate the role that bone loading has on these disorders in vitro, bone cell mechanotransduction studies are typically performed using parallel plate flow chambers (PPFC). However, these chambers do not allow for dynamic cellular interactions among different cell populations to be investigated. We present a microfluidic approach that exposes different cell populations, which are located at physiologically relevant distances within adjacent channels, to different levels of fluid shear stress, and promotes cell-cell communication between the different channels. We employed this microfluidic system to assess mechanically regulated osteocyte-osteoclast communication. Osteoclast precursors (RAW264.7 cells) responded to cytokine gradients (e.g., RANKL, OPG, PGE-2) developed by both mechanically stimulated (fOCY) and unstimulated (nOCY) osteocyte-like MLO-Y4 cells simultaneously. Specifically, we observed increased osteoclast precursor cell densities and osteoclast differentiation towards nOCY. We also used this system to show an increased mechanoresponse of osteocytes when in co-culture with osteoclasts. We envision broad applicability of the presented approach for microfluidic perfusion co-culture of multiple cell types in the presence of fluid flow stimulation, and as a tool to investigate osteocyte mechanotransduction, as well as bone metastasis extravasation. This system could also be applied to any multi-cell population cross-talk studies that are typically performed using PPFCs (e.g. endothelial cells, smooth muscle cells, and fibroblasts). Copyright © 2017 Elsevier Ltd. All rights reserved.

Population Dynamics of a Lac(-) Strain of Escherichia Coli during Selection for Lactose Utilization

PubMed Central

Foster, P. L.

1994-01-01

During selection for lactose utilization, Lac(+) revertants of FC40, a Lac(-) strain of Escherichia coli, appear at a high rate. Yet, no Lac(+) revertants appear in the absence of lactose, or in its presence if the cells have another, unfulfilled requirement for growth. This study investigates more fully the population dynamics of FC40 when incubated in the absence of a carbon source or when undergoing selection for lactose utilization. In the absence of a carbon source, the viable cell numbers do not change over 6 days. When incubated in liquid lactose medium, Lac(-) cells do not undergo any measurable increase in numbers or in turbidity for at least 2 days. When FC40 is plated on lactose minimum medium in the presence of scavenger cells, the upper limit to the amount of growth of Lac(-) cells during 5 days is one doubling, and there is no evidence for turnover (i.e., a balance between growth and death). The presence of a minority population that could form microcolonies was not detected. The implications of these results, plus the fact that the appearance of Lac(+) revertants during lactose selection is nearly constant with time, are discussed in reference to several models that have been postulated to account for adaptive mutations. PMID:7828809

Internal Disequilibria and Phenotypic Diversification during Replication of Hepatitis C Virus in a Noncoevolving Cellular Environment

PubMed Central

Moreno, Elena; Gallego, Isabel; Gregori, Josep; Lucía-Sanz, Adriana; Soria, María Eugenia; Castro, Victoria; Beach, Nathan M.; Manrubia, Susanna; Quer, Josep; Esteban, Juan Ignacio; Rice, Charles M.; Gómez, Jordi; Gastaminza, Pablo

2017-01-01

ABSTRACT Viral quasispecies evolution upon long-term virus replication in a noncoevolving cellular environment raises relevant general issues, such as the attainment of population equilibrium, compliance with the molecular-clock hypothesis, or stability of the phenotypic profile. Here, we evaluate the adaptation, mutant spectrum dynamics, and phenotypic diversification of hepatitis C virus (HCV) in the course of 200 passages in human hepatoma cells in an experimental design that precluded coevolution of the cells with the virus. Adaptation to the cells was evidenced by increase in progeny production. The rate of accumulation of mutations in the genomic consensus sequence deviated slightly from linearity, and mutant spectrum analyses revealed a complex dynamic of mutational waves, which was sustained beyond passage 100. The virus underwent several phenotypic changes, some of which impacted the virus-host relationship, such as enhanced cell killing, a shift toward higher virion density, and increased shutoff of host cell protein synthesis. Fluctuations in progeny production and failure to reach population equilibrium at the genomic level suggest internal instabilities that anticipate an unpredictable HCV evolution in the complex liver environment. IMPORTANCE Long-term virus evolution in an unperturbed cellular environment can reveal features of virus evolution that cannot be explained by comparing natural viral isolates. In the present study, we investigate genetic and phenotypic changes that occur upon prolonged passage of hepatitis C virus (HCV) in human hepatoma cells in an experimental design in which host cell evolutionary change is prevented. Despite replication in a noncoevolving cellular environment, the virus exhibited internal population disequilibria that did not decline with increased adaptation to the host cells. The diversification of phenotypic traits suggests that disequilibria inherent to viral populations may provide a selective advantage to viruses that can be fully exploited in changing environments. PMID:28275194

Optical dissection of odor information processing in vivo using GCaMPs expressed in specified cell types of the olfactory bulb

PubMed Central

Wachowiak, Matt; Economo, Michael N.; Díaz-Quesada, Marta; Brunert, Daniela; Wesson, Daniel W.; White, John. A.; Rothermel, Markus

2013-01-01

Understanding central processing requires precise monitoring of neural activity across populations of identified neurons in the intact brain. Here we used recently-optimized variants of the genetically-encoded calcium sensor GCaMP (GCaMP3 and GCaMPG5G) to image activity among genetically- and anatomically-defined neuronal populations in the olfactory bulb (OB), including two types of GABA-ergic interneurons (periglomerular (PG) and short axon (SA) cells) and OB output neurons (mitral/tufted (MT) cells) projecting to piriform cortex. We first established that changes in neuronal spiking can be accurately related to GCaMP fluorescence changes via a simple quantitative relationship over a large dynamic range. We next used in vivo two-photon imaging from individual neurons and epifluorescence signals reflecting population-level activity to investigate the spatiotemporal representation of odorants across these neuron types in anesthetized and awake mice. Under anesthesia, individual PG and SA cells showed temporally simple responses and little spontaneous activity, while MT cells were spontaneously active and showed diverse temporal responses. At the population level, response patterns of PG, SA and MT cells were surprisingly similar to those imaged from sensory inputs, with shared odorant-specific topography across the dorsal OB and inhalation-coupled temporal dynamics. During wakefulness, PG and SA cell responses increased in magnitude but remained temporally simple while those of MT cells changed to complex spatiotemporal patterns reflecting restricted excitation and widespread inhibition. These results point to multiple circuit elements with distinct roles in transforming odor representations in the OB and provide a framework for further dissecting early olfactory processing using optical and genetic tools. PMID:23516293

Arsenite inhibits mitotic division and perturbs spindle dynamics in HeLa S3 cells.

PubMed

Huang, S C; Lee, T C

1998-05-01

Arsenical compounds, known to be human carcinogens, were shown to disturb cell cycle progression and induce cytogenetic alterations in a variety of cell systems. We report here that a 24 h treatment of arsenite induced mitotic accumulation in human cell lines. HeLa S3 and KB cells were most susceptible: 35% of the total cell population was arrested at the mitotic stage after treatment with 5 microM sodium arsenite in HeLa S3 cells and after 10 microM in KB cells. Under a microscope, we observed abnormal mitotic figures in arsenite-arrested mitotic cells, including deranged chromosome congression, elongated polar distance of mitotic spindle, and enhanced microtubule immunofluorescence. The spindle microtubules of arsenite-arrested mitotic cells were more resistant to nocodazole-induced dissolution than those of control mitotic cells. According to turbidity assay, arsenite at concentrations below 100 microM significantly enhanced polymerization of tubulins. Since spindle dynamics play a crucial role in mitotic progression, our results suggest that arsenite-induced mitotic arrest may be due to arsenite's effects on attenuation of spindle dynamics.

T Cell Dynamic Activation and Functional Analysis in Nanoliter Droplet Microarray.

PubMed

Sarkar, Saheli; Motwani, Vinny; Sabhachandani, Pooja; Cohen, Noa; Konry, Tania

2015-06-01

Characterization of the heterogeneity in immune reactions requires assessing dynamic single cell responses as well as interactions between the various immune cell subsets. Maturation and activation of effector cells is regulated by cell contact-dependent and soluble factor-mediated paracrine signalling. Currently there are few methods available that allow dynamic investigation of both processes simultaneously without physically constraining non-adherent cells and eliminating crosstalk from neighboring cell pairs. We describe here a microfluidic droplet microarray platform that permits rapid functional analysis of single cell responses and co-encapsulation of heterotypic cell pairs, thereby allowing us to evaluate the dynamic activation state of primary T cells. The microfluidic droplet platform enables generation and docking of monodisperse nanoliter volume (0.523 nl) droplets, with the capacity of monitoring a thousand droplets per experiment. Single human T cells were encapsulated in droplets and stimulated on-chip with the calcium ionophore ionomycin. T cells were also co-encapsulated with dendritic cells activated by ovalbumin peptide, followed by dynamic calcium signal monitoring. Ionomycin-stimulated cells depicted fluctuation in calcium signalling compared to control. Both cell populations demonstrated marked heterogeneity in responses. Calcium signalling was observed in T cells immediately following contact with DCs, suggesting an early activation signal. T cells further showed non-contact mediated increase in calcium level, although this response was delayed compared to contact-mediated signals. Our results suggest that this nanoliter droplet array-based microfluidic platform is a promising technique for assessment of heterogeneity in various types of cellular responses, detection of early/delayed signalling events and live cell phenotyping of immune cells.

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.

The type VI secretion system impacts bacterial invasion and population dynamics in a model intestinal microbiota

NASA Astrophysics Data System (ADS)

Logan, Savannah L.; Shields, Drew S.; Hammer, Brian K.; Xavier, Joao B.; Parthasarathy, Raghuveer

Animal gastrointestinal tracts are home to a diverse community of microbes. The mechanisms by which microbial species interact and compete in this dense, physically dynamic space are poorly understood, limiting our understanding of how natural communities are assembled and how different communities could be engineered. Here, we focus on a physical mechanism for competition: the type VI secretion system (T6SS). The T6SS is a syringe-like organelle used by certain bacteria to translocate effector proteins across the cell membranes of target bacterial cells, killing them. Here, we use T6SS+ and T6SS- strains of V. cholerae, the pathogen that causes cholera in humans, and light sheet fluorescence microscopy for in vivo imaging to show that the T6SS provides an advantage to strains colonizing the larval zebrafish gut. Furthermore, we show that T6SS+ bacteria can invade and alter an existing population of a different species in the zebrafish gut, reducing its abundance and changing the form of its population dynamics. This work both demonstrates a mechanism for altering the gut microbiota with an invasive species and explores the processes controlling the stability and dynamics of the gut ecosystem. Research Corporation, Gordon and Betty Moore Foundation, and the Simons Foundation.

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.

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

Consequence of a sudden wind event on the dynamics of a coastal phytoplankton community: an insight into specific population growth rates using a single cell high frequency approach

PubMed Central

Dugenne, Mathilde; Thyssen, Melilotus; Nerini, David; Mante, Claude; Poggiale, Jean-Christophe; Garcia, Nicole; Garcia, Fabrice; Grégori, Gérald J.

2014-01-01

Phytoplankton is a key component in marine ecosystems. It is responsible for most of the marine primary production, particularly in eutrophic lagoons, where it frequently blooms. Because they are very sensitive to their environment, the dynamics of these microbial communities has to be observed over different time scales, however, assessment of short term variability is often out of reach of traditional monitoring methods. To overcome these limitations, we set up a Cytosense automated flow cytometer (Cytobuoy b.v.), designed for high frequency monitoring of phytoplankton composition, abundance, cell size, and pigment content, in one of the largest Mediterranean lagoons, the Berre lagoon (South-Eastern France). During October 2011, it recorded the cell optical properties of 12 groups of pico-, nano-, and microphytoplankton. Daily variations in the cluster optical properties were consistent with individual changes observed using microscopic imaging, during the cell cycle. We therefore used an adaptation of the size-structured matrix population model, developed by Sosik et al. (2003) to process the single cell analysis of the clusters and estimate the division rates of 2 dinoflagellate populations before, during, and after a strong wind event. The increase in the estimated in situ daily cluster growth rates suggest that physiological changes in the cells can prevail over the response of abundance. PMID:25309523

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.

Defining a stem cell hierarchy in the intestine: markers, caveats and controversies

PubMed Central

Smith, Nicholas R.; Gallagher, Alexandra C.

2016-01-01

Abstract The past decade has appreciated rapid advance in identifying the once elusive intestinal stem cell (ISC) populations that fuel the continual renewal of the epithelial layer. This advance was largely driven by identification of novel stem cell marker genes, revealing the existence of quiescent, slowly‐ and active‐cycling ISC populations. However, a critical barrier for translating this knowledge to human health and disease remains elucidating the functional interplay between diverse stem cell populations. Currently, the precise hierarchical and regulatory relationships between these ISC populations are under intense scrutiny. The classical theory of a linear hierarchy, where quiescent and slowly‐cycling stem cells self‐renew but replenish an active‐cycling population, is well established in other rapidly renewing tissues such as the haematopoietic system. Efforts to definitively establish a similar stem cell hierarchy within the intestinal epithelium have yielded conflicting results, been difficult to interpret, and suggest non‐conventional alternatives to a linear hierarchy. While these new and potentially paradigm‐shifting discoveries are intriguing, the field will require development of a number of critical tools, including highly specific stem cell marker genes along with more rigorous experimental methodologies, to delineate the complex cellular relationships within this dynamic organ system. PMID:26864260

Analysis of population structures of the microalga Acutodesmus obliquus during lipid production using multi-dimensional single-cell analysis.

PubMed

Sandmann, Michael; Schafberg, Michaela; Lippold, Martin; Rohn, Sascha

2018-04-19

Microalgae bear a great potential to produce lipids for biodiesel, feed, or even food applications. To understand the still not well-known single-cell dynamics during lipid production in microalgae, a novel single-cell analytical technology was applied to study a well-established model experiment. Multidimensional single-cell dynamics were investigated with a non-supervised image analysis technique that utilizes data from epi-fluorescence microscopy. Reliability of this technique was successfully proven via reference analysis. The technique developed was used to determine cell size, chlorophyll amount, neutral lipid amount, and deriving properties on a single-cellular level in cultures of the biotechnologically promising alga Acutodesmus obliquus. The results illustrated a high correlation between cell size and chlorophyll amount, but a very low and dynamic correlation between cell size, lipid amount, and lipid density. During growth conditions under nitrogen starvation, cells with low chlorophyll content tend to start the lipid production first and the cell suspension differentiated in two subpopulations with significantly different lipid contents. Such quantitative characterization of single-cell dynamics of lipid synthesizing algae was done for the first time and the potential of such simple technology is highly relevant to other biotechnological applications and to deeper investigate the process of microalgal lipid accumulation.

The Z-cad dual fluorescent sensor detects dynamic changes between the epithelial and mesenchymal cellular states.

PubMed

Toneff, M J; Sreekumar, A; Tinnirello, A; Hollander, P Den; Habib, S; Li, S; Ellis, M J; Xin, L; Mani, S A; Rosen, J M

2016-06-17

The epithelial to mesenchymal transition (EMT) has been implicated in metastasis and therapy resistance of carcinomas and can endow cancer cells with cancer stem cell (CSC) properties. The ability to detect cancer cells that are undergoing or have completed EMT has typically relied on the expression of cell surface antigens that correlate with an EMT/CSC phenotype. Alternatively these cells may be permanently marked through Cre-mediated recombination or through immunostaining of fixed cells. The EMT process is dynamic, and these existing methods cannot reveal such changes within live cells. The development of fluorescent sensors that mirror the dynamic EMT state by following the expression of bona fide EMT regulators in live cells would provide a valuable new tool for characterizing EMT. In addition, these sensors will allow direct observation of cellular plasticity with respect to the epithelial/mesenchymal state to enable more effective studies of EMT in cancer and development. We generated a lentiviral-based, dual fluorescent reporter system, designated as the Z-cad dual sensor, comprising destabilized green fluorescent protein containing the ZEB1 3' UTR and red fluorescent protein driven by the E-cadherin (CDH1) promoter. Using this sensor, we robustly detected EMT and mesenchymal to epithelial transition (MET) in breast cancer cells by flow cytometry and fluorescence microscopy. Importantly, we observed dynamic changes in cellular populations undergoing MET. Additionally, we used the Z-cad sensor to identify and isolate minor subpopulations of cells displaying mesenchymal properties within a population comprising predominately epithelial-like cells. The Z-cad dual sensor identified cells with CSC-like properties more effectively than either the ZEB1 3' UTR or E-cadherin sensor alone. The Z-cad dual sensor effectively reports the activities of two factors critical in determining the epithelial/mesenchymal state of carcinoma cells. The ability of this stably integrating dual sensor system to detect dynamic fluctuations between these two states through live cell imaging offers a significant improvement over existing methods and helps facilitate the study of EMT/MET plasticity in response to different stimuli and in cancer pathogenesis. Finally, the versatile Z-cad sensor can be adapted to a variety of in vitro or in vivo systems to elucidate whether EMT/MET contributes to normal and disease phenotypes.

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.

Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

PubMed

Jothi, Raja; Balaji, S; Wuster, Arthur; Grochow, Joshua A; Gsponer, Jörg; Przytycka, Teresa M; Aravind, L; Babu, M Madan

2009-01-01

Although several studies have provided important insights into the general principles of biological networks, the link between network organization and the genome-scale dynamics of the underlying entities (genes, mRNAs, and proteins) and its role in systems behavior remain unclear. Here we show that transcription factor (TF) dynamics and regulatory network organization are tightly linked. By classifying TFs in the yeast regulatory network into three hierarchical layers (top, core, and bottom) and integrating diverse genome-scale datasets, we find that the TFs have static and dynamic properties that are similar within a layer and different across layers. At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs. Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation. We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells.

PubMed

Andrews, J O; Conway, W; Cho, W -K; Narayanan, A; Spille, J -H; Jayanth, N; Inoue, T; Mullen, S; Thaler, J; Cissé, I I

2018-05-09

We present qSR, an analytical tool for the quantitative analysis of single molecule based super-resolution data. The software is created as an open-source platform integrating multiple algorithms for rigorous spatial and temporal characterizations of protein clusters in super-resolution data of living cells. First, we illustrate qSR using a sample live cell data of RNA Polymerase II (Pol II) as an example of highly dynamic sub-diffractive clusters. Then we utilize qSR to investigate the organization and dynamics of endogenous RNA Polymerase I (Pol I) in live human cells, throughout the cell cycle. Our analysis reveals a previously uncharacterized transient clustering of Pol I. Both stable and transient populations of Pol I clusters co-exist in individual living cells, and their relative fraction vary during cell cycle, in a manner correlating with global gene expression. Thus, qSR serves to facilitate the study of protein organization and dynamics with very high spatial and temporal resolutions directly in live cell.

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.

Amniotic-Fluid Stem Cells: Growth Dynamics and Differentiation Potential after a CD-117-Based Selection Procedure

PubMed Central

Arnhold, S.; Glüer, S.; Hartmann, K.; Raabe, O.; Addicks, K.; Wenisch, S.; Hoopmann, M.

2011-01-01

Amniotic fluid (AF) has become an interesting source of fetal stem cells. However, AF contains heterogeneous and multiple, partially differentiated cell types. After isolation from the amniotic fluid, cells were characterized regarding their morphology and growth dynamics. They were sorted by magnetic associated cell sorting using the surface marker CD 117. In order to show stem cell characteristics such as pluripotency and to evaluate a possible therapeutic application of these cells, AF fluid-derived stem cells were differentiated along the adipogenic, osteogenic, and chondrogenic as well as the neuronal lineage under hypoxic conditions. Our findings reveal that magnetic associated cell sorting (MACS) does not markedly influence growth characteristics as demonstrated by the generation doubling time. There was, however, an effect regarding an altered adipogenic, osteogenic, and chondrogenic differentiation capacity in the selected cell fraction. In contrast, in the unselected cell population neuronal differentiation is enhanced. PMID:21437196

Growth dynamics of cancer cell colonies and their comparison with noncancerous cells

NASA Astrophysics Data System (ADS)

Huergo, M. A. C.; Pasquale, M. A.; González, P. H.; Bolzán, A. E.; Arvia, A. J.

2012-01-01

The two-dimensional (2D) growth dynamics of HeLa (cervix cancer) cell colonies was studied following both their growth front and the pattern morphology evolutions utilizing large population colonies exhibiting linearly and radially spreading fronts. In both cases, the colony profile fractal dimension was df=1.20±0.05 and the growth fronts displaced at the constant velocity 0.90±0.05 μm min-1. Colonies showed changes in both cell morphology and average size. As time increased, the formation of large cells at the colony front was observed. Accordingly, the heterogeneity of the colony increased and local driving forces that set in began to influence the dynamics of the colony front. The dynamic scaling analysis of rough colony fronts resulted in a roughness exponent α = 0.50±0.05, a growth exponent β = 0.32±0.04, and a dynamic exponent z=1.5±0.2. The validity of this set of scaling exponents extended from a lower cutoff lc≈60 μm upward, and the exponents agreed with those predicted by the standard Kardar-Parisi-Zhang continuous equation. HeLa data were compared with those previously reported for Vero cell colonies. The value of df and the Kardar-Parisi-Zhang-type 2D front growth dynamics were similar for colonies of both cell lines. This indicates that the cell colony growth dynamics is independent of the genetic background and the tumorigenic nature of the cells. However, one can distinguish some differences between both cell lines during the growth of colonies that may result from specific cooperative effects and the nature of each biosystem.

A deterministic and stochastic model for the system dynamics of tumor-immune responses to chemotherapy

NASA Astrophysics Data System (ADS)

Liu, Xiangdong; Li, Qingze; Pan, Jianxin

2018-06-01

Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.

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

Cell fate determination dynamics in bacteria

NASA Astrophysics Data System (ADS)

Kuchina, Anna; Espinar, Lorena; Cagatay, Tolga; Garcia-Ojalvo, Jordi; Suel, Gurol

2010-03-01

The fitness of an organism depends on many processes that serve the purpose to adapt to changing environment in a robust and coordinated fashion. One example of such process is cellular fate determination. In the presence of a variety of alternative responses each cell adopting a particular fate represents a ``choice'' that must be tightly regulated to ensure the best survival strategy for the population taking into account the broad range of possible environmental challenges. We investigated this problem in the model organism B.Subtilis which under stress conditions differentiates terminally into highly resistant spores or initiates an alternative transient state of competence. The dynamics underlying cell fate choice remains largely unknown. We utilize quantitative fluorescent microscopy to track the activities of genes involved in these responses on a single-cell level. We explored the importance of temporal interactions between competing cell fates by re- engineering the differentiation programs. I will discuss how the precise dynamics of cellular ``decision-making'' governed by the corresponding biological circuits may enable cells to adjust to diverse environments and determine survival.

Heterogeneous fates and dynamic rearrangement of regenerative epidermis-derived cells during zebrafish fin regeneration.

PubMed

Shibata, Eri; Ando, Kazunori; Murase, Emiko; Kawakami, Atsushi

2018-04-13

The regenerative epidermis (RE) is a specialized tissue that plays an essential role in tissue regeneration. However, the fate of the RE during and after regeneration is unknown. In this study, we performed Cre- loxP -mediated cell fate tracking and revealed the fates of a major population of the RE cells that express fibronectin 1b ( fn1b ) during zebrafish fin regeneration. Our study showed that these RE cells are mainly recruited from the inter-ray epidermis, and that they follow heterogeneous cell fates. Early recruited cells contribute to initial wound healing and soon disappear by apoptosis, while the later recruited cells contribute to the regenerated epidermis. Intriguingly, many of these cells are also expelled from the regenerated tissue by a dynamic caudal movement of the epidermis over time, and in turn the loss of epidermal cells is replenished by a global self-replication of basal and suprabasal cells in fin. De-differentiation of non-basal epidermal cells into the basal epidermal cells did not occur during regeneration. Overall, our study reveals the heterogeneous fates of RE cells and a dynamic rearrangement of the epidermis during and after regeneration. © 2018. Published by The Company of Biologists Ltd.

Direct observation of frequency modulated transcription in single cells using light activation

PubMed Central

Larson, Daniel R; Fritzsch, Christoph; Sun, Liang; Meng, Xiuhau; Lawrence, David S; Singer, Robert H

2013-01-01

Single-cell analysis has revealed that transcription is dynamic and stochastic, but tools are lacking that can determine the mechanism operating at a single gene. Here we utilize single-molecule observations of RNA in fixed and living cells to develop a single-cell model of steroid-receptor mediated gene activation. We determine that steroids drive mRNA synthesis by frequency modulation of transcription. This digital behavior in single cells gives rise to the well-known analog dose response across the population. To test this model, we developed a light-activation technology to turn on a single steroid-responsive gene and follow dynamic synthesis of RNA from the activated locus. DOI: http://dx.doi.org/10.7554/eLife.00750.001 PMID:24069527

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

Kleiner, J.B.; Amiel, D.; Harwood, F.L.

A rabbit model for anterior cruciate ligament (ACL) reconstruction using autogenous patellar tendon was utilized to study the early events of autograft cellular dynamics. Biochemical, autoradiographic, histological, and vascular injection techniques demonstrated that the native autograft cell population rapidly necroses. This repopulation occurs without a vascular contribution; cells entering the autograft are reliant upon synovial fluid nutrition.

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.

Quantitative time-resolved chemoproteomics reveals that stable O-GlcNAc regulates box C/D snoRNP biogenesis

PubMed Central

Qin, Wei; Lv, Pinou; Fan, Xinqi; Quan, Baiyi; Zhu, Yuntao; Qin, Ke; Chen, Ying; Wang, Chu

2017-01-01

O-linked GlcNAcylation (O-GlcNAcylation), a ubiquitous posttranslational modification on intracellular proteins, is dynamically regulated in cells. To analyze the turnover dynamics of O-GlcNAcylated proteins, we developed a quantitative time-resolved O-linked GlcNAc proteomics (qTOP) strategy based on metabolic pulse-chase labeling with an O-GlcNAc chemical reporter and stable isotope labeling with amino acids in cell culture (SILAC). Applying qTOP, we quantified the turnover rates of 533 O-GlcNAcylated proteins in NIH 3T3 cells and discovered that about 14% exhibited minimal removal of O-GlcNAc or degradation of protein backbones. The stability of those hyperstable O-GlcNAcylated proteins was more sensitive to O-GlcNAcylation inhibition compared with the more dynamic populations. Among the hyperstable population were three core proteins of box C/D small nucleolar ribonucleoprotein complexes (snoRNPs): fibrillarin (FBL), nucleolar protein 5A (NOP56), and nucleolar protein 5 (NOP58). We showed that O-GlcNAcylation stabilized these proteins and was essential for snoRNP assembly. Blocking O-GlcNAcylation on FBL altered the 2′-O-methylation of rRNAs and impaired cancer cell proliferation and tumor formation in vivo. PMID:28760965

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

PubMed

Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

2016-01-01

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

Dynamic single-cell NAD(P)H measurement reveals oscillatory metabolism throughout the E. coli cell division cycle.

PubMed

Zhang, Zheng; Milias-Argeitis, Andreas; Heinemann, Matthias

2018-02-01

Recent work has shown that metabolism between individual bacterial cells in an otherwise isogenetic population can be different. To investigate such heterogeneity, experimental methods to zoom into the metabolism of individual cells are required. To this end, the autofluoresence of the redox cofactors NADH and NADPH offers great potential for single-cell dynamic NAD(P)H measurements. However, NAD(P)H excitation requires UV light, which can cause cell damage. In this work, we developed a method for time-lapse NAD(P)H imaging in single E. coli cells. Our method combines a setup with reduced background emission, UV-enhanced microscopy equipment and optimized exposure settings, overall generating acceptable NAD(P)H signals from single cells, with minimal negative effect on cell growth. Through different experiments, in which we perturb E. coli's redox metabolism, we demonstrated that the acquired fluorescence signal indeed corresponds to NAD(P)H. Using this new method, for the first time, we report that intracellular NAD(P)H levels oscillate along the bacterial cell division cycle. The developed method for dynamic measurement of NAD(P)H in single bacterial cells will be an important tool to zoom into metabolism of individual cells.

The evolution within us

PubMed Central

Cobey, Sarah; Wilson, Patrick; Matsen, Frederick A.

2015-01-01

The B-cell immune response is a remarkable evolutionary system found in jawed vertebrates. B-cell receptors, the membrane-bound form of antibodies, are capable of evolving high affinity to almost any foreign protein. High germline diversity and rapid evolution upon encounter with antigen explain the general adaptability of B-cell populations, but the dynamics of repertoires are less well understood. These dynamics are scientifically and clinically important. After highlighting the remarkable characteristics of naive and experienced B-cell repertoires, especially biased usage of genes encoding the B-cell receptors, we contrast methods of sequence analysis and their attempts to explain patterns of B-cell evolution. These phylogenetic approaches are currently unlinked to explicit models of B-cell competition, which analyse repertoire evolution at the level of phenotype, the affinities and specificities to particular antigenic sites. The models, in turn, suggest how chance, infection history and other factors contribute to different patterns of immunodominance and protection between people. Challenges in rational vaccine design, specifically vaccines to induce broadly neutralizing antibodies to HIV, underscore critical gaps in our understanding of B cells' evolutionary and ecological dynamics. PMID:26194749

Complete Firing-Rate Response of Neurons with Complex Intrinsic Dynamics

PubMed Central

Puelma Touzel, Maximilian; Wolf, Fred

2015-01-01

The response of a neuronal population over a space of inputs depends on the intrinsic properties of its constituent neurons. Two main modes of single neuron dynamics–integration and resonance–have been distinguished. While resonator cell types exist in a variety of brain areas, few models incorporate this feature and fewer have investigated its effects. To understand better how a resonator’s frequency preference emerges from its intrinsic dynamics and contributes to its local area’s population firing rate dynamics, we analyze the dynamic gain of an analytically solvable two-degree of freedom neuron model. In the Fokker-Planck approach, the dynamic gain is intractable. The alternative Gauss-Rice approach lifts the resetting of the voltage after a spike. This allows us to derive a complete expression for the dynamic gain of a resonator neuron model in terms of a cascade of filters on the input. We find six distinct response types and use them to fully characterize the routes to resonance across all values of the relevant timescales. We find that resonance arises primarily due to slow adaptation with an intrinsic frequency acting to sharpen and adjust the location of the resonant peak. We determine the parameter regions for the existence of an intrinsic frequency and for subthreshold and spiking resonance, finding all possible intersections of the three. The expressions and analysis presented here provide an account of how intrinsic neuron dynamics shape dynamic population response properties and can facilitate the construction of an exact theory of correlations and stability of population activity in networks containing populations of resonator neurons. PMID:26720924

Turbulent Dynamics of Epithelial Cell Cultures

NASA Astrophysics Data System (ADS)

Blanch-Mercader, C.; Yashunsky, V.; Garcia, S.; Duclos, G.; Giomi, L.; Silberzan, P.

2018-05-01

We investigate the large length and long time scales collective flows and structural rearrangements within in vitro human bronchial epithelial cell (HBEC) cultures. Activity-driven collective flows result in ensembles of vortices randomly positioned in space. By analyzing a large population of vortices, we show that their area follows an exponential law with a constant mean value and their rotational frequency is size independent, both being characteristic features of the chaotic dynamics of active nematic suspensions. Indeed, we find that HBECs self-organize in nematic domains of several cell lengths. Nematic defects are found at the interface between domains with a total number that remains constant due to the dynamical balance of nucleation and annihilation events. The mean velocity fields in the vicinity of defects are well described by a hydrodynamic theory of extensile active nematics.

Bioreactors to Influence Stem Cell Fate: Augmentation of Mesenchymal Stem Cell Signaling Pathways via Dynamic Culture Systems

PubMed Central

Yeatts, Andrew B.; Choquette, Daniel T.; Fisher, John P.

2012-01-01

Background Mesenchymal stem cells (MSCs) are a promising cell source for bone and cartilage tissue engineering as they can be easily isolated from the body and differentiated into osteoblasts and chondrocytes. A cell based tissue engineering strategy using MSCs often involves the culture of these cells on three-dimensional scaffolds; however the size of these scaffolds and the cell population they can support can be restricted in traditional static culture. Thus dynamic culture in bioreactor systems provides a promising means to culture and differentiate MSCs in vitro. Scope of Review This review seeks to characterize key MSC differentiation signaling pathways and provides evidence as to how dynamic culture is augmenting these pathways. Following an overview of dynamic culture systems, discussion will be provided on how these systems can effectively modify and maintain important culture parameters including oxygen content and shear stress. Literature is reviewed for both a highlight of key signaling pathways and evidence for regulation of these signaling pathways via dynamic culture systems. Major Conclusions The ability to understand how these culture systems are affecting MSC signaling pathways could lead to a shear or oxygen regime to direct stem cell differentiation. In this way the efficacy of in vitro culture and differentiation of MSCs on three-dimensional scaffolds could be greatly increased. General Significance Bioreactor systems have the ability to control many key differentiation stimuli including mechanical stress and oxygen content. The further integration of cell signaling investigations within dynamic culture systems will lead to a quicker realization of the promise of tissue engineering and regenerative medicine. PMID:22705676

Network dynamics underlying the formation of sparse, informative representations in the hippocampus.

PubMed

Karlsson, Mattias P; Frank, Loren M

2008-12-24

During development, activity-dependent processes increase the specificity of neural responses to stimuli, but the role that this type of process plays in adult plasticity is unclear. We examined the dynamics of hippocampal activity as animals learned about new environments to understand how neural selectivity changes with experience. Hippocampal principal neurons fire when the animal is located in a particular subregion of its environment, and in any given environment the hippocampal representation is sparse: less than half of the neurons in areas CA1 and CA3 are active whereas the rest are essentially silent. Here we show that different dynamics govern the evolution of this sparsity in CA1 and upstream area CA3. CA1, but not CA3, produces twice as many spikes in novel compared with familiar environments. This high rate firing continues during sharp wave ripple events in a subsequent rest period. The overall CA1 population rate declines and the number of active cells decreases as the environment becomes familiar and task performance improves, but the decline in rate is not uniform across neurons. Instead, the activity of cells with initial peak spatial rates above approximately 12 Hz is enhanced, whereas the activity of cells with lower initial peak rates is suppressed. The result of these changes is that the active CA1 population comes to consist of a relatively small group of cells with strong spatial tuning. This process is not evident in CA3, indicating that a region-specific and long timescale process operates in CA1 to create a sparse, spatially informative population of neurons.

Micro-proteomics with iterative data analysis: Proteome analysis in C. elegans at the single worm level.

PubMed

Bensaddek, Dalila; Narayan, Vikram; Nicolas, Armel; Murillo, Alejandro Brenes; Gartner, Anton; Kenyon, Cynthia J; Lamond, Angus I

2016-02-01

Proteomics studies typically analyze proteins at a population level, using extracts prepared from tens of thousands to millions of cells. The resulting measurements correspond to average values across the cell population and can mask considerable variation in protein expression and function between individual cells or organisms. Here, we report the development of micro-proteomics for the analysis of Caenorhabditis elegans, a eukaryote composed of 959 somatic cells and ∼1500 germ cells, measuring the worm proteome at a single organism level to a depth of ∼3000 proteins. This includes detection of proteins across a wide dynamic range of expression levels (>6 orders of magnitude), including many chromatin-associated factors involved in chromosome structure and gene regulation. We apply the micro-proteomics workflow to measure the global proteome response to heat-shock in individual nematodes. This shows variation between individual animals in the magnitude of proteome response following heat-shock, including variable induction of heat-shock proteins. The micro-proteomics pipeline thus facilitates the investigation of stochastic variation in protein expression between individuals within an isogenic population of C. elegans. All data described in this study are available online via the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd), an open access, searchable database resource. © 2015 The Authors. PROTEOMICS Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development and maintenance of the brain's immune toolkit: Microglia and non-parenchymal brain macrophages.

PubMed

Lopez-Atalaya, Jose P; Askew, Katharine E; Sierra, Amanda; Gomez-Nicola, Diego

2018-06-01

Microglia and non-parenchymal macrophages located in the perivascular space, the meninges and the choroid plexus are independent immune populations that play vital roles in brain development, homeostasis, and tissue healing. Resident macrophages account for a significant proportion of cells in the brain and their density remains stable throughout the lifespan thanks to constant turnover. Microglia develop from yolk sac progenitors, later evolving through intermediate progenitors in a fine-tuned process in which intrinsic factors and external stimuli combine to progressively sculpt their cell type-specific transcriptional profiles. Recent evidence demonstrates that non-parenchymal macrophages are also generated during early embryonic development. In recent years, the development of powerful fate mapping approaches combined with novel genomic and transcriptomic methodologies have greatly expanded our understanding of how brain macrophages develop and acquire specialized functions, and how cell population dynamics are regulated. Here, we review the transcription factors, epigenetic remodeling, and signaling pathways orchestrating the embryonic development of microglia and non-parenchymal macrophages. Next, we describe the dynamics of the macrophage populations of the brain and discuss the role of progenitor cells, to gain a better understanding of their functions in the healthy and diseased brain. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 561-579, 2018. © 2017 The Authors Developmental Neurobiology Published by Wiley Periodicals, Inc.

Analyzing the dynamics of DNA replication in Mammalian cells using DNA combing.

PubMed

Bialic, Marta; Coulon, Vincent; Drac, Marjorie; Gostan, Thierry; Schwob, Etienne

2015-01-01

How cells duplicate their chromosomes is a key determinant of cell identity and genome stability. DNA replication can initiate from more than 100,000 sites distributed along mammalian chromosomes, yet a given cell uses only a subset of these origins due to inefficient origin activation and regulation by developmental or environmental cues. An impractical consequence of cell-to-cell variations in origin firing is that population-based techniques do not accurately describe how chromosomes are replicated in single cells. DNA combing is a biophysical DNA fiber stretching method which permits visualization of ongoing DNA synthesis along Mb-sized single-DNA molecules purified from cells that were previously pulse-labeled with thymidine analogues. This allows quantitative measurements of several salient features of chromosome replication dynamics, such as fork velocity, fork asymmetry, inter-origin distances, and global instant fork density. In this chapter we describe how to obtain this information from asynchronous cultures of mammalian cells.

Global asymptotic stability and hopf bifurcation for a blood cell production model.

PubMed

Crauste, Fabien

2006-04-01

We analyze the asymptotic stability of a nonlinear system of two differential equations with delay, describing the dynamics of blood cell produc- tion. This process takes place in the bone marrow, where stem cells differen- tiate throughout division in blood cells. Taking into account an explicit role of the total population of hematopoietic stem cells in the introduction of cells in cycle, we are led to study a characteristic equation with delay-dependent coefficients. We determine a necessary and sufficient condition for the global stability of the first steady state of our model, which describes the popula- tion's dying out, and we obtain the existence of a Hopf bifurcation for the only nontrivial positive steady state, leading to the existence of periodic solutions. These latter are related to dynamical diseases affecting blood cells known for their cyclic nature.

Neutral dynamics and cell renewal of colonic crypts in homeostatic regime

NASA Astrophysics Data System (ADS)

Fendrik, A. J.; Romanelli, L.; Rotondo, E.

2018-05-01

The self renewal process in colonic crypts is the object of several studies. We present here a new compartment model with the following characteristics: (a) we distinguish different classes of cells: stem cells, six generations of transit amplifying cells and the differentiated cells; (b) in order to take into account the monoclonal character of crypts in homeostatic regimes we include symmetric divisions of the stem cells. We first consider the dynamic differential equations that describe the evolution of the mean values of the populations, but the small observed value of the total number of cells involved plus the huge dispersion of experimental data found in the literature leads us to study the stochastic discrete process. This analysis allows us to study fluctuations, the neutral drift that leads to monoclonality, and the effects of the fixation of mutant clones.

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation.

PubMed

Chisholm, Rebecca H; Lorenzi, Tommaso; Clairambault, Jean

2016-11-01

Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level. We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies. Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies. Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016 Elsevier B.V. All rights reserved.

SYNTHETIC BIOLOGY. Emergent genetic oscillations in a synthetic microbial consortium.

PubMed

Chen, Ye; Kim, Jae Kyoung; Hirning, Andrew J; Josić, Krešimir; Bennett, Matthew R

2015-08-28

A challenge of synthetic biology is the creation of cooperative microbial systems that exhibit population-level behaviors. Such systems use cellular signaling mechanisms to regulate gene expression across multiple cell types. We describe the construction of a synthetic microbial consortium consisting of two distinct cell types—an "activator" strain and a "repressor" strain. These strains produced two orthogonal cell-signaling molecules that regulate gene expression within a synthetic circuit spanning both strains. The two strains generated emergent, population-level oscillations only when cultured together. Certain network topologies of the two-strain circuit were better at maintaining robust oscillations than others. The ability to program population-level dynamics through the genetic engineering of multiple cooperative strains points the way toward engineering complex synthetic tissues and organs with multiple cell types. Copyright © 2015, American Association for the Advancement of Science.

Decipher the dynamic coordination between enzymatic activity and structural modulation at focal adhesions in living cells

NASA Astrophysics Data System (ADS)

Lu, Shaoying; Seong, Jihye; Wang, Yi; Chang, Shiou-Chi; Eichorst, John Paul; Ouyang, Mingxing; Li, Julie Y.-S.; Chien, Shu; Wang, Yingxiao

2014-07-01

Focal adhesions (FAs) are dynamic subcellular structures crucial for cell adhesion, migration and differentiation. It remains an enigma how enzymatic activities in these local complexes regulate their structural remodeling in live cells. Utilizing biosensors based on fluorescence resonance energy transfer (FRET), we developed a correlative FRET imaging microscopy (CFIM) approach to quantitatively analyze the subcellular coordination between the enzymatic Src activation and the structural FA disassembly. CFIM reveals that the Src kinase activity only within the microdomain of lipid rafts at the plasma membrane is coupled with FA dynamics. FA disassembly at cell periphery was linearly dependent on this raft-localized Src activity, although cells displayed heterogeneous levels of response to stimulation. Within lipid rafts, the time delay between Src activation and FA disassembly was 1.2 min in cells seeded on low fibronectin concentration ([FN]) and 4.3 min in cells on high [FN]. CFIM further showed that the level of Src-FA coupling, as well as the time delay, was regulated by cell-matrix interactions, as a tight enzyme-structure coupling occurred in FA populations mediated by integrin αvβ3, but not in those by integrin α5β1. Therefore, different FA subpopulations have distinctive regulation mechanisms between their local kinase activity and structural FA dynamics.

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.

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

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.

Dynamic range adaptation in primary motor cortical populations

PubMed Central

Rasmussen, Robert G; Schwartz, Andrew; Chase, Steven M

2017-01-01

Neural populations from various sensory regions demonstrate dynamic range adaptation in response to changes in the statistical distribution of their input stimuli. These adaptations help optimize the transmission of information about sensory inputs. Here, we show a similar effect in the firing rates of primary motor cortical cells. We trained monkeys to operate a brain-computer interface in both two- and three-dimensional virtual environments. We found that neurons in primary motor cortex exhibited a change in the amplitude of their directional tuning curves between the two tasks. We then leveraged the simultaneous nature of the recordings to test several hypotheses about the population-based mechanisms driving these changes and found that the results are most consistent with dynamic range adaptation. Our results demonstrate that dynamic range adaptation is neither limited to sensory regions nor to rescaling of monotonic stimulus intensity tuning curves, but may rather represent a canonical feature of neural encoding. DOI: http://dx.doi.org/10.7554/eLife.21409.001 PMID:28417848

Notch1-Dll4 signaling and mechanical force regulate leader cell formation during collective cell migration

PubMed Central

Riahi, Reza; Sun, Jian; Wang, Shue; Long, Min; Zhang, Donna D.; Wong, Pak Kin

2015-01-01

At the onset of collective cell migration, a subset of cells within an initially homogenous population acquires a distinct “leader” phenotype with characteristic morphology and motility. However, the factors driving leader cell formation as well as the mechanisms regulating leader cell density during the migration process remain to be determined. Here, we use single cell gene expression analysis and computational modeling to show that leader cell identity is dynamically regulated by Dll4 signaling through both Notch1 and cellular stress in a migrating epithelium. Time-lapse microscopy reveals that Dll4 is induced in leader cells after the creation of the cell-free region and leader cells are regulated via Notch1-Dll4 lateral inhibition. Furthermore, mechanical stress inhibits Dll4 expression and leader cell formation in the monolayer. Collectively, our findings suggest that a reduction of mechanical force near the boundary promotes Notch1-Dll4 signaling to dynamically regulate the density of leader cells during collective cell migration. PMID:25766473

Bone Marrow Stem Cells in Clinical Application: Harnessing Paracrine Roles and Niche Mechanisms

NASA Astrophysics Data System (ADS)

Backly, Rania M. El; Cancedda, Ranieri

The being of any individual throughout life is a dynamic process relying on the capacity to retain processes of self-renewal and differentiation, both of which are hallmarks of stem cells. Although limited in the adult human organism, regeneration and repair do take place in virtue of the presence of adult stem cells. In the bone marrow, two major populations of stem cells govern the dynamic equilibrium of both hemopoiesis and skeletal homeostasis; the hematopoietic and the mesenchymal stem cells. Recent cell based clinical trials utilizing bone marrow-derived stem cells as therapeutic agents have revealed promising results, while others have failed to display as such. It is therefore imperative to strive to understand the mechanisms by which these cells function in vivo, how their properties can be maintained ex-vivo, and to explore further their recently highlighted immunomodulatory and trophic effects.

Seasonal Diversity Patterns of a Coastal Synechococcus Population

NASA Astrophysics Data System (ADS)

Hunter-Cevera, K. R.; Sosik, H. M.; Neubert, M.; Hammar, K.; Post, A.

2016-02-01

Understanding how environmental and ecological factors determine phytoplankton species abundances requires knowledge of the diversity present within a population. For the important primary producer Synechococcus, clades demonstrate differences in temperature tolerance, light acclimation, grazer palatability, and more. Marine Synechococcus populations are often composed of more than one clade, and overall population dynamics will be governed by the types of cells present and by their individual physiological capabilities. We investigate the diversity of the Synechococcus assemblage at the Martha's Vineyard Coastal Observatory with high-throughput sequencing of the V6 hypervariable region of the 16S rRNA gene. Small nucleotide differences within this region allow for resolution of distinct phylotypes that can have a direct correspondence to the well-defined Synechococcus clades. From a three-year time series, we find that the Synechococcus population is dominated by 5 distinct phylotypes, and that each type exhibits a repeatable, seasonal pattern in relative abundance. We use compositional data analysis techniques to investigate the relationships between these patterns and environmental factors. We further interpret these patterns in the context of Synechococcus population dynamics assessed by automated, submersible flow cytometry (FlowCytobot). Observed diel changes in cell size distributions, coupled with a validated matrix population model, provide estimates of in situ population division rates. We find strong evidence that the main seasonal diversity patterns are governed by temperature, but that biological loss agents likely shape the diversity structure for certain times of year. For some phylotypes, relative abundance patterns are also related to light and nutrients. The composition of Synechococcus over the annual cycle appears to directly affect seasonal features of cell abundance patterns, such as the spring bloom.

Dynamics of place, boundary and object encoding in rat anterior claustrum

PubMed Central

Jankowski, Maciej M.; O’Mara, Shane M.

2015-01-01

Discrete populations of brain cells signal differing types of spatial information. These “spatial cells” are largely confined to a closely-connected network of sites. We describe here, for the first time, cells in the anterior claustrum of the freely-moving rat encoding place, boundary and object information. This novel claustral spatial signal potentially directly modulates a wide variety of anterior cortical regions. We hypothesize that one of the functions of the claustrum is to provide information about body position, boundaries and landmark information, enabling dynamic control of behavior. PMID:26557060

Lymphocyte maintenance during healthy aging requires no substantial alterations in cellular turnover.

PubMed

Westera, Liset; van Hoeven, Vera; Drylewicz, Julia; Spierenburg, Gerrit; van Velzen, Jeroen F; de Boer, Rob J; Tesselaar, Kiki; Borghans, José A M

2015-04-01

In healthy humans, lymphocyte populations are maintained at a relatively constant size throughout life, reflecting a balance between lymphocyte production and loss. Given the profound immunological changes that occur during healthy aging, including a significant decline in T-cell production by the thymus, lymphocyte maintenance in the elderly is generally thought to require homeostatic alterations in lymphocyte dynamics. Surprisingly, using in vivo (2) H2 O labeling, we find similar dynamics of most lymphocyte subsets between young adult and elderly healthy individuals. As the contribution of thymic output to T-cell production is only minor from young adulthood onward, compensatory increases in peripheral T-cell division rates are not required to maintain the T-cell pool, despite a tenfold decline in thymic output. These fundamental insights will aid the interpretation of further research into aging and clinical conditions related to disturbed lymphocyte dynamics. © 2015 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Clustering in Cell Cycle Dynamics with General Response/Signaling Feedback

PubMed Central

Young, Todd R.; Fernandez, Bastien; Buckalew, Richard; Moses, Gregory; Boczko, Erik M.

2011-01-01

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call Responsive/Signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behaviour of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as “uniform” solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments. PMID:22001733

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.

Self-organization of bacterial communities against environmental pH variation: Controlled chemotactic motility arranges cell population structures in biofilms

PubMed Central

Nakayama, Madoka; Shoji, Wataru

2017-01-01

As with many living organisms, bacteria often live on the surface of solids, such as foods, organisms, buildings and soil. Compared with dispersive behavior in liquid, bacteria on surface environment exhibit significantly restricted mobility. They have access to only limited resources and cannot be liberated from the changing environment. Accordingly, appropriate collective strategies are necessarily required for long-term growth and survival. However, in spite of our deepening knowledge of the structure and characteristics of individual cells, strategic self-organizing dynamics of their community is poorly understood and therefore not yet predictable. Here, we report a morphological change in Bacillus subtilis biofilms due to environmental pH variations, and present a mathematical model for the macroscopic spatio-temporal dynamics. We show that an environmental pH shift transforms colony morphology on hard agar media from notched ‘volcano-like’ to round and front-elevated ‘crater-like’. We discover that a pH-dependent dose-response relationship between nutritional resource level and quantitative bacterial motility at the population level plays a central role in the mechanism of the spatio-temporal cell population structure design in biofilms. PMID:28253348

Self-organization of bacterial communities against environmental pH variation: Controlled chemotactic motility arranges cell population structures in biofilms.

PubMed

Tasaki, Sohei; Nakayama, Madoka; Shoji, Wataru

2017-01-01

As with many living organisms, bacteria often live on the surface of solids, such as foods, organisms, buildings and soil. Compared with dispersive behavior in liquid, bacteria on surface environment exhibit significantly restricted mobility. They have access to only limited resources and cannot be liberated from the changing environment. Accordingly, appropriate collective strategies are necessarily required for long-term growth and survival. However, in spite of our deepening knowledge of the structure and characteristics of individual cells, strategic self-organizing dynamics of their community is poorly understood and therefore not yet predictable. Here, we report a morphological change in Bacillus subtilis biofilms due to environmental pH variations, and present a mathematical model for the macroscopic spatio-temporal dynamics. We show that an environmental pH shift transforms colony morphology on hard agar media from notched 'volcano-like' to round and front-elevated 'crater-like'. We discover that a pH-dependent dose-response relationship between nutritional resource level and quantitative bacterial motility at the population level plays a central role in the mechanism of the spatio-temporal cell population structure design in biofilms.

Studying the Symbiotic Bacterium Xenorhabdus nematophila in Individual, Living Steinernema carpocapsae Nematodes Using Microfluidic Systems.

PubMed

Stilwell, Matthew D; Cao, Mengyi; Goodrich-Blair, Heidi; Weibel, Douglas B

2018-01-01

Animal-microbe symbioses are ubiquitous in nature and scientifically important in diverse areas, including ecology, medicine, and agriculture. Steinernema nematodes and Xenorhabdus bacteria compose an established, successful model system for investigating microbial pathogenesis and mutualism. The bacterium Xenorhabdus nematophila is a species-specific mutualist of insect-infecting Steinernema carpocapsae nematodes. The bacterium colonizes a specialized intestinal pocket within the infective stage of the nematode, which transports the bacteria between insects that are killed and consumed by the pair for reproduction. Current understanding of the interaction between the infective-stage nematode and its bacterial colonizers is based largely on population-level, snapshot time point studies on these organisms. This limitation arises because investigating temporal dynamics of the bacterium within the nematode is impeded by the difficulty of isolating and maintaining individual living nematodes and tracking colonizing bacterial cells over time. To overcome this challenge, we developed a microfluidic system that enables us to spatially isolate and microscopically observe individual, living Steinernema nematodes and monitor the growth and development of the associated X. nematophila bacterial communities-starting from a single cell or a few cells-over weeks. Our data demonstrate, to our knowledge, the first direct, temporal, in vivo visual analysis of a symbiosis system and the application of this system to reveal continuous dynamics of the symbiont population in the living host animal. IMPORTANCE This paper describes an experimental system for directly investigating population dynamics of a symbiotic bacterium, Xenorhabdus nematophila , in its host-the infective stage of the entomopathogenic nematode Steinernema carpocapsae . Tracking individual and groups of bacteria in individual host nematodes over days and weeks yielded insight into dynamic growth and topology changes of symbiotic bacterial populations within infective juvenile nematodes. Our approach for studying symbioses between bacteria and nematodes provides a system to investigate long-term host-microbe interactions in individual nematodes and extrapolate the lessons learned to other bacterium-animal interactions.

Single-cell analysis of population context advances RNAi screening at multiple levels

PubMed Central

Snijder, Berend; Sacher, Raphael; Rämö, Pauli; Liberali, Prisca; Mench, Karin; Wolfrum, Nina; Burleigh, Laura; Scott, Cameron C; Verheije, Monique H; Mercer, Jason; Moese, Stefan; Heger, Thomas; Theusner, Kristina; Jurgeit, Andreas; Lamparter, David; Balistreri, Giuseppe; Schelhaas, Mario; De Haan, Cornelis A M; Marjomäki, Varpu; Hyypiä, Timo; Rottier, Peter J M; Sodeik, Beate; Marsh, Mark; Gruenberg, Jean; Amara, Ali; Greber, Urs; Helenius, Ari; Pelkmans, Lucas

2012-01-01

Isogenic cells in culture show strong variability, which arises from dynamic adaptations to the microenvironment of individual cells. Here we study the influence of the cell population context, which determines a single cell's microenvironment, in image-based RNAi screens. We developed a comprehensive computational approach that employs Bayesian and multivariate methods at the single-cell level. We applied these methods to 45 RNA interference screens of various sizes, including 7 druggable genome and 2 genome-wide screens, analysing 17 different mammalian virus infections and four related cell physiological processes. Analysing cell-based screens at this depth reveals widespread RNAi-induced changes in the population context of individual cells leading to indirect RNAi effects, as well as perturbations of cell-to-cell variability regulators. We find that accounting for indirect effects improves the consistency between siRNAs targeted against the same gene, and between replicate RNAi screens performed in different cell lines, in different labs, and with different siRNA libraries. In an era where large-scale RNAi screens are increasingly performed to reach a systems-level understanding of cellular processes, we show that this is often improved by analyses that account for and incorporate the single-cell microenvironment. PMID:22531119

There are four dynamically and functionally distinct populations of E-cadherin in cell junctions

PubMed Central

Erami, Zahra; Timpson, Paul; Yao, Wu; Zaidel-Bar, Ronen; Anderson, Kurt I.

2015-01-01

ABSTRACT E-cadherin is a trans-membrane tumor suppressor responsible for epithelial cell adhesion. E-cadherin forms adhesive clusters through combined extra-cellular cis- and trans-interactions and intracellular interaction with the actin cytoskeleton. Here we identify four populations of E-cadherin within cell junctions based on the molecular interactions which determine their mobility and adhesive properties. Adhesive and non-adhesive populations of E-cadherin each consist of mobile and immobile fractions. Up to half of the E-cadherin immobilized in cell junctions is non-adhesive. Incorporation of E-cadherin into functional adhesions require all three adhesive interactions, with deletion of any one resulting in loss of effective cell-cell adhesion. Interestingly, the only interaction which could independently slow the diffusion of E-cadherin was the tail-mediated intra-cellular interaction. The adhesive and non-adhesive mobile fractions of E-cadherin can be distinguished by their sensitivity to chemical cross-linking with adhesive clusters. Our data define the size, mobility, and adhesive properties of four distinct populations of E-cadherin within cell junctions, and support association with the actin cytoskeleton as the first step in adhesion formation. PMID:26471767

Development of microbial genome-probing microarrays using digital multiple displacement amplification of uncultivated microbial single cells.

PubMed

Chang, Ho-Won; Sung, Youlboong; Kim, Kyoung-Ho; Nam, Young-Do; Roh, Seong Woon; Kim, Min-Soo; Jeon, Che Ok; Bae, Jin-Woo

2008-08-15

A crucial problem in the use of previously developed genome-probing microarrays (GPM) has been the inability to use uncultivated bacterial genomes to take advantage of the high sensitivity and specificity of GPM in microbial detection and monitoring. We show here a method, digital multiple displacement amplification (MDA), to amplify and analyze various genomes obtained from single uncultivated bacterial cells. We used 15 genomes from key microbes involved in dichloromethane (DCM)-dechlorinating enrichment as microarray probes to uncover the bacterial population dynamics of samples without PCR amplification. Genomic DNA amplified from single cells originating from uncultured bacteria with 80.3-99.4% similarity to 16S rRNA genes of cultivated bacteria. The digital MDA-GPM method successfully monitored the dynamics of DCM-dechlorinating communities from different phases of enrichment status. Without a priori knowledge of microbial diversity, the digital MDA-GPM method could be designed to monitor most microbial populations in a given environmental sample.

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.

Cooperation among cancer cells as public goods games on Voronoi networks.

PubMed

Archetti, Marco

2016-05-07

Cancer cells produce growth factors that diffuse and sustain tumour proliferation, a form of cooperation that can be studied using mathematical models of public goods in the framework of evolutionary game theory. Cell populations, however, form heterogeneous networks that cannot be described by regular lattices or scale-free networks, the types of graphs generally used in the study of cooperation. To describe the dynamics of growth factor production in populations of cancer cells, I study public goods games on Voronoi networks, using a range of non-linear benefits that account for the known properties of growth factors, and different types of diffusion gradients. The results are surprisingly similar to those obtained on regular graphs and different from results on scale-free networks, revealing that network heterogeneity per se does not promote cooperation when public goods diffuse beyond one-step neighbours. The exact shape of the diffusion gradient is not crucial, however, whereas the type of non-linear benefit is an essential determinant of the dynamics. Public goods games on Voronoi networks can shed light on intra-tumour heterogeneity, the evolution of resistance to therapies that target growth factors, and new types of cell therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

A kinetic theory for age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Chou, Tom; Greenman, Chris

Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but they are structurally unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Conversely, current theories that include size-dependent population dynamics (e.g., carrying capacity) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a BBGKY-like hierarchy. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution. NSF.

Mouse Hair Cycle Expression Dynamics Modeled as Coupled Mesenchymal and Epithelial Oscillators

PubMed Central

Tasseff, Ryan; Bheda-Malge, Anjali; DiColandrea, Teresa; Bascom, Charles C.; Isfort, Robert J.; Gelinas, Richard

2014-01-01

The hair cycle is a dynamic process where follicles repeatedly move through phases of growth, retraction, and relative quiescence. This process is an example of temporal and spatial biological complexity. Understanding of the hair cycle and its regulation would shed light on many other complex systems relevant to biological and medical research. Currently, a systematic characterization of gene expression and summarization within the context of a mathematical model is not yet available. Given the cyclic nature of the hair cycle, we felt it was important to consider a subset of genes with periodic expression. To this end, we combined several mathematical approaches with high-throughput, whole mouse skin, mRNA expression data to characterize aspects of the dynamics and the possible cell populations corresponding to potentially periodic patterns. In particular two gene clusters, demonstrating properties of out-of-phase synchronized expression, were identified. A mean field, phase coupled oscillator model was shown to quantitatively recapitulate the synchronization observed in the data. Furthermore, we found only one configuration of positive-negative coupling to be dynamically stable, which provided insight on general features of the regulation. Subsequent bifurcation analysis was able to identify and describe alternate states based on perturbation of system parameters. A 2-population mixture model and cell type enrichment was used to associate the two gene clusters to features of background mesenchymal populations and rapidly expanding follicular epithelial cells. Distinct timing and localization of expression was also shown by RNA and protein imaging for representative genes. Taken together, the evidence suggests that synchronization between expanding epithelial and background mesenchymal cells may be maintained, in part, by inhibitory regulation, and potential mediators of this regulation were identified. Furthermore, the model suggests that impairing this negative regulation will drive a bifurcation which may represent transition into a pathological state such as hair miniaturization. PMID:25375120

Internal Disequilibria and Phenotypic Diversification during Replication of Hepatitis C Virus in a Noncoevolving Cellular Environment.

PubMed

Moreno, Elena; Gallego, Isabel; Gregori, Josep; Lucía-Sanz, Adriana; Soria, María Eugenia; Castro, Victoria; Beach, Nathan M; Manrubia, Susanna; Quer, Josep; Esteban, Juan Ignacio; Rice, Charles M; Gómez, Jordi; Gastaminza, Pablo; Domingo, Esteban; Perales, Celia

2017-05-15

Viral quasispecies evolution upon long-term virus replication in a noncoevolving cellular environment raises relevant general issues, such as the attainment of population equilibrium, compliance with the molecular-clock hypothesis, or stability of the phenotypic profile. Here, we evaluate the adaptation, mutant spectrum dynamics, and phenotypic diversification of hepatitis C virus (HCV) in the course of 200 passages in human hepatoma cells in an experimental design that precluded coevolution of the cells with the virus. Adaptation to the cells was evidenced by increase in progeny production. The rate of accumulation of mutations in the genomic consensus sequence deviated slightly from linearity, and mutant spectrum analyses revealed a complex dynamic of mutational waves, which was sustained beyond passage 100. The virus underwent several phenotypic changes, some of which impacted the virus-host relationship, such as enhanced cell killing, a shift toward higher virion density, and increased shutoff of host cell protein synthesis. Fluctuations in progeny production and failure to reach population equilibrium at the genomic level suggest internal instabilities that anticipate an unpredictable HCV evolution in the complex liver environment. IMPORTANCE Long-term virus evolution in an unperturbed cellular environment can reveal features of virus evolution that cannot be explained by comparing natural viral isolates. In the present study, we investigate genetic and phenotypic changes that occur upon prolonged passage of hepatitis C virus (HCV) in human hepatoma cells in an experimental design in which host cell evolutionary change is prevented. Despite replication in a noncoevolving cellular environment, the virus exhibited internal population disequilibria that did not decline with increased adaptation to the host cells. The diversification of phenotypic traits suggests that disequilibria inherent to viral populations may provide a selective advantage to viruses that can be fully exploited in changing environments. Copyright © 2017 American Society for Microbiology.

Correlative Light-Electron Microscopy Shows RGD-Targeted ZnO Nanoparticles Dissolve in the Intracellular Environment of Triple Negative Breast Cancer Cells and Cause Apoptosis with Intratumor Heterogeneity.

PubMed

Othman, Basmah A; Greenwood, Christina; Abuelela, Ayman F; Bharath, Anil A; Chen, Shu; Theodorou, Ioannis; Douglas, Trevor; Uchida, Maskai; Ryan, Mary; Merzaban, Jasmeen S; Porter, Alexandra E

2016-06-01

ZnO nanoparticles (NPs) are reported to show a high degree of cancer cell selectivity with potential use in cancer imaging and therapy. Questions remain about the mode by which the ZnO NPs cause cell death, whether they exert an intra- or extracellular effect, and the resistance among different cancer cell types to ZnO NP exposure. The present study quantifies the variability between the cellular toxicity, dynamics of cellular uptake, and dissolution of bare and RGD (Arg-Gly-Asp)-targeted ZnO NPs by MDA-MB-231 cells. Compared to bare ZnO NPs, RGD-targeting of the ZnO NPs to integrin αvβ3 receptors expressed on MDA-MB-231 cells appears to increase the toxicity of the ZnO NPs to breast cancer cells at lower doses. Confocal microscopy of live MDA-MB-231 cells confirms uptake of both classes of ZnO NPs with a commensurate rise in intracellular Zn(2+) concentration prior to cell death. The response of the cells within the population to intracellular Zn(2+) is highly heterogeneous. In addition, the results emphasize the utility of dynamic and quantitative imaging in understanding cell uptake and processing of targeted therapeutic ZnO NPs at the cellular level by heterogeneous cancer cell populations, which can be crucial for the development of optimized treatment strategies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

HIV-1 dynamics revisited: biphasic decay by cytotoxic T lymphocyte killing?

PubMed Central

Arnaout, R A; Nowak, M A; Wodarz, D

2000-01-01

The biphasic decay of blood viraemia in patients being treated for human immunodeficiency virus type 1 (HIV-1) infection has been explained as the decay of two distinct populations of cells: the rapid death of productively infected cells followed by the much slower elimination of a second population the identity of which remains unknown. Here we advance an alternative explanation based on the immune response against a single population of infected cells. We show that the biphasic decay can be explained simply, without invoking multiple compartments: viral load falls quickly while cytotoxic T lymphocytes (CTL) are still abundant, and more slowly as CTL disappear. We propose a method to test this idea, and develop a framework that is readily applicable to treatment of other infections. PMID:10972131

Metabolic heterogeneity in clonal microbial populations.

PubMed

Takhaveev, Vakil; Heinemann, Matthias

2018-02-21

In the past decades, numerous instances of phenotypic diversity were observed in clonal microbial populations, particularly, on the gene expression level. Much less is, however, known about phenotypic differences that occur on the level of metabolism. This is likely explained by the fact that experimental tools probing metabolism of single cells are still at an early stage of development. Here, we review recent exciting discoveries that point out different causes for metabolic heterogeneity within clonal microbial populations. These causes range from ecological factors and cell-inherent dynamics in constant environments to molecular noise in gene expression that propagates into metabolism. Furthermore, we provide an overview of current methods to quantify the levels of metabolites and biomass components in single cells. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

Dynamic Fungal Cell Wall Architecture in Stress Adaptation and Immune Evasion.

PubMed

Hopke, Alex; Brown, Alistair J P; Hall, Rebecca A; Wheeler, Robert T

2018-04-01

Deadly infections from opportunistic fungi have risen in frequency, largely because of the at-risk immunocompromised population created by advances in modern medicine and the HIV/AIDS pandemic. This review focuses on dynamics of the fungal polysaccharide cell wall, which plays an outsized role in fungal pathogenesis and therapy because it acts as both an environmental barrier and as the major interface with the host immune system. Human fungal pathogens use architectural strategies to mask epitopes from the host and prevent immune surveillance, and recent work elucidates how biotic and abiotic stresses present during infection can either block or enhance masking. The signaling components implicated in regulating fungal immune recognition can teach us how cell wall dynamics are controlled, and represent potential targets for interventions designed to boost or dampen immunity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Charge Generation Dynamics in Efficient All-Polymer Solar Cells: Influence of Polymer Packing and Morphology.

PubMed

Gautam, Bhoj R; Lee, Changyeon; Younts, Robert; Lee, Wonho; Danilov, Evgeny; Kim, Bumjoon J; Gundogdu, Kenan

2015-12-23

All-polymer solar cells exhibit rapid progress in power conversion efficiency (PCE) from 2 to 7.7% over the past few years. While this improvement is primarily attributed to efficient charge transport and balanced mobility between the carriers, not much is known about the charge generation dynamics in these systems. Here we measured exciton relaxation and charge separation dynamics using ultrafast spectroscopy in polymer/polymer blends with different molecular packing and morphology. These measurements indicate that preferential face-on configuration with intermixed nanomorphology increases the charge generation efficiency. In fact, there is a direct quantitative correlation between the free charge population in the ultrafast time scales and the external quantum efficiency, suggesting not only the transport but also charge generation is key for the design of high performance all polymer solar cells.

Single-cell gene expression analysis reveals diversity among human spermatogonia.

PubMed

Neuhaus, N; Yoon, J; Terwort, N; Kliesch, S; Seggewiss, J; Huge, A; Voss, R; Schlatt, S; Grindberg, R V; Schöler, H R

2017-02-10

Is the molecular profile of human spermatogonia homogeneous or heterogeneous when analysed at the single-cell level? Heterogeneous expression profiles may be a key characteristic of human spermatogonia, supporting the existence of a heterogeneous stem cell population. Despite the fact that many studies have sought to identify specific markers for human spermatogonia, the molecular fingerprint of these cells remains hitherto unknown. Testicular tissues from patients with spermatogonial arrest (arrest, n = 1) and with qualitatively normal spermatogenesis (normal, n = 7) were selected from a pool of 179 consecutively obtained biopsies. Gene expression analyses of cell populations and single-cells (n = 105) were performed. Two OCT4-positive individual cells were selected for global transcriptional capture using shallow RNA-seq. Finally, expression of four candidate markers was assessed by immunohistochemistry. Histological analysis and blood hormone measurements for LH, FSH and testosterone were performed prior to testicular sample selection. Following enzymatic digestion of testicular tissues, differential plating and subsequent micromanipulation of individual cells was employed to enrich and isolate human spermatogonia, respectively. Endpoint analyses were qPCR analysis of cell populations and individual cells, shallow RNA-seq and immunohistochemical analyses. Unexpectedly, single-cell expression data from the arrest patient (20 cells) showed heterogeneous expression profiles. Also, from patients with normal spermatogenesis, heterogeneous expression patterns of undifferentiated (OCT4, UTF1 and MAGE A4) and differentiated marker genes (BOLL and PRM2) were obtained within each spermatogonia cluster (13 clusters with 85 cells). Shallow RNA-seq analysis of individual human spermatogonia was validated, and a spermatogonia-specific heterogeneous protein expression of selected candidate markers (DDX5, TSPY1, EEF1A1 and NGN3) was demonstrated. The heterogeneity of human spermatogonia at the RNA and protein levels is a snapshot. To further assess the functional meaning of this heterogeneity and the dynamics of stem cell populations, approaches need to be developed to facilitate the repeated analysis of individual cells. Our data suggest that heterogeneous expression profiles may be a key characteristic of human spermatogonia, supporting the model of a heterogeneous stem cell population. Future studies will assess the dynamics of spermatogonial populations in fertile and infertile patients. RNA-seq data is published in the GEO database: GSE91063. This work was supported by the Max Planck Society and the Deutsche Forschungsgemeinschaft DFG-Research Unit FOR 1041 Germ Cell Potential (grant numbers SCHO 340/7-1, SCHL394/11-2). The authors declare that there is no conflict of interest. © The Author 2017. 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

Three-dimensional confocal morphometry – a new approach for studying dynamic changes in cell morphology in brain slices

PubMed Central

Chvátal, Alexandr; Anděrová, Miroslava; Kirchhoff, Frank

2007-01-01

Pathological states in the central nervous system lead to dramatic changes in the activity of neuroactive substances in the extracellular space, to changes in ionic homeostasis and often to cell swelling. To quantify changes in cell morphology over a certain period of time, we employed a new technique, three-dimensional confocal morphometry. In our experiments, performed on enhanced green fluorescent protein/glial fibrillary acidic protein astrocytes in brain slices in situ and thus preserving the extracellular microenvironment, confocal morphometry revealed that the application of hypotonic solution evoked two types of volume change. In one population of astrocytes, hypotonic stress evoked small cell volume changes followed by a regulatory volume decrease, while in the second population volume changes were significantly larger without subsequent volume regulation. Three-dimensional cell reconstruction revealed that even though the total astrocyte volume increased during hypotonic stress, the morphological changes in various cell compartments and processes were more complex than have been previously shown, including swelling, shrinking and structural rearrangement. Our data show that astrocytes in brain slices in situ during hypotonic stress display complex behaviour. One population of astrocytes is highly capable of cell volume regulation, while the second population is characterized by prominent cell swelling, accompanied by plastic changes in morphology. It is possible to speculate that these two astrocyte populations play different roles during physiological and pathological states. PMID:17488344

New insights into mechanisms of stem cell daughter fate determination in regenerative tissues.

PubMed

Sada, Aiko; Tumbar, Tudorita

2013-01-01

Stem cells can self-renew and differentiate over extended periods of time. Understanding how stem cells acquire their fates is a central question in stem cell biology. Early work in Drosophila germ line and neuroblast showed that fate choice is achieved by strict asymmetric divisions that can generate each time one stem and one differentiated cell. More recent work suggests that during homeostasis, some stem cells can divide symmetrically to generate two differentiated cells or two identical stem cells to compensate for stem cell loss that occurred by direct differentiation or apoptosis. The interplay of all these factors ensures constant tissue regeneration and the maintenance of stem cell pool size. This interplay can be modeled as a population-deterministic dynamics that, at least in some systems, may be described as stochastic behavior. Here, we overview recent progress made on the characterization of stem cell dynamics in regenerative tissues. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Autofluorescence imaging captures heterogeneous drug response differences between 2D and 3D breast cancer cultures

PubMed Central

Cannon, T. M.; Shah, A. T.; Skala, M. C.

2017-01-01

Two-photon microscopy of cellular autofluorescence intensity and lifetime (optical metabolic imaging, or OMI) is a promising tool for preclinical drug development. OMI, which exploits the endogenous fluorescence from the metabolic coenzymes NAD(P)H and FAD, is sensitive to changes in cell metabolism produced by drug treatment. Previous studies have shown that drug response, genetic expression, cell-cell communication, and cell signaling in 3D culture match those of the original in vivo tumor, but not those of 2D culture. The goal of this study is to use OMI to quantify dynamic cell-level metabolic differences in drug response in 2D cell lines vs. 3D organoids generated from xenograft tumors of the same cell origin. BT474 cells and Herceptin-resistant BT474 (HR6) cells were tested. Cells were treated with vehicle control, Herceptin, XL147 (PI3K inhibitor), and the combination. The OMI index was used to quantify response, and is a linear combination of the redox ratio (intensity of NAD(P)H divided by FAD), mean NADH lifetime, and mean FAD lifetime. The results confirm that the OMI index resolves significant differences (p<0.05) in drug response for 2D vs. 3D cultures, specifically for BT474 cells 24 hours after Herceptin treatment, for HR6 cells 24 and 72 hours after combination treatment, and for HR6 cells 72 hours after XL147 treatment. Cell-level analysis of the OMI index also reveals differences in the number of cell sub-populations in 2D vs. 3D culture at 24, 48, and 72 hours post-treatment in control and treated groups. Finally, significant increases (p<0.05) in the mean lifetime of NADH and FAD were measured in 2D vs. 3D for both cell lines at 72 hours post-treatment in control and all treatment groups. These whole-population differences in the mean NADH and FAD lifetimes are supported by differences in the number of cell sub-populations in 2D vs. 3D. Overall, these studies confirm that OMI is sensitive to differences in drug response in 2D vs. 3D, and provides further information on dynamic changes in the relative abundance of metabolic cell sub-populations that contribute to this difference. PMID:28663873

About the discrete-continuous nature of a hematopoiesis model for Chronic Myeloid Leukemia.

PubMed

Gaudiano, Marcos E; Lenaerts, Tom; Pacheco, Jorge M

2016-12-01

Blood of mammals is composed of a variety of cells suspended in a fluid medium known as plasma. Hematopoiesis is the biological process of birth, replication and differentiation of blood cells. Despite of being essentially a stochastic phenomenon followed by a huge number of discrete entities, blood formation has naturally an associated continuous dynamics, because the cellular populations can - on average - easily be described by (e.g.) differential equations. This deterministic dynamics by no means contemplates some important stochastic aspects related to abnormal hematopoiesis, that are especially significant for studying certain blood cancer deceases. For instance, by mere stochastic competition against the normal cells, leukemic cells sometimes do not reach the population thereshold needed to kill the organism. Of course, a pure discrete model able to follow the stochastic paths of billons of cells is computationally impossible. In order to avoid this difficulty, we seek a trade-off between the computationally feasible and the biologically realistic, deriving an equation able to size conveniently both the discrete and continuous parts of a model for hematopoiesis in terrestrial mammals, in the context of Chronic Myeloid Leukemia. Assuming the cancer is originated from a single stem cell inside of the bone marrow, we also deduce a theoretical formula for the probability of non-diagnosis as a function of the mammal average adult mass. In addition, this work cellular dynamics analysis may shed light on understanding Peto's paradox, which is shown here as an emergent property of the discrete-continuous nature of the system. Copyright © 2016 Elsevier Inc. All rights reserved.

Heterogeneity for IGF-II production maintained by public goods dynamics in neuroendocrine pancreatic cancer.

PubMed

Archetti, Marco; Ferraro, Daniela A; Christofori, Gerhard

2015-02-10

The extensive intratumor heterogeneity revealed by sequencing cancer genomes is an essential determinant of tumor progression, diagnosis, and treatment. What maintains heterogeneity remains an open question because competition within a tumor leads to a strong selection for the fittest subclone. Cancer cells also cooperate by sharing molecules with paracrine effects, such as growth factors, and heterogeneity can be maintained if subclones depend on each other for survival. Without strict interdependence between subclones, however, nonproducer cells can free-ride on the growth factors produced by neighboring producer cells, a collective action problem known in game theory as the "tragedy of the commons," which has been observed in microbial cell populations. Here, we report that similar dynamics occur in cancer cell populations. Neuroendocrine pancreatic cancer (insulinoma) cells that do not produce insulin-like growth factor II (IGF-II) grow slowly in pure cultures but have a proliferation advantage in mixed cultures, where they can use the IGF-II provided by producer cells. We show that, as predicted by evolutionary game theory, producer cells do not go extinct because IGF-II acts as a nonlinear public good, creating negative frequency-dependent selection that leads to a stable coexistence of the two cell types. Intratumor cell heterogeneity can therefore be maintained even without strict interdependence between cell subclones. Reducing the amount of growth factors available within a tumor may lead to a reduction in growth followed by a new equilibrium, which may explain relapse in therapies that target growth factors.

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.

Optical control demonstrates switch-like PIP3 dynamics underlying the initiation of immune cell migration

PubMed Central

Karunarathne, W. K. Ajith; Giri, Lopamudra; Patel, Anilkumar K.; Venkatesh, Kareenhalli V.; Gautam, N.

2013-01-01

There is a dearth of approaches to experimentally direct cell migration by continuously varying signal input to a single cell, evoking all possible migratory responses and quantitatively monitoring the cellular and molecular response dynamics. Here we used a visual blue opsin to recruit the endogenous G-protein network that mediates immune cell migration. Specific optical inputs to this optical trigger of signaling helped steer migration in all possible directions with precision. Spectrally selective imaging was used to monitor cell-wide phosphatidylinositol (3,4,5)-triphosphate (PIP3), cytoskeletal, and cellular dynamics. A switch-like PIP3 increase at the cell front and a decrease at the back were identified, underlying the decisive migratory response. Migration was initiated at the rapidly increasing switch stage of PIP3 dynamics. This result explains how a migratory cell filters background fluctuations in the intensity of an extracellular signal but responds by initiating directionally sensitive migration to a persistent signal gradient across the cell. A two-compartment computational model incorporating a localized activator that is antagonistic to a diffusible inhibitor was able to simulate the switch-like PIP3 response. It was also able simulate the slow dissipation of PIP3 on signal termination. The ability to independently apply similar signaling inputs to single cells detected two cell populations with distinct thresholds for migration initiation. Overall the optical approach here can be applied to understand G-protein–coupled receptor network control of other cell behaviors. PMID:23569254

Optical control demonstrates switch-like PIP3 dynamics underlying the initiation of immune cell migration.

PubMed

Karunarathne, W K Ajith; Giri, Lopamudra; Patel, Anilkumar K; Venkatesh, Kareenhalli V; Gautam, N

2013-04-23

There is a dearth of approaches to experimentally direct cell migration by continuously varying signal input to a single cell, evoking all possible migratory responses and quantitatively monitoring the cellular and molecular response dynamics. Here we used a visual blue opsin to recruit the endogenous G-protein network that mediates immune cell migration. Specific optical inputs to this optical trigger of signaling helped steer migration in all possible directions with precision. Spectrally selective imaging was used to monitor cell-wide phosphatidylinositol (3,4,5)-triphosphate (PIP3), cytoskeletal, and cellular dynamics. A switch-like PIP3 increase at the cell front and a decrease at the back were identified, underlying the decisive migratory response. Migration was initiated at the rapidly increasing switch stage of PIP3 dynamics. This result explains how a migratory cell filters background fluctuations in the intensity of an extracellular signal but responds by initiating directionally sensitive migration to a persistent signal gradient across the cell. A two-compartment computational model incorporating a localized activator that is antagonistic to a diffusible inhibitor was able to simulate the switch-like PIP3 response. It was also able simulate the slow dissipation of PIP3 on signal termination. The ability to independently apply similar signaling inputs to single cells detected two cell populations with distinct thresholds for migration initiation. Overall the optical approach here can be applied to understand G-protein-coupled receptor network control of other cell behaviors.

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.

Mechanisms for the epigenetic inheritance of stress response in single cells.

PubMed

Xue, Yuan; Acar, Murat

2018-05-30

Cells have evolved to dynamically respond to different types of environmental and physiological stress conditions. The information about a previous stress stimulus experience by a mother cell can be passed to its descendants, allowing them to better adapt to and survive in new environments. In recent years, live-cell imaging combined with cell-lineage tracking approaches has elucidated many important principles that guide stress inheritance at the single-cell and population level. In this review, we summarize different strategies that cells can employ to pass the 'memory' of previous stress responses to their descendants. Among these strategies, we focus on a recent discovery of how specific features of Msn2 nucleo-cytoplasmic shuttling dynamics could be inherited across cell lineages. We also discuss how stress response can be transmitted to progenies through changes in chromatin and through partitioning of anti-stress factors and/or damaged macromolecules between mother and daughter cells during cell division. Finally, we highlight how emergent technologies will help address open questions in the field.

Estimating Cyanobacteria Community Dynamics and its Relationship with Environmental Factors

PubMed Central

Luo, Wenhuai; Chen, Huirong; Lei, Anping; Lu, Jun; Hu, Zhangli

2014-01-01

The cyanobacteria community dynamics in two eutrophic freshwater bodies (Tiegang Reservoir and Shiyan Reservoir) was studied with both a traditional microscopic counting method and a PCR-DGGE genotyping method. Results showed that cyanobacterium Phormidium tenue was the predominant species; twenty-six cyanobacteria species were identified in water samples collected from the two reservoirs, among which fourteen were identified with the morphological method and sixteen with the PCR-DGGE method. The cyanobacteria community composition analysis showed a seasonal fluctuation from July to December. The cyanobacteria population peaked in August in both reservoirs, with cell abundances of 3.78 × 108 cells L-1 and 1.92 × 108 cells L-1 in the Tiegang and Shiyan reservoirs, respectively. Canonical Correspondence Analysis (CCA) was applied to further investigate the correlation between cyanobacteria community dynamics and environmental factors. The result indicated that the cyanobacteria community dynamics was mostly correlated with pH, temperature and total nitrogen. This study demonstrated that data obtained from PCR-DGGE combined with a traditional morphological method could reflect cyanobacteria community dynamics and its correlation with environmental factors in eutrophic freshwater bodies. PMID:24448632

Single-cell resolution of intracellular T cell Ca2+ dynamics in response to frequency-based H2O2 stimulation.

PubMed

Kniss-James, Ariel S; Rivet, Catherine A; Chingozha, Loice; Lu, Hang; Kemp, Melissa L

2017-03-01

Adaptive immune cells, such as T cells, integrate information from their extracellular environment through complex signaling networks with exquisite sensitivity in order to direct decisions on proliferation, apoptosis, and cytokine production. These signaling networks are reliant on the interplay between finely tuned secondary messengers, such as Ca 2+ and H 2 O 2 . Frequency response analysis, originally developed in control engineering, is a tool used for discerning complex networks. This analytical technique has been shown to be useful for understanding biological systems and facilitates identification of the dominant behaviour of the system. We probed intracellular Ca 2+ dynamics in the frequency domain to investigate the complex relationship between two second messenger signaling molecules, H 2 O 2 and Ca 2+ , during T cell activation with single cell resolution. Single-cell analysis provides a unique platform for interrogating and monitoring cellular processes of interest. We utilized a previously developed microfluidic device to monitor individual T cells through time while applying a dynamic input to reveal a natural frequency of the system at approximately 2.78 mHz stimulation. Although our network was much larger with more unknown connections than previous applications, we are able to derive features from our data, observe forced oscillations associated with specific amplitudes and frequencies of stimuli, and arrive at conclusions about potential transfer function fits as well as the underlying population dynamics.

Variation is function: Are single cell differences functionally important?: Testing the hypothesis that single cell variation is required for aggregate function.

PubMed

Dueck, Hannah; Eberwine, James; Kim, Junhyong

2016-02-01

There is a growing appreciation of the extent of transcriptome variation across individual cells of the same cell type. While expression variation may be a byproduct of, for example, dynamic or homeostatic processes, here we consider whether single-cell molecular variation per se might be crucial for population-level function. Under this hypothesis, molecular variation indicates a diversity of hidden functional capacities within an ensemble of identical cells, and this functional diversity facilitates collective behavior that would be inaccessible to a homogenous population. In reviewing this topic, we explore possible functions that might be carried by a heterogeneous ensemble of cells; however, this question has proven difficult to test, both because methods to manipulate molecular variation are limited and because it is complicated to define, and measure, population-level function. We consider several possible methods to further pursue the hypothesis that variation is function through the use of comparative analysis and novel experimental techniques. © 2015 The Authors. BioEssays published by WILEY Periodicals, Inc.

Cell Population Kinetics of Collagen Scaffolds in Ex Vivo Oral Wound Repair

PubMed Central

Agis, Hermann; Collins, Amy; Taut, Andrei D.; Jin, Qiming; Kruger, Laura; Görlach, Christoph; Giannobile, William V.

2014-01-01

Biodegradable collagen scaffolds are used clinically for oral soft tissue augmentation to support wound healing. This study sought to provide a novel ex vivo model for analyzing healing kinetics and gene expression of primary human gingival fibroblasts (hGF) within collagen scaffolds. Sponge type and gel type scaffolds with and without platelet-derived growth factor-BB (PDGF) were assessed in an hGF containing matrix. Morphology was evaluated with scanning electron microscopy, and hGF metabolic activity using MTT. We quantitated the population kinetics within the scaffolds based on cell density and distance from the scaffold border of DiI-labled hGFs over a two-week observation period. Gene expression was evaluated with gene array and qPCR. The sponge type scaffolds showed a porous morphology. Absolute cell number and distance was higher in sponge type scaffolds when compared to gel type scaffolds, in particular during the first week of observation. PDGF incorporated scaffolds increased cell numbers, distance, and formazan formation in the MTT assay. Gene expression dynamics revealed the induction of key genes associated with the generation of oral tissue. DKK1, CYR61, CTGF, TGFBR1 levels were increased and integrin ITGA2 levels were decreased in the sponge type scaffolds compared to the gel type scaffold. The results suggest that this novel model of oral wound healing provides insights into population kinetics and gene expression dynamics of biodegradable scaffolds. PMID:25397671

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.

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

Optimal growth entails risky localization in population dynamics

NASA Astrophysics Data System (ADS)

Gueudré, Thomas; Martin, David G.

2018-03-01

Essential to each other, growth and exploration are jointly observed in alive and inanimate entities, such as animals, cells or goods. But how the environment's structural and temporal properties weights in this balance remains elusive. We analyze a model of stochastic growth with time correlations and diffusive dynamics that sheds light on the way populations grow and spread over general networks. This model suggests natural explanations of empirical facts in econo-physics or ecology, such as the risk-return trade-off and the Zipf law. We conclude that optimal growth leads to a localized population distribution, but such risky position can be mitigated through the space geometry. These results have broad applicability and are subsequently illustrated over an empirical study of financial data.

Lineage tracing reveals multipotent stem cells maintain human adenomas and the pattern of clonal expansion in tumor evolution

PubMed Central

Humphries, Adam; Cereser, Biancastella; Gay, Laura J.; Miller, Daniel S. J.; Das, Bibek; Gutteridge, Alice; Elia, George; Nye, Emma; Jeffery, Rosemary; Poulsom, Richard; Novelli, Marco R.; Rodriguez-Justo, Manuel; McDonald, Stuart A. C.; Wright, Nicholas A.; Graham, Trevor A.

2013-01-01

The genetic and morphological development of colorectal cancer is a paradigm for tumorigenesis. However, the dynamics of clonal evolution underpinning carcinogenesis remain poorly understood. Here we identify multipotential stem cells within human colorectal adenomas and use methylation patterns of nonexpressed genes to characterize clonal evolution. Numerous individual crypts from six colonic adenomas and a hyperplastic polyp were microdissected and characterized for genetic lesions. Clones deficient in cytochrome c oxidase (CCO−) were identified by histochemical staining followed by mtDNA sequencing. Topographical maps of clone locations were constructed using a combination of these data. Multilineage differentiation within clones was demonstrated by immunofluorescence. Methylation patterns of adenomatous crypts were determined by clonal bisulphite sequencing; methylation pattern diversity was compared with a mathematical model to infer to clonal dynamics. Individual adenomatous crypts were clonal for mtDNA mutations and contained both mucin-secreting and neuroendocrine cells, demonstrating that the crypt contained a multipotent stem cell. The intracrypt methylation pattern was consistent with the crypts containing multiple competing stem cells. Adenomas were epigenetically diverse populations, suggesting that they were relatively mitotically old populations. Intratumor clones typically showed less diversity in methylation pattern than the tumor as a whole. Mathematical modeling suggested that recent clonal sweeps encompassing the whole adenoma had not occurred. Adenomatous crypts within human tumors contain actively dividing stem cells. Adenomas appeared to be relatively mitotically old populations, pocketed with occasional newly generated subclones that were the result of recent rapid clonal expansion. Relative stasis and occasional rapid subclone growth may characterize colorectal tumorigenesis. PMID:23766371

Lineage tracing reveals multipotent stem cells maintain human adenomas and the pattern of clonal expansion in tumor evolution.

PubMed

Humphries, Adam; Cereser, Biancastella; Gay, Laura J; Miller, Daniel S J; Das, Bibek; Gutteridge, Alice; Elia, George; Nye, Emma; Jeffery, Rosemary; Poulsom, Richard; Novelli, Marco R; Rodriguez-Justo, Manuel; McDonald, Stuart A C; Wright, Nicholas A; Graham, Trevor A

2013-07-02

The genetic and morphological development of colorectal cancer is a paradigm for tumorigenesis. However, the dynamics of clonal evolution underpinning carcinogenesis remain poorly understood. Here we identify multipotential stem cells within human colorectal adenomas and use methylation patterns of nonexpressed genes to characterize clonal evolution. Numerous individual crypts from six colonic adenomas and a hyperplastic polyp were microdissected and characterized for genetic lesions. Clones deficient in cytochrome c oxidase (CCO(-)) were identified by histochemical staining followed by mtDNA sequencing. Topographical maps of clone locations were constructed using a combination of these data. Multilineage differentiation within clones was demonstrated by immunofluorescence. Methylation patterns of adenomatous crypts were determined by clonal bisulphite sequencing; methylation pattern diversity was compared with a mathematical model to infer to clonal dynamics. Individual adenomatous crypts were clonal for mtDNA mutations and contained both mucin-secreting and neuroendocrine cells, demonstrating that the crypt contained a multipotent stem cell. The intracrypt methylation pattern was consistent with the crypts containing multiple competing stem cells. Adenomas were epigenetically diverse populations, suggesting that they were relatively mitotically old populations. Intratumor clones typically showed less diversity in methylation pattern than the tumor as a whole. Mathematical modeling suggested that recent clonal sweeps encompassing the whole adenoma had not occurred. Adenomatous crypts within human tumors contain actively dividing stem cells. Adenomas appeared to be relatively mitotically old populations, pocketed with occasional newly generated subclones that were the result of recent rapid clonal expansion. Relative stasis and occasional rapid subclone growth may characterize colorectal tumorigenesis.

Spatial structure and nutrients promote invasion of IncP-1 plasmids in bacterial populations

PubMed Central

Fox, Randal E; Zhong, Xue; Krone, Stephen M; Top, Eva M

2008-01-01

In spite of the importance of plasmids in bacterial adaptation, we have a poor understanding of their dynamics. It is not known if or how plasmids persist in and spread through (invade) a bacterial population when there is no selection for plasmid-encoded traits. Moreover, the differences in dynamics between spatially structured and mixed populations are poorly understood. Through a joint experimental/theoretical approach, we tested the hypothesis that self-transmissible IncP-1 plasmids can invade a bacterial population in the absence of selection when initially very rare, but only in spatially structured habitats and when nutrients are regularly replenished. Using protocols that differed in the degree of spatial structure and nutrient levels, the invasiveness of plasmid pB10 in Escherichia coli was monitored during at least 15 days, with an initial fraction of plasmid-bearing (p+) cells as low as 10−7. To further explore the mechanisms underlying plasmid dynamics, we developed a spatially explicit mathematical model. When cells were grown on filters and transferred to fresh medium daily, the p+ fraction increased to 13%, whereas almost complete invasion occurred when the population structure was disturbed daily. The plasmid was unable to invade in liquid. When carbon source levels were lower or not replenished, plasmid invasion was hampered. Simulations of the mathematical model closely matched the experimental results and produced estimates of the effects of alternative experimental parameters. This allowed us to isolate the likely mechanisms most responsible for the observations. In conclusion, spatial structure and nutrient availability can be key determinants in the invasiveness of plasmids. PMID:18528415

Analyzing the dynamics of cell cycle processes from fixed samples through ergodic principles.

PubMed

Wheeler, Richard John

2015-11-05

Tools to analyze cyclical cellular processes, particularly the cell cycle, are of broad value for cell biology. Cell cycle synchronization and live-cell time-lapse observation are widely used to analyze these processes but are not available for many systems. Simple mathematical methods built on the ergodic principle are a well-established, widely applicable, and powerful alternative analysis approach, although they are less widely used. These methods extract data about the dynamics of a cyclical process from a single time-point "snapshot" of a population of cells progressing through the cycle asynchronously. Here, I demonstrate application of these simple mathematical methods to analysis of basic cyclical processes--cycles including a division event, cell populations undergoing unicellular aging, and cell cycles with multiple fission (schizogony)--as well as recent advances that allow detailed mapping of the cell cycle from continuously changing properties of the cell such as size and DNA content. This includes examples using existing data from mammalian, yeast, and unicellular eukaryotic parasite cell biology. Through the ongoing advances in high-throughput cell analysis by light microscopy, electron microscopy, and flow cytometry, these mathematical methods are becoming ever more important and are a powerful complementary method to traditional synchronization and time-lapse cell cycle analysis methods. © 2015 Wheeler. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Chemotaxis of Cell Populations through Confined Spaces at Single-Cell Resolution

PubMed Central

Tong, ZiQiu; Balzer, Eric M.; Dallas, Matthew R.; Hung, Wei-Chien; Stebe, Kathleen J.; Konstantopoulos, Konstantinos

2012-01-01

Cell migration is crucial for both physiological and pathological processes. Current in vitro cell motility assays suffer from various drawbacks, including insufficient temporal and/or optical resolution, or the failure to include a controlled chemotactic stimulus. Here, we address these limitations with a migration chamber that utilizes a self-sustaining chemotactic gradient to induce locomotion through confined environments that emulate physiological settings. Dynamic real-time analysis of both population-scale and single-cell movement are achieved at high resolution. Interior surfaces can be functionalized through adsorption of extracellular matrix components, and pharmacological agents can be administered to cells directly, or indirectly through the chemotactic reservoir. Direct comparison of multiple cell types can be achieved in a single enclosed system to compare inherent migratory potentials. Our novel microfluidic design is therefore a powerful tool for the study of cellular chemotaxis, and is suitable for a wide range of biological and biomedical applications. PMID:22279529

High-resolution Myogenic Lineage Mapping by Single-Cell Mass Cytometry

PubMed Central

Porpiglia, Ermelinda; Samusik, Nikolay; Ho, Andrew Tri Van; Cosgrove, Benjamin D.; Mai, Thach; Davis, Kara L.; Jager, Astraea; Nolan, Garry P.; Bendall, Sean C.; Fantl, Wendy J.; Blau, Helen M.

2017-01-01

Muscle regeneration is a dynamic process during which cell state and identity change over time. A major roadblock has been a lack of tools to resolve a myogenic progression in vivo. Here we capitalize on a transformative technology, single-cell mass cytometry (CyTOF), to identify in vivo skeletal muscle stem cell and previously unrecognized progenitor populations that precede differentiation. We discovered two cell surface markers, CD9 and CD104, whose combined expression enabled in vivo identification and prospective isolation of stem and progenitor cells. Data analysis using the X-shift algorithm paired with single-cell force directed layout visualization, defined a molecular signature of the activated stem cell state (CD44+/CD98+/MyoD+) and delineated a myogenic trajectory during recovery from acute muscle injury. Our studies uncover the dynamics of skeletal muscle regeneration in vivo and pave the way for the elucidation of the regulatory networks that underlie cell-state transitions in muscle diseases and aging. PMID:28414312

A robust and tunable mitotic oscillator in artificial cells

PubMed Central

Wang, Shiyuan; Barnes, Patrick M; Liu, Xuwen; Xu, Haotian; Jin, Minjun; Liu, Allen P

2018-01-01

Single-cell analysis is pivotal to deciphering complex phenomena like heterogeneity, bistability, and asynchronous oscillations, where a population ensemble cannot represent individual behaviors. Bulk cell-free systems, despite having unique advantages of manipulation and characterization of biochemical networks, lack the essential single-cell information to understand a class of out-of-steady-state dynamics including cell cycles. Here, by encapsulating Xenopus egg extracts in water-in-oil microemulsions, we developed artificial cells that are adjustable in sizes and periods, sustain mitotic oscillations for over 30 cycles, and function in forms from the simplest cytoplasmic-only to the more complicated ones involving nuclear dynamics, mimicking real cells. Such innate flexibility and robustness make it key to studying clock properties like tunability and stochasticity. Our results also highlight energy as an important regulator of cell cycles. We demonstrate a simple, powerful, and likely generalizable strategy of integrating strengths of single-cell approaches into conventional in vitro systems to study complex clock functions. PMID:29620527

Technological advances in real-time tracking of cell death

PubMed Central

Skommer, Joanna; Darzynkiewicz, Zbigniew; Wlodkowic, Donald

2010-01-01

Cell population can be viewed as a quantum system, which like Schrödinger’s cat exists as a combination of survival- and death-allowing states. Tracking and understanding cell-to-cell variability in processes of high spatio-temporal complexity such as cell death is at the core of current systems biology approaches. As probabilistic modeling tools attempt to impute information inaccessible by current experimental approaches, advances in technologies for single-cell imaging and omics (proteomics, genomics, metabolomics) should go hand in hand with the computational efforts. Over the last few years we have made exciting technological advances that allow studies of cell death dynamically in real-time and with the unprecedented accuracy. These approaches are based on innovative fluorescent assays and recombinant proteins, bioelectrical properties of cells, and more recently also on state-of-the-art optical spectroscopy. Here, we review current status of the most innovative analytical technologies for dynamic tracking of cell death, and address the interdisciplinary promises and future challenges of these methods. PMID:20519963

Reconstructing the in vivo dynamics of hematopoietic stem cells from telomere length distributions

PubMed Central

Werner, Benjamin; Beier, Fabian; Hummel, Sebastian; Balabanov, Stefan; Lassay, Lisa; Orlikowsky, Thorsten; Dingli, David; Brümmendorf, Tim H; Traulsen, Arne

2015-01-01

We investigate the in vivo patterns of stem cell divisions in the human hematopoietic system throughout life. In particular, we analyze the shape of telomere length distributions underlying stem cell behavior within individuals. Our mathematical model shows that these distributions contain a fingerprint of the progressive telomere loss and the fraction of symmetric cell proliferations. Our predictions are tested against measured telomere length distributions in humans across all ages, collected from lymphocyte and granulocyte sorted telomere length data of 356 healthy individuals, including 47 cord blood and 28 bone marrow samples. We find an increasing stem cell pool during childhood and adolescence and an approximately maintained stem cell population in adults. Furthermore, our method is able to detect individual differences from a single tissue sample, i.e. a single snapshot. Prospectively, this allows us to compare cell proliferation between individuals and identify abnormal stem cell dynamics, which affects the risk of stem cell related diseases. DOI: http://dx.doi.org/10.7554/eLife.08687.001 PMID:26468615

Engineering Microbial Metabolite Dynamics and Heterogeneity.

PubMed

Schmitz, Alexander C; Hartline, Christopher J; Zhang, Fuzhong

2017-10-01

As yields for biological chemical production in microorganisms approach their theoretical maximum, metabolic engineering requires new tools, and approaches for improvements beyond what traditional strategies can achieve. Engineering metabolite dynamics and metabolite heterogeneity is necessary to achieve further improvements in product titers, productivities, and yields. Metabolite dynamics, the ensemble change in metabolite concentration over time, arise from the need for microbes to adapt their metabolism in response to the extracellular environment and are important for controlling growth and productivity in industrial fermentations. Metabolite heterogeneity, the cell-to-cell variation in a metabolite concentration in an isoclonal population, has a significant impact on ensemble productivity. Recent advances in single cell analysis enable a more complete understanding of the processes driving metabolite heterogeneity and reveal metabolic engineering targets. The authors present an overview of the mechanistic origins of metabolite dynamics and heterogeneity, why they are important, their potential effects in chemical production processes, and tools and strategies for engineering metabolite dynamics and heterogeneity. The authors emphasize that the ability to control metabolite dynamics and heterogeneity will bring new avenues of engineering to increase productivity of microbial strains. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Differential sensitivity of Glioma stem cells to Aurora kinase A inhibitors: implications for stem cell mitosis and centrosome dynamics.

PubMed

Mannino, Mariella; Gomez-Roman, Natividad; Hochegger, Helfrid; Chalmers, Anthony J

2014-07-01

Glioma stem-cell-like cells are considered to be responsible for treatment resistance and tumour recurrence following chemo-radiation in glioblastoma patients, but specific targets by which to kill the cancer stem cell population remain elusive. A characteristic feature of stem cells is their ability to undergo both symmetric and asymmetric cell divisions. In this study we have analysed specific features of glioma stem cell mitosis. We found that glioma stem cells appear to be highly prone to undergo aberrant cell division and polyploidization. Moreover, we discovered a pronounced change in the dynamic of mitotic centrosome maturation in these cells. Accordingly, glioma stem cell survival appeared to be strongly dependent on Aurora A activity. Unlike differentiated cells, glioma stem cells responded to moderate Aurora A inhibition with spindle defects, polyploidization and a dramatic increase in cellular senescence, and were selectively sensitive to Aurora A and Plk1 inhibitor treatment. Our study proposes inhibition of centrosomal kinases as a novel strategy to selectively target glioma stem cells. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

On the global dynamics of a chronic myelogenous leukemia model

NASA Astrophysics Data System (ADS)

Krishchenko, Alexander P.; Starkov, Konstantin E.

2016-04-01

In this paper we analyze some features of global dynamics of a three-dimensional chronic myelogenous leukemia (CML) model with the help of the stability analysis and the localization method of compact invariant sets. The behavior of CML model is defined by concentrations of three cellpopulations circulating in the blood: naive T cells, effector T cells specific to CML and CML cancer cells. We prove that the dynamics of the CML system around the tumor-free equilibrium point is unstable. Further, we compute ultimate upper bounds for all three cell populations and provide the existence conditions of the positively invariant polytope. One ultimate lower bound is obtained as well. Moreover, we describe the iterative localization procedure for refining localization bounds; this procedure is based on cyclic using of localizing functions. Applying this procedure we obtain conditions under which the internal tumor equilibrium point is globally asymptotically stable. Our theoretical analyses are supplied by results of the numerical simulation.

Noisy Oscillations in the Actin Cytoskeleton of Chemotactic Amoeba.

PubMed

Negrete, Jose; Pumir, Alain; Hsu, Hsin-Fang; Westendorf, Christian; Tarantola, Marco; Beta, Carsten; Bodenschatz, Eberhard

2016-09-30

Biological systems with their complex biochemical networks are known to be intrinsically noisy. Here we investigate the dynamics of actin polymerization of amoeboid cells, which are close to the onset of oscillations. We show that the large phenotypic variability in the polymerization dynamics can be accurately captured by a generic nonlinear oscillator model in the presence of noise. We determine the relative role of the noise with a single dimensionless, experimentally accessible parameter, thus providing a quantitative description of the variability in a population of cells. Our approach, which rests on a generic description of a system close to a Hopf bifurcation and includes the effect of noise, can characterize the dynamics of a large class of noisy systems close to an oscillatory instability.

Noisy Oscillations in the Actin Cytoskeleton of Chemotactic Amoeba

NASA Astrophysics Data System (ADS)

Negrete, Jose; Pumir, Alain; Hsu, Hsin-Fang; Westendorf, Christian; Tarantola, Marco; Beta, Carsten; Bodenschatz, Eberhard

2016-09-01

Biological systems with their complex biochemical networks are known to be intrinsically noisy. Here we investigate the dynamics of actin polymerization of amoeboid cells, which are close to the onset of oscillations. We show that the large phenotypic variability in the polymerization dynamics can be accurately captured by a generic nonlinear oscillator model in the presence of noise. We determine the relative role of the noise with a single dimensionless, experimentally accessible parameter, thus providing a quantitative description of the variability in a population of cells. Our approach, which rests on a generic description of a system close to a Hopf bifurcation and includes the effect of noise, can characterize the dynamics of a large class of noisy systems close to an oscillatory instability.

Heterogeneity and proliferation of invasive cancer subclones in game theory models of the Warburg effect.

PubMed

Archetti, M

2015-04-01

The Warburg effect, a switch from aerobic energy production to anaerobic glycolysis, promotes tumour proliferation and motility by inducing acidification of the tumour microenvironment. Therapies that reduce acidity could impair tumour growth and invasiveness. I analysed the dynamics of cell proliferation and of resistance to therapies that target acidity, in a population of cells, under the Warburg effect. The dynamics of mutant cells with increased glycolysis and motility has been assessed in a multi-player game with collective interactions in the framework of evolutionary game theory. Perturbations of the level of acidity in the microenvironment have been used to simulate the effect of therapies that target glycolysis. The non-linear effects of glycolysis induce frequency-dependent clonal selection leading to coexistence of glycolytic and non-glycolytic cells within a tumour. Mutants with increased motility can invade such a polymorphic population and spread within the tumour. While reducing acidity may produce a sudden reduction in tumour cell proliferation, frequency-dependent selection enables it to adapt to the new conditions and can enable the tumour to restore its original levels of growth and invasiveness. The acidity produced by glycolysis acts as a non-linear public good that leads to coexistence of cells with high and low glycolysis within the tumour. Such a heterogeneous population can easily adapt to changes in acidity. Therapies that target acidity can only be effective in the long term if the cost of glycolysis is high, that is, under non-limiting oxygen concentrations. Their efficacy, therefore, is reduced when combined with therapies that impair angiogenesis. © 2015 The Authors Cell Proliferation Published by John Wiley & Sons Ltd.

Intratumoral bidirectional transitions between epithelial and mesenchymal cells in triple-negative breast cancer.

PubMed

Yamamoto, Mizuki; Sakane, Kota; Tominaga, Kana; Gotoh, Noriko; Niwa, Takayoshi; Kikuchi, Yasuko; Tada, Keiichiro; Goshima, Naoki; Semba, Kentaro; Inoue, Jun-Ichiro

2017-06-01

Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition MET, are crucial in several stages of cancer metastasis. Epithelial-mesenchymal transition allows cancer cells to move to proximal blood vessels for intravasation. However, because EMT and MET processes are dynamic, mesenchymal cancer cells are likely to undergo MET transiently and subsequently re-undergo EMT to restart the metastatic process. Therefore, spatiotemporally coordinated mutual regulation between EMT and MET could occur during metastasis. To elucidate such regulation, we chose HCC38, a human triple-negative breast cancer cell line, because HCC38 is composed of epithelial and mesenchymal populations at a fixed ratio even though mesenchymal cells proliferate significantly more slowly than epithelial cells. We purified epithelial and mesenchymal cells from Venus-labeled and unlabeled HCC38 cells and mixed them at various ratios to follow EMT and MET. Using this system, we found that the efficiency of EMT is approximately an order of magnitude higher than that of MET and that the two populations significantly enhance the transition of cells from the other population to their own. In addition, knockdown of Zinc finger E-box-binding homeobox 1 (ZEB1) or Zinc finger protein SNAI2 (SLUG) significantly suppressed EMT but promoted partial MET, indicating that ZEB1 and SLUG are crucial to EMT and MET. We also show that primary breast cancer cells underwent EMT that correlated with changes in expression profiles of genes determining EMT status and breast cancer subtype. These changes were very similar to those observed in EMT in HCC38 cells. Consequently, we propose HCC38 as a suitable model to analyze EMT-MET dynamics that could affect the development of triple-negative breast cancer. © 2017 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

Isolation and culture of neural crest cells from embryonic murine neural tube.

PubMed

Pfaltzgraff, Elise R; Mundell, Nathan A; Labosky, Patricia A

2012-06-02

The embryonic neural crest (NC) is a multipotent progenitor population that originates at the dorsal aspect of the neural tube, undergoes an epithelial to mesenchymal transition (EMT) and migrates throughout the embryo, giving rise to diverse cell types. NC also has the unique ability to influence the differentiation and maturation of target organs. When explanted in vitro, NC progenitors undergo self-renewal, migrate and differentiate into a variety of tissue types including neurons, glia, smooth muscle cells, cartilage and bone. NC multipotency was first described from explants of the avian neural tube. In vitro isolation of NC cells facilitates the study of NC dynamics including proliferation, migration, and multipotency. Further work in the avian and rat systems demonstrated that explanted NC cells retain their NC potential when transplanted back into the embryo. Because these inherent cellular properties are preserved in explanted NC progenitors, the neural tube explant assay provides an attractive option for studying the NC in vitro. To attain a better understanding of the mammalian NC, many methods have been employed to isolate NC populations. NC-derived progenitors can be cultured from post-migratory locations in both the embryo and adult to study the dynamics of post-migratory NC progenitors, however isolation of NC progenitors as they emigrate from the neural tube provides optimal preservation of NC cell potential and migratory properties. Some protocols employ fluorescence activated cell sorting (FACS) to isolate a NC population enriched for particular progenitors. However, when starting with early stage embryos, cell numbers adequate for analyses are difficult to obtain with FACS, complicating the isolation of early NC populations from individual embryos. Here, we describe an approach that does not rely on FACS and results in an approximately 96% pure NC population based on a Wnt1-Cre activated lineage reporter. The method presented here is adapted from protocols optimized for the culture of rat NC. The advantages of this protocol compared to previous methods are that 1) the cells are not grown on a feeder layer, 2) FACS is not required to obtain a relatively pure NC population, 3) premigratory NC cells are isolated and 4) results are easily quantified. Furthermore, this protocol can be used for isolation of NC from any mutant mouse model, facilitating the study of NC characteristics with different genetic manipulations. The limitation of this approach is that the NC is removed from the context of the embryo, which is known to influence the survival, migration and differentiation of the NC.

Cancer stem cells and personalized cancer nanomedicine.

PubMed

Gener, Petra; Rafael, Diana Fernandes de Sousa; Fernández, Yolanda; Ortega, Joan Sayós; Arango, Diego; Abasolo, Ibane; Videira, Mafalda; Schwartz, Simo

2016-02-01

Despite the progress in cancer treatment over the past years advanced cancer is still an incurable disease. Special attention is pointed toward cancer stem cell (CSC)-targeted therapies, because this minor cell population is responsible for the treatment resistance, metastatic growth and tumor recurrence. The recently described CSC dynamic phenotype and interconversion model of cancer growth hamper even more the possible success of current cancer treatments in advanced cancer stages. Accordingly, CSCs can be generated through dedifferentiation processes from non-CSCs, in particular, when CSC populations are depleted after treatment. In this context, the use of targeted CSC nanomedicines should be considered as a promising tool to increase CSC sensitivity and efficacy of specific anti-CSC therapies.

Temporal dynamics of the primary human T cell response to yellow fever virus 17D as it matures from an effector- to a memory-type response.

PubMed

Blom, Kim; Braun, Monika; Ivarsson, Martin A; Gonzalez, Veronica D; Falconer, Karolin; Moll, Markus; Ljunggren, Hans-Gustaf; Michaëlsson, Jakob; Sandberg, Johan K

2013-03-01

The live attenuated yellow fever virus (YFV) 17D vaccine provides a good model to study immune responses to an acute viral infection in humans. We studied the temporal dynamics, composition, and character of the primary human T cell response to YFV. The acute YFV-specific effector CD8 T cell response was broad and complex; it was composed of dominant responses that persisted into the memory population, as well as of transient subdominant responses that were not detected at the memory stage. Furthermore, HLA-A2- and HLA-B7-restricted YFV epitope-specific effector cells predominantly displayed a CD45RA(-)CCR7(-)PD-1(+)CD27(high) phenotype, which transitioned into a CD45RA(+)CCR7(-)PD-1(-)CD27(low) memory population phenotype. The functional profile of the YFV-specific CD8 T cell response changed in composition as it matured from an effector- to a memory-type response, and it tended to become less polyfunctional during the course of this transition. Interestingly, activation of CD4 T cells, as well as FOXP3(+) T regulatory cells, in response to YFV vaccination preceded the kinetics of the CD8 T cell response. The present results contribute to our understanding of how immunodominance patterns develop, as well as the phenotypic and functional characteristics of the primary human T cell response to a viral infection as it evolves and matures into memory.

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.

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

In vivo detection of peripherin-specific autoreactive B cells during type 1 diabetes pathogenesis1

PubMed Central

Garabatos, Nahir; Alvarez, Raimon; Carrillo, Jorge; Carrascal, Jorge; Izquierdo, Cristina; Chapman, Harold D.; Presa, Maximiliano; Mora, Conchi; Serreze, David V.; Verdaguer, Joan; Stratmann, Thomas

2014-01-01

Summary Autoreactive B cells are essential for the pathogenesis of type 1 diabetes. The genesis and dynamics of autoreactive B cells remain unknown. Here, we analyzed the immune response in the NOD mouse model to the neuronal protein peripherin (PRPH), a target antigen of islet-infiltrating B cells. PRPH autoreactive B cells recognized a single linear epitope of this protein, in contrast to the multiple epitope recognition commonly observed during autoreactive B cell responses. Autoantibodies to this epitope were also detected in the disease-resistant NOR and C57BL/6 strains. To specifically detect the accumulation of these B cells, we developed a novel approach, octameric peptide display, to follow the dynamics and localization of anti-PRPH B cell during disease progression. Before extended insulitis established, anti-PRPH B cells preferentially accumulated in the peritoneum. Anti-PRPH B cells were likewise detected in C57BL/6 mice, albeit at lower frequencies. As disease unfolded in NOD mice, anti-PRPH B cells invaded the islets and increased in number at the peritoneum of diabetic but not pre-diabetic mice. Isotype switched B cells were only detected in the peritoneum. Anti-PRPH B cells represent a heterogeneous population composed of both B1 and B2 subsets. In the spleen, anti-PRPH B cell were predominantly in the follicular subset. Therefore, anti-PRPH B cells represent a heterogeneous population that is generated early in life but proliferates as diabetes establishes. These findings on the temporal and spatial progression of autoreactive B cells should be relevant for our understanding of B cell function in diabetes pathogenesis. PMID:24610011

Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition

NASA Astrophysics Data System (ADS)

Pfeuty, B.; Kaneko, K.

2016-04-01

The proper functioning of multicellular organisms requires the robust establishment of precise proportions between distinct cell types. This developmental differentiation process typically involves intracellular regulatory and stochastic mechanisms to generate cell-fate diversity as well as intercellular signaling mechanisms to coordinate cell-fate decisions at tissue level. We thus surmise that key insights about the developmental regulation of cell-type proportion can be captured by the modeling study of clustering dynamics in population of inhibitory-coupled noisy bistable systems. This general class of dynamical system is shown to exhibit a very stable two-cluster state, but also metastability, collective oscillations or noise-induced state hopping, which can prevent from timely and reliably reaching a robust and well-proportioned clustered state. To circumvent these obstacles or to avoid fine-tuning, we highlight a general strategy based on dual-time positive feedback loops, such as mediated through transcriptional versus epigenetic mechanisms, which improves proportion regulation by coordinating early and flexible lineage priming with late and firm commitment. This result sheds new light on the respective and cooperative roles of multiple regulatory feedback, stochasticity and lateral inhibition in developmental dynamics.

What Tumor Dynamics Modeling Can Teach us About Exploiting the Stem-Cell View for Better Cancer Treatment

PubMed Central

Day, Roger S

2015-01-01

The cancer stem cell hypothesis is that in human solid cancers, only a small proportion of the cells, the cancer stem cells (CSCs), are self-renewing; the vast majority of the cancer cells are unable to sustain tumor growth indefinitely on their own. In recent years, discoveries have led to the concentration, if not isolation, of putative CSCs. The evidence has mounted that CSCs do exist and are important. This knowledge may promote better understanding of treatment resistance, create opportunities to test agents against CSCs, and open up promise for a fresh approach to cancer treatment. The first clinical trials of new anti-CSC agents are completed, and many others follow. Excitement is mounting that this knowledge will lead to major improvements, even breakthroughs, in treating cancer. However, exploitation of this phenomenon may be more successful if informed by insights into the population dynamics of tumor development. We revive some ideas in tumor dynamics modeling to extract some guidance in designing anti-CSC treatment regimens and the clinical trials that test them. PMID:25780337

Cell fate regulation in the shoot meristem.

PubMed

Laux, T; Mayer, K F

1998-04-01

The shoot meristem is a proliferative centre containing pluripotent stem cells that are the ultimate source of all cells and organs continuously added to the growing shoot. The progeny of the stem cells have two developmental options, either to renew the stem cell population or to leave the meristem and to differentiate, possibly according to signals from more mature tissue. The destiny of each cell depends on its position within the dynamic shoot meristem. Genetic data suggest a simple model in which graded positional information is provided by antagonistic gene functions and is interpreted by genes which regulate cell fate.

A stochastic and dynamical view of pluripotency in mouse embryonic stem cells

PubMed Central

Lee, Esther J.

2018-01-01

Pluripotent embryonic stem cells are of paramount importance for biomedical sciences because of their innate ability for self-renewal and differentiation into all major cell lines. The fateful decision to exit or remain in the pluripotent state is regulated by complex genetic regulatory networks. The rapid growth of single-cell sequencing data has greatly stimulated applications of statistical and machine learning methods for inferring topologies of pluripotency regulating genetic networks. The inferred network topologies, however, often only encode Boolean information while remaining silent about the roles of dynamics and molecular stochasticity inherent in gene expression. Herein we develop a framework for systematically extending Boolean-level network topologies into higher resolution models of networks which explicitly account for the promoter architectures and gene state switching dynamics. We show the framework to be useful for disentangling the various contributions that gene switching, external signaling, and network topology make to the global heterogeneity and dynamics of transcription factor populations. We find the pluripotent state of the network to be a steady state which is robust to global variations of gene switching rates which we argue are a good proxy for epigenetic states of individual promoters. The temporal dynamics of exiting the pluripotent state, on the other hand, is significantly influenced by the rates of genetic switching which makes cells more responsive to changes in extracellular signals. PMID:29451874

Functional nucleic acids as in vivo metabolite and ion biosensors.

PubMed

Alsaafin, Alaa; McKeague, Maureen

2017-08-15

Characterizing the role of metabolites, metals, and proteins is required to understand normal cell function, and ultimately, elucidate the mechanism of disease. Metabolite concentration and transformation results collected from cell lysates or fixed-cells conceal important dynamic information and differences between individual cells that often have profound functional consequences. Functional nucleic acid-based biosensors are emerging tools that are capable of monitoring ions and metabolites in cell populations or whole animals. Functional nucleic acids (FNAs) are a class of biomolecules that can exhibit either ligand binding or enzymatic activity. Unlike their protein analogues or the use of instrument-based analysis, FNA-based biosensors are capable of entering cells without disruption to the cellular environment and can report on the concentration, dynamics, and spatial localization of molecules in cells. Here, we review the types of FNAs that have been used as in vivo biosensors, and how FNAs can be coupled to transduction systems and delivered inside cells. We also provide examples from the literature that demonstrate their impact in practical applications. Finally, we comment on the critical limitations that need to be addressed to enable their use for single-cell dynamic tracking of metabolites and ions in vivo. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

A Molecular Smart Surface for Spatio-Temporal Studies of Cell Mobility

PubMed Central

Lee, Eun-ju; Luo, Wei; Chan, Eugene W. L.; Yousaf, Muhammad N.

2015-01-01

Active migration in both healthy and malignant cells requires the integration of information derived from soluble signaling molecules with positional information gained from interactions with the extracellular matrix and with other cells. How a cell responds and moves involves complex signaling cascades that guide the directional functions of the cytoskeleton as well as the synthesis and release of proteases that facilitate movement through tissues. The biochemical events of the signaling cascades occur in a spatially and temporally coordinated manner then dynamically shape the cytoskeleton in specific subcellular regions. Therefore, cell migration and invasion involve a precise but constantly changing subcellular nano-architecture. A multidisciplinary effort that combines new surface chemistry and cell biological tools is required to understand the reorganization of cytoskeleton triggered by complex signaling during migration. Here we generate a class of model substrates that modulate the dynamic environment for a variety of cell adhesion and migration experiments. In particular, we use these dynamic substrates to probe in real-time how the interplay between the population of cells, the initial pattern geometry, ligand density, ligand affinity and integrin composition affects cell migration and growth. Whole genome microarray analysis indicates that several classes of genes ranging from signal transduction to cytoskeletal reorganization are differentially regulated depending on the nature of the surface conditions. PMID:26030281

Nonlinear dynamics support a linear population code in a retinal target-tracking circuit.

PubMed

Leonardo, Anthony; Meister, Markus

2013-10-23

A basic task faced by the visual system of many organisms is to accurately track the position of moving prey. The retina is the first stage in the processing of such stimuli; the nature of the transformation here, from photons to spike trains, constrains not only the ultimate fidelity of the tracking signal but also the ease with which it can be extracted by other brain regions. Here we demonstrate that a population of fast-OFF ganglion cells in the salamander retina, whose dynamics are governed by a nonlinear circuit, serve to compute the future position of the target over hundreds of milliseconds. The extrapolated position of the target is not found by stimulus reconstruction but is instead computed by a weighted sum of ganglion cell outputs, the population vector average (PVA). The magnitude of PVA extrapolation varies systematically with target size, speed, and acceleration, such that large targets are tracked most accurately at high speeds, and small targets at low speeds, just as is seen in the motion of real prey. Tracking precision reaches the resolution of single photoreceptors, and the PVA algorithm performs more robustly than several alternative algorithms. If the salamander brain uses the fast-OFF cell circuit for target extrapolation as we suggest, the circuit dynamics should leave a microstructure on the behavior that may be measured in future experiments. Our analysis highlights the utility of simple computations that, while not globally optimal, are efficiently implemented and have close to optimal performance over a limited but ethologically relevant range of stimuli.

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.

Spatial computation of intratumoral T cells correlates with survival of patients with pancreatic cancer.

PubMed

Carstens, Julienne L; Correa de Sampaio, Pedro; Yang, Dalu; Barua, Souptik; Wang, Huamin; Rao, Arvind; Allison, James P; LeBleu, Valerie S; Kalluri, Raghu

2017-04-27

The exact nature and dynamics of pancreatic ductal adenocarcinoma (PDAC) immune composition remains largely unknown. Desmoplasia is suggested to polarize PDAC immunity. Therefore, a comprehensive evaluation of the composition and distribution of desmoplastic elements and T-cell infiltration is necessary to delineate their roles. Here we develop a novel computational imaging technology for the simultaneous evaluation of eight distinct markers, allowing for spatial analysis of distinct populations within the same section. We report a heterogeneous population of infiltrating T lymphocytes. Spatial distribution of cytotoxic T cells in proximity to cancer cells correlates with increased overall patient survival. Collagen-I and αSMA + fibroblasts do not correlate with paucity in T-cell accumulation, suggesting that PDAC desmoplasia may not be a simple physical barrier. Further exploration of this technology may improve our understanding of how specific stromal composition could impact T-cell activity, with potential impact on the optimization of immune-modulatory therapies.

An autoregulatory circuit for long-range self-organization in Dictyostelium cell populations.

PubMed

Sawai, Satoshi; Thomason, Peter A; Cox, Edward C

2005-01-20

Nutrient-deprived Dictyostelium amoebae aggregate to form a multicellular structure by chemotaxis, moving towards propagating waves of cyclic AMP that are relayed from cell to cell. Organizing centres are not formed by founder cells, but are dynamic entities consisting of cores of outwardly rotating spiral waves that self-organize in a homogeneous cell population. Spiral waves are ubiquitously observed in chemical reactions as well as in biological systems. Although feedback control of spiral waves in spatially extended chemical reactions has been demonstrated in recent years, the mechanism by which control is achieved in living systems is unknown. Here we show that mutants of the cyclic AMP/protein kinase A pathway show periodic signalling, but fail to organize coherent long-range wave territories, owing to the appearance of numerous spiral cores. A theoretical model suggests that autoregulation of cell excitability mediated by protein kinase A acts to optimize the number of signalling centres.

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

Timing the start of division in E. coli: a single-cell study

NASA Astrophysics Data System (ADS)

Reshes, G.; Vanounou, S.; Fishov, I.; Feingold, M.

2008-12-01

We monitor the shape dynamics of individual E. coli cells using time-lapse microscopy together with accurate image analysis. This allows measuring the dynamics of single-cell parameters throughout the cell cycle. In previous work, we have used this approach to characterize the main features of single-cell morphogenesis between successive divisions. Here, we focus on the behavior of the parameters that are related to cell division and study their variation over a population of 30 cells. In particular, we show that the single-cell data for the constriction width dynamics collapse onto a unique curve following appropriate rescaling of the corresponding variables. This suggests the presence of an underlying time scale that determines the rate at which the cell cycle advances in each individual cell. For the case of cell length dynamics a similar rescaling of variables emphasizes the presence of a breakpoint in the growth rate at the time when division starts, τc. We also find that the τc of individual cells is correlated with their generation time, τg, and inversely correlated with the corresponding length at birth, L0. Moreover, the extent of the T-period, τg - τc, is apparently independent of τg. The relations between τc, τg and L0 indicate possible compensation mechanisms that maintain cell length variability at about 10%. Similar behavior was observed for both fast-growing cells in a rich medium (LB) and for slower growth in a minimal medium (M9-glucose). To reveal the molecular mechanisms that lead to the observed organization of the cell cycle, we should further extend our approach to monitor the formation of the divisome.

Chemosensory brush cells of the trachea. A stable population in a dynamic epithelium.

PubMed

Saunders, Cecil J; Reynolds, Susan D; Finger, Thomas E

2013-08-01

Tracheal brush cells (BCs) are specialized epithelial chemosensors that use the canonical taste transduction cascade to detect irritants. To test whether BCs are replaced at the same rate as other cells in the surrounding epithelium of adult mice, we used 5-bromo-2'-deoxyuridine (BrdU) to label dividing cells. Although scattered BrdU-labeled epithelial cells are present 5-20 days after BrdU, no BCs are labeled. These data indicate that BCs comprise a relatively static population. To determine how BCs are generated during development, we injected 5-day-old mice with BrdU and found labeled BCs and non-BC epithelial cells 5 days after BrdU. During the next 60 days, the percentage of labeled BCs increased, whereas the percentage of other labeled cell types decreased. These data suggest that BCs are generated from non-BC progenitor cells during postnatal tracheal growth. To test whether the adult epithelium retains the capacity to generate BCs, tracheal epithelial cells were recovered from adult mice and grown in an air-liquid interface (ALI) culture. After transition to differentiation conditions, BCs are detected, and comprise 1% of the total cell population by Day 14. BrdU added to cultures before the differentiation of BCs was chased into BCs, indicating that the increase in BC density is attributable to the proliferation of a non-BC progenitor. We conclude that: (1) BCs are normally a static population in adult mice; (2) BC progenitors proliferate and differentiate during neonatal development; and (3) BCs can be regenerated from a proliferative population resident in adult epithelium.

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

Dynamic activation of basilar membrane macrophages in response to chronic sensory cell degeneration in aging mouse cochleae

PubMed Central

Frye, Mitchell D.; Yang, Weiping; Zhang, Celia; Xiong, Binbin; Hu, Bo Hua

2016-01-01

In the sensory epithelium, macrophages have been identified on the scala tympani side of the basilar membrane. These basilar membrane macrophages are the spatially closest immune cells to sensory cells and are able to directly respond to and influence sensory cell pathogenesis. While basilar membrane macrophages have been studied in acute cochlear stresses, their behavior in response to chronic sensory cell degeneration is largely unknown. Here we report a systematic observation of the variance in phenotypes, the changes in morphology and distribution of basilar membrane tissue macrophages in different age groups of C57BL/6J mice, a mouse model of age-related sensory cell degeneration. This study reveals that mature, fully differentiated tissue macrophages, not recently infiltrated monocytes, are the major macrophage population for immune responses to chronic sensory cell death. These macrophages display dynamic changes in their numbers and morphologies as age increases, and the changes are related to the phases of sensory cell degeneration. Notably, macrophage activation precedes sensory cell pathogenesis, and strong macrophage activity is maintained until sensory cell degradation is complete. Collectively, these findings suggest that mature tissue macrophages on the basilar membrane are a dynamic group of cells that are capable of vigorous adaptation to changes in the local sensory epithelium environment influenced by sensory cell status. PMID:27837652

Dynamic activation of basilar membrane macrophages in response to chronic sensory cell degeneration in aging mouse cochleae.

PubMed

Frye, Mitchell D; Yang, Weiping; Zhang, Celia; Xiong, Binbin; Hu, Bo Hua

2017-02-01

In the sensory epithelium, macrophages have been identified on the scala tympani side of the basilar membrane. These basilar membrane macrophages are the spatially closest immune cells to sensory cells and are able to directly respond to and influence sensory cell pathogenesis. While basilar membrane macrophages have been studied in acute cochlear stresses, their behavior in response to chronic sensory cell degeneration is largely unknown. Here we report a systematic observation of the variance in phenotypes, the changes in morphology and distribution of basilar membrane tissue macrophages in different age groups of C57BL/6J mice, a mouse model of age-related sensory cell degeneration. This study reveals that mature, fully differentiated tissue macrophages, not recently infiltrated monocytes, are the major macrophage population for immune responses to chronic sensory cell death. These macrophages display dynamic changes in their numbers and morphologies as age increases, and the changes are related to the phases of sensory cell degeneration. Notably, macrophage activation precedes sensory cell pathogenesis, and strong macrophage activity is maintained until sensory cell degradation is complete. Collectively, these findings suggest that mature tissue macrophages on the basilar membrane are a dynamic group of cells that are capable of vigorous adaptation to changes in the local sensory epithelium environment influenced by sensory cell status. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Towards monitoring real-time cellular response using an integrated microfluidics-MALDI/nESI-ion mobility-mass spectrometry platform

PubMed Central

Enders, Jeffrey R.; Marasco, Christina C.; Kole, Ayeeshik; Nguyen, Bao; Sundarapandian, Sevugarajan; Seale, Kevin T.; Wikswo, John P.; McLean, John A.

2014-01-01

The combination of microfluidic cell trapping devices with ion mobility-mass spectrometry offers the potential for elucidating in real time the dynamic responses of small populations of cells to paracrine signals, changes in metabolite levels, and delivery of drugs and toxins. Preliminary experiments examining peptides in methanol and recording the interactions of yeast and Jurkat cells with their superfusate have identified instrumental setup and control parameters and on-line desalting procedures. Numerous initial experiments demonstrate and validate this new instrumental platform. Future outlooks and potential applications are addressed, specifically how this instrumentation may be used for fully automated systems biology studies of the significantly interdependent, dynamic internal workings of cellular metabolic and signaling pathways. PMID:21073240

On the dynamics of neutral mutations in a mathematical model for a homogeneous stem cell population.

PubMed

Traulsen, Arne; Lenaerts, Tom; Pacheco, Jorge M; Dingli, David

2013-02-01

The theory of the clonal origin of cancer states that a tumour arises from one cell that acquires mutation(s) leading to the malignant phenotype. It is the current belief that many of these mutations give a fitness advantage to the mutant population allowing it to expand, eventually leading to disease. However, mutations that lead to such a clonal expansion need not give a fitness advantage and may in fact be neutral--or almost neutral--with respect to fitness. Such mutant clones can be eliminated or expand stochastically, leading to a malignant phenotype (disease). Mutations in haematopoietic stem cells give rise to diseases such as chronic myeloid leukaemia (CML) and paroxysmal nocturnal haemoglobinuria (PNH). Although neutral drift often leads to clonal extinction, disease is still possible, and in this case, it has important implications both for the incidence of disease and for therapy, as it may be more difficult to eliminate neutral mutations with therapy. We illustrate the consequences of such dynamics, using CML and PNH as examples. These considerations have implications for many other tumours as well.

DNA methylation dynamics during in vivo differentiation of blood and skin stem cells

PubMed Central

Bock, Christoph; Beerman, Isabel; Lien, Wen-Hui; Smith, Zachary D.; Gu, Hongcang; Boyle, Patrick; Gnirke, Andreas; Fuchs, Elaine; Rossi, Derrick J.; Meissner, Alexander

2012-01-01

DNA methylation is a mechanism of epigenetic regulation that is common to all vertebrates. Functional studies underscore its relevance for tissue homeostasis, but the global dynamics of DNA methylation during in vivo differentiation remain underexplored. Here we report high-resolution DNA methylation maps of adult stem cell differentiation in mouse, focusing on 19 purified cell populations of the blood and skin lineages. DNA methylation changes were locus-specific and relatively modest in magnitude. They frequently overlapped with lineage-associated transcription factors and their binding sites, suggesting that DNA methylation may protect cells from aberrant transcription factor activation. DNA methylation and gene expression provided complementary information, and combining the two enabled us to infer the cellular differentiation hierarchy of the blood lineage directly from genomic data. In summary, these results demonstrate that in vivo differentiation of adult stem cells is associated with small but informative changes in the genomic distribution of DNA methylation. PMID:22841485

Elucidation of monocyte/macrophage dynamics and function by intravital imaging

PubMed Central

Rua, Rejane; McGavern, Dorian B.

2015-01-01

Monocytes and macrophages are a diverse population of innate immune cells that play a critical role in homeostasis and inflammation. These cells are surveillant by nature and closely monitor the vasculature and surrounding tissue during states of health and disease. Given their abundance and strategic positioning throughout the body, myeloid cells are among the first responders to any inflammatory challenge and are active participants in most immune-mediated diseases. Recent studies have shed new light on myeloid cell dynamics and function by use of an imaging technique referred to as intravital microscopy (IVM). This powerful approach allows researchers to gain real-time insights into monocytes and macrophages performing homeostatic and inflammatory tasks in living tissues. In this review, we will present a contemporary synopsis of how intravital microscopy has revolutionized our understanding of myeloid cell contributions to vascular maintenance, microbial defense, autoimmunity, tumorigenesis, and acute/chronic inflammatory diseases. PMID:26162402

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

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

Universal Temporal Profile of Replication Origin Activation in Eukaryotes

NASA Astrophysics Data System (ADS)

Goldar, Arach

2011-03-01

The complete and faithful transmission of eukaryotic genome to daughter cells involves the timely duplication of mother cell's DNA. DNA replication starts at multiple chromosomal positions called replication origin. From each activated replication origin two replication forks progress in opposite direction and duplicate the mother cell's DNA. While it is widely accepted that in eukaryotic organisms replication origins are activated in a stochastic manner, little is known on the sources of the observed stochasticity. It is often associated to the population variability to enter S phase. We extract from a growing Saccharomyces cerevisiae population the average rate of origin activation in a single cell by combining single molecule measurements and a numerical deconvolution technique. We show that the temporal profile of the rate of origin activation in a single cell is similar to the one extracted from a replicating cell population. Taking into account this observation we exclude the population variability as the origin of observed stochasticity in origin activation. We confirm that the rate of origin activation increases in the early stage of S phase and decreases at the latter stage. The population average activation rate extracted from single molecule analysis is in prefect accordance with the activation rate extracted from published micro-array data, confirming therefore the homogeneity and genome scale invariance of dynamic of replication process. All these observations point toward a possible role of replication fork to control the rate of origin activation.

Effects of aging in catastrophe on the steady state and dynamics of a microtubule population

NASA Astrophysics Data System (ADS)

Jemseena, V.; Gopalakrishnan, Manoj

2015-05-01

Several independent observations have suggested that the catastrophe transition in microtubules is not a first-order process, as is usually assumed. Recent in vitro observations by Gardner et al. [M. K. Gardner et al., Cell 147, 1092 (2011), 10.1016/j.cell.2011.10.037] showed that microtubule catastrophe takes place via multiple steps and the frequency increases with the age of the filament. Here we investigate, via numerical simulations and mathematical calculations, some of the consequences of the age dependence of catastrophe on the dynamics of microtubules as a function of the aging rate, for two different models of aging: exponential growth, but saturating asymptotically, and purely linear growth. The boundary demarcating the steady-state and non-steady-state regimes in the dynamics is derived analytically in both cases. Numerical simulations, supported by analytical calculations in the linear model, show that aging leads to nonexponential length distributions in steady state. More importantly, oscillations ensue in microtubule length and velocity. The regularity of oscillations, as characterized by the negative dip in the autocorrelation function, is reduced by increasing the frequency of rescue events. Our study shows that the age dependence of catastrophe could function as an intrinsic mechanism to generate oscillatory dynamics in a microtubule population, distinct from hitherto identified ones.

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

Effects of nutrient enrichment on Prymnesium parvum population dynamics and toxicity: Results from field experiments, Lake Possum Kingdom, USA

USGS Publications Warehouse

Roelke, D.L.; Errera, R.M.; Riesling, R.; Brooks, B.W.; Grover, J.P.; Schwierzke, L.; Urena-Boeck, F.; Baker, J.; Pinckney, J.L.

2007-01-01

Large fish kills associated with toxic populations of the haptophyte Prymnesium parvum occur worldwide. In the past 5 yr, incidences of P. parvum blooms in inland water bodies of Texas (USA) have increased dramatically, where cell densities in excess of 1 ?? 107 cells l-1 are typically observed. We conducted field experiments (Lake Possum Kingdom) during the fall and early spring of 28 d duration using 24 enclosures of 1.57 m 3 each. The experiments investigated the effect of nutrient enrichment, immigration of P. parvum and addition of barley straw extract on phytoplankton biomass and assemblage structure, P. parvum population density, zooplankton biomass and assemblage structure, bacteria, and toxicity. Nutrient enrichment stimulated P. parvum population growth beyond bloom proportions (>1 ?? 107 cells l-1). However, P. parvum did not dominate the assemblage under these conditions, as it does during natural blooms. Instead, euglenophytes and chlorophytes dominated. Toxicity, estimated using fish (Pimephales promelas) and cladoceran (Daphnia magna) bioassays and which is linked to P. parvum's allelopathic and mixotrophic effectiveness, was greatly reduced (eliminated in many cases) under conditions of nutrient enrichment. The suppression of toxicity by nutrient addition suggested that targeted and time-limited nutrient manipulations might be used to mitigate the effects of P. parvum blooms. Immigration of P. parvum into natural assemblages and addition of barley straw extract had no significant effect on plankton dynamics. ?? Inter-Research 2007.

Dynamic analysis of apoptosis using cyanine SYTO probes: From classical to microfluidic cytometry

PubMed Central

Wlodkowic, Donald; Skommer, Joanna; Faley, Shannon; Darzynkiewicz, Zbigniew; Cooper, Jonathan M.

2013-01-01

Cell death is a stochastic process, often initiated and/or executed in a multi-pathway/multi-organelle fashion. Therefore, high-throughput single-cell analysis platforms are required to provide detailed characterization of kinetics and mechanisms of cell death in heterogeneous cell populations. However, there is still a largely unmet need for inert fluorescent probes, suitable for prolonged kinetic studies. Here, we compare the use of innovative adaptation of unsymmetrical SYTO dyes for dynamic real-time analysis of apoptosis in conventional as well as microfluidic chip-based systems. We show that cyanine SYTO probes allow non-invasive tracking of intracellular events over extended time. Easy handling and “stain–no wash” protocols open up new opportunities for high-throughput analysis and live-cell sorting. Furthermore, SYTO probes are easily adaptable for detection of cell death using automated microfluidic chip-based cytometry. Overall, the combined use of SYTO probes and state-of-the-art Lab-on-a-Chip platform emerges as a cost effective solution for automated drug screening compared to conventional Annexin V or TUNEL assays. In particular, it should allow for dynamic analysis of samples where low cell number has so far been an obstacle, e.g. primary cancer stems cells or circulating minimal residual tumors. PMID:19298813

Autonomy and Non-autonomy of Angiogenic Cell Movements Revealed by Experiment-Driven Mathematical Modeling.

PubMed

Sugihara, Kei; Nishiyama, Koichi; Fukuhara, Shigetomo; Uemura, Akiyoshi; Arima, Satoshi; Kobayashi, Ryo; Köhn-Luque, Alvaro; Mochizuki, Naoki; Suda, Toshio; Ogawa, Hisao; Kurihara, Hiroki

2015-12-01

Angiogenesis is a multicellular phenomenon driven by morphogenetic cell movements. We recently reported morphogenetic vascular endothelial cell (EC) behaviors to be dynamic and complex. However, the principal mechanisms orchestrating individual EC movements in angiogenic morphogenesis remain largely unknown. Here we present an experiment-driven mathematical model that enables us to systematically dissect cellular mechanisms in branch elongation. We found that cell-autonomous and coordinated actions governed these multicellular behaviors, and a cell-autonomous process sufficiently illustrated essential features of the morphogenetic EC dynamics at both the single-cell and cell-population levels. Through refining our model and experimental verification, we further identified a coordinated mode of tip EC behaviors regulated via a spatial relationship between tip and follower ECs, which facilitates the forward motility of tip ECs. These findings provide insights that enhance our mechanistic understanding of not only angiogenic morphogenesis, but also other types of multicellular phenomenon. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Longitudinal tracking of subpopulation dynamics and molecular changes during LNCaP cell castration and identification of inhibitors that could target the PSA-/lo castration-resistant cells.

PubMed

Rycaj, Kiera; Cho, Eun Jeong; Liu, Xin; Chao, Hsueh-Ping; Liu, Bigang; Li, Qiuhui; Devkota, Ashwini K; Zhang, Dingxiao; Chen, Xin; Moore, John; Dalby, Kevin N; Tang, Dean G

2016-03-22

We have recently demonstrated that the undifferentiated PSA-/lo prostate cancer (PCa) cell population harbors self-renewing long-term tumor-propagating cells that are refractory to castration, thus representing a therapeutic target. Our goals here are, by using the same lineage-tracing reporter system, to track the dynamic changes of PSA-/lo and PSA+ cells upon castration in vitro, investigate the molecular changes accompanying persistent castration, and develop large numbers of PSA-/lo PCa cells for drug screening. To these ends, we treated LNCaP cells infected with the PSAP-GFP reporter with three regimens of castration, i.e., CDSS, CDSS plus bicalutamide, and MDV3100 continuously for up to ~21 months. We observed that in the first ~7 months, castration led to time-dependent increases in PSA-/lo cells, loss of AR and PSA expression, increased expression of cancer stem cell markers, and many other molecular changes. Meanwhile, castrated LNCaP cells became resistant to high concentrations of MDV3100, chemotherapeutic drugs, and other agents. However, targeted and medium-throughput library screening identified several kinase (e.g., IGF-1R, AKT, PI3K/mTOR, Syk, GSK3) inhibitors as well as the BCL2 inhibitor that could effectively sensitize the LNCaP-CRPC cells to killing. Of interest, LNCaP cells castrated for >7 months showed evidence of cyclic changes in AR and the mTOR/AKT signaling pathways potentially involving epigenetic mechanisms. These observations indicate that castration elicits numerous molecular changes and leads to enrichment of PSA-/lo PCa cells. The ability to generate large numbers of PSA-/lo PCa cells should allow future high-throughput screening to identify novel therapeutics that specifically target this population.

Longitudinal tracking of subpopulation dynamics and molecular changes during LNCaP cell castration and identification of inhibitors that could target the PSA−/lo castration-resistant cells

PubMed Central

Rycaj, Kiera; Cho, Eun Jeong; Liu, Xin; Chao, Hsueh-Ping; Liu, Bigang; Li, Qiuhui; Devkota, Ashwini K.; Zhang, Dingxiao; Chen, Xin; Moore, John; Dalby, Kevin N.; Tang, Dean G.

2016-01-01

We have recently demonstrated that the undifferentiated PSA−/lo prostate cancer (PCa) cell population harbors self-renewing long-term tumor-propagating cells that are refractory to castration, thus representing a therapeutic target. Our goals here are, by using the same lineage-tracing reporter system, to track the dynamic changes of PSA−/lo and PSA+ cells upon castration in vitro, investigate the molecular changes accompanying persistent castration, and develop large numbers of PSA−/lo PCa cells for drug screening. To these ends, we treated LNCaP cells infected with the PSAP-GFP reporter with three regimens of castration, i.e., CDSS, CDSS plus bicalutamide, and MDV3100 continuously for up to ~21 months. We observed that in the first ~7 months, castration led to time-dependent increases in PSA−/lo cells, loss of AR and PSA expression, increased expression of cancer stem cell markers, and many other molecular changes. Meanwhile, castrated LNCaP cells became resistant to high concentrations of MDV3100, chemotherapeutic drugs, and other agents. However, targeted and medium-throughput library screening identified several kinase (e.g., IGF-1R, AKT, PI3K/mTOR, Syk, GSK3) inhibitors as well as the BCL2 inhibitor that could effectively sensitize the LNCaP-CRPC cells to killing. Of interest, LNCaP cells castrated for >7 months showed evidence of cyclic changes in AR and the mTOR/AKT signaling pathways potentially involving epigenetic mechanisms. These observations indicate that castration elicits numerous molecular changes and leads to enrichment of PSA−/lo PCa cells. The ability to generate large numbers of PSA−/lo PCa cells should allow future high-throughput screening to identify novel therapeutics that specifically target this population. PMID:26871947

On the long-term fitness of cells in periodically switching environments.

PubMed

Pang, Ning-Ning; Tzeng, Wen-Jer

2008-01-01

Because all the cell populations are capable of making switches between different genetic expression states in response to the environmental change, Thattai and van Oudenaarden (Genetics 167, 523-530, 2004) have raised a very interesting question: In a constantly fluctuating environment, which type of cell population (heterogeneous or homogeneous) is fitter in the long term? This problem is very important to development and evolution biology. We thus take an extensive analysis about how the cell population evolves in a periodically switching environment either with symmetrical time-span or asymmetrical time-span. A complete picture of the phase diagrams for both cases is obtained. Furthermore, we find that the systems with time-dependent cellular transitions all collapse to the same set of dynamical equations with the modified parameters. Furthermore, we also explain in detail how the fitness problem bears much resemblance to the phenomenon, stochastic resonance, in physical sciences. Our results could be helpful for the biologists to design artificial evolution experiments and unveil the mystery of development and evolution.

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

Poly(3-hydroxybutyrate) anabolism in Cupriavidus necator cultivated at various carbon-to-nitrogen ratios: insights from single-cell Raman spectroscopy

NASA Astrophysics Data System (ADS)

Tao, Zhanhua; Zhang, Pengfei; Qin, Zhaojun; Li, Yong-Qing; Wang, Guiwen

2016-09-01

Cupriavidus necator accumulates large amounts of poly(3-hydroxybutyrate) (PHB), a biodegradable substitute for petroleum-based plastics, under certain nutrient conditions. Conventional solvent-extraction-based methods for PHB quantification only obtain average information from cell populations and, thus, mask the heterogeneity among individual cells. Laser tweezers Raman spectroscopy (LTRS) was used to monitor dynamic changes in the contents of PHB, nucleic acids, and proteins in C. necator at the population and single-cell levels when the microorganism cells were cultivated at various carbon-to-nitrogen ratios. The biosynthetic activities of nucleic acids and proteins were maintained at high levels, and only a small amount of PHB was produced when the bacterial cells were cultured under balanced growth conditions. By contrast, the syntheses of nucleic acids and proteins were blocked, and PHB was accumulated in massive amount inside the microbial cells under nitrogen-limiting growth circumstances. Single-cell analysis revealed a relatively high heterogeneity in PHB level at the early stage of the bacterial growth. Additionally, bacterial cells in populations at certain cultivation stages were composed of two or three subpopulations on the basis of their PHB abundance. Overall, LTRS is a reliable single-cell analysis tool that can provide insights into PHB fermentation.

Persistence, period and precision of autonomous cellular oscillators from the zebrafish segmentation clock

PubMed Central

Webb, Alexis B; Lengyel, Iván M; Jörg, David J; Valentin, Guillaume; Jülicher, Frank; Morelli, Luis G; Oates, Andrew C

2016-01-01

In vertebrate development, the sequential and rhythmic segmentation of the body axis is regulated by a “segmentation clock”. This clock is comprised of a population of coordinated oscillating cells that together produce rhythmic gene expression patterns in the embryo. Whether individual cells autonomously maintain oscillations, or whether oscillations depend on signals from neighboring cells is unknown. Using a transgenic zebrafish reporter line for the cyclic transcription factor Her1, we recorded single tailbud cells in vitro. We demonstrate that individual cells can behave as autonomous cellular oscillators. We described the observed variability in cell behavior using a theory of generic oscillators with correlated noise. Single cells have longer periods and lower precision than the tissue, highlighting the role of collective processes in the segmentation clock. Our work reveals a population of cells from the zebrafish segmentation clock that behave as self-sustained, autonomous oscillators with distinctive noisy dynamics. DOI: http://dx.doi.org/10.7554/eLife.08438.001 PMID:26880542

In situ dynamics of cyst and vegetative cell populations of the toxic dinoflagellate Alexandrium catenella in Ago Bay, central Japan

PubMed Central

Ishikawa, Akira; Hattori, Mayuko; Ishii, Ken-Ichiro; Kulis, David M.; Anderson, Donald M.; Imai, Ichiro

2014-01-01

Temporal changes in the in situ germination flux of cysts and the abundance of vegetative cells of the toxic dinoflagellate Alexandrium catenella were investigated in Ago Bay, central Japan from July 2003 to December 2004. The in situ germination flux (cells m−2 day−1) was measured using ‘plankton emergence trap/chambers (PET chambers)’. Germination of the cysts in the sediments occurred continuously during the study, ranging from 52 to 1753 cells m−2 day−1, with no temporal trend. This germination pattern appeared to be promoted by a short mandatory dormancy period for newly formed cysts coupled with a broad temperature window for germination. For the vegetative populations, high abundances (>105 cells m−2) were recorded in the water column from spring to summer and from autumn to early winter. The size of the vegetative populations did not correlate with the cyst germination flux but rather larger vegetative populations were often observed when the water temperature was around 20°C, indicating that bloom development was mainly regulated by the temperature. Nonetheless, the continuous germination pattern of A. catenella is advantageous enabling the germinated cells to immediately exploit favorable bloom conditions. PMID:25221373

Probabilistic Learning by Rodent Grid Cells

PubMed Central

Cheung, Allen

2016-01-01

Mounting evidence shows mammalian brains are probabilistic computers, but the specific cells involved remain elusive. Parallel research suggests that grid cells of the mammalian hippocampal formation are fundamental to spatial cognition but their diverse response properties still defy explanation. No plausible model exists which explains stable grids in darkness for twenty minutes or longer, despite being one of the first results ever published on grid cells. Similarly, no current explanation can tie together grid fragmentation and grid rescaling, which show very different forms of flexibility in grid responses when the environment is varied. Other properties such as attractor dynamics and grid anisotropy seem to be at odds with one another unless additional properties are assumed such as a varying velocity gain. Modelling efforts have largely ignored the breadth of response patterns, while also failing to account for the disastrous effects of sensory noise during spatial learning and recall, especially in darkness. Here, published electrophysiological evidence from a range of experiments are reinterpreted using a novel probabilistic learning model, which shows that grid cell responses are accurately predicted by a probabilistic learning process. Diverse response properties of probabilistic grid cells are statistically indistinguishable from rat grid cells across key manipulations. A simple coherent set of probabilistic computations explains stable grid fields in darkness, partial grid rescaling in resized arenas, low-dimensional attractor grid cell dynamics, and grid fragmentation in hairpin mazes. The same computations also reconcile oscillatory dynamics at the single cell level with attractor dynamics at the cell ensemble level. Additionally, a clear functional role for boundary cells is proposed for spatial learning. These findings provide a parsimonious and unified explanation of grid cell function, and implicate grid cells as an accessible neuronal population readout of a set of probabilistic spatial computations. PMID:27792723

Turning Oscillations Into Opportunities: Lessons from a Bacterial Decision Gate

NASA Astrophysics Data System (ADS)

Schultz, Daniel; Lu, Mingyang; Stavropoulos, Trevor; Onuchic, Jose'; Ben-Jacob, Eshel

2013-04-01

Sporulation vs. competence provides a prototypic example of collective cell fate determination. The decision is performed by the action of three modules: 1) A stochastic competence switch whose transition probability is regulated by population density, population stress and cell stress. 2) A sporulation timer whose clock rate is regulated by cell stress and population stress. 3) A decision gate that is coupled to the timer via a special repressilator-like loop. We show that the distinct circuit architecture of this gate leads to special dynamics and noise management characteristics: The gate opens a time-window of opportunity for competence transitions during which it generates oscillations that are turned into a chain of transition opportunities - each oscillation opens a short interval with high transition probability. The special architecture of the gate also leads to filtering of external noise and robustness against internal noise and variations in the circuit parameters.

Turning Oscillations Into Opportunities: Lessons from a Bacterial Decision Gate

PubMed Central

Schultz, Daniel; Lu, Mingyang; Stavropoulos, Trevor; Onuchic, Jose'; Ben-Jacob, Eshel

2013-01-01

Sporulation vs. competence provides a prototypic example of collective cell fate determination. The decision is performed by the action of three modules: 1) A stochastic competence switch whose transition probability is regulated by population density, population stress and cell stress. 2) A sporulation timer whose clock rate is regulated by cell stress and population stress. 3) A decision gate that is coupled to the timer via a special repressilator-like loop. We show that the distinct circuit architecture of this gate leads to special dynamics and noise management characteristics: The gate opens a time-window of opportunity for competence transitions during which it generates oscillations that are turned into a chain of transition opportunities – each oscillation opens a short interval with high transition probability. The special architecture of the gate also leads to filtering of external noise and robustness against internal noise and variations in the circuit parameters. PMID:23591544

Bringing consistency to simulation of population models--Poisson simulation as a bridge between micro and macro simulation.

PubMed

Gustafsson, Leif; Sternad, Mikael

2007-10-01

Population models concern collections of discrete entities such as atoms, cells, humans, animals, etc., where the focus is on the number of entities in a population. Because of the complexity of such models, simulation is usually needed to reproduce their complete dynamic and stochastic behaviour. Two main types of simulation models are used for different purposes, namely micro-simulation models, where each individual is described with its particular attributes and behaviour, and macro-simulation models based on stochastic differential equations, where the population is described in aggregated terms by the number of individuals in different states. Consistency between micro- and macro-models is a crucial but often neglected aspect. This paper demonstrates how the Poisson Simulation technique can be used to produce a population macro-model consistent with the corresponding micro-model. This is accomplished by defining Poisson Simulation in strictly mathematical terms as a series of Poisson processes that generate sequences of Poisson distributions with dynamically varying parameters. The method can be applied to any population model. It provides the unique stochastic and dynamic macro-model consistent with a correct micro-model. The paper also presents a general macro form for stochastic and dynamic population models. In an appendix Poisson Simulation is compared with Markov Simulation showing a number of advantages. Especially aggregation into state variables and aggregation of many events per time-step makes Poisson Simulation orders of magnitude faster than Markov Simulation. Furthermore, you can build and execute much larger and more complicated models with Poisson Simulation than is possible with the Markov approach.

Phagocyte dynamics in a highly regenerative urochordate: insights into development and host defense.

PubMed

Lauzon, Robert J; Brown, Christina; Kerr, Louie; Tiozzo, Stefano

2013-02-15

Phagocytosis is a cellular process by which particles and foreign bodies are engulfed and degraded by specialized cells. It is functionally involved in nutrient acquisition and represents a fundamental mechanism used to remove pathogens and cellular debris. In the marine invertebrate chordate Botryllus schlosseri, cell corpse engulfment by phagocytic cells is the recurrent mechanism of programmed cell clearance and a critical process for the successful execution of asexual regeneration and colony homeostasis. In the present study, we have utilized a naturally occurring process of vascular parabiosis coupled with intravascular microinjection of fluorescent bioparticles and liposomes as tools to investigate the dynamics of phagocyte behavior in real-time during cyclical body regeneration. Our findings indicate that B. schlosseri harbors two major populations of post-mitotic phagocytes, which display distinct phagocytic specificity and homing patterns: a static population that lines the circulatory system epithelia, and a mobile population that continuously recirculates throughout the colony and exhibits a characteristic homing pattern within mesenchymal niches called ventral islands (VI). We observed that a significant proportion of ventral island phagocytes (VIP) die and are engulfed by other VIP following takeover. Selective impairment of VIP activity curtailed zooid resorption and asexual development. Together, these findings strongly suggest that ventral islands are sites of phagocyte homing and turnover. As botryllid ascidians represent invertebrate chordates capable of whole body regeneration in a non-embryonic scenario, we discuss the pivotal role that phagocytosis plays in homeostasis, tissue renewal and host defense. Copyright © 2012 Elsevier Inc. All rights reserved.

RchyOptimyx: Cellular Hierarchy Optimization for Flow Cytometry

PubMed Central

Aghaeepour, Nima; Jalali, Adrin; O’Neill, Kieran; Chattopadhyay, Pratip K.; Roederer, Mario; Hoos, Holger H.; Brinkman, Ryan R.

2013-01-01

Analysis of high-dimensional flow cytometry datasets can reveal novel cell populations with poorly understood biology. Following discovery, characterization of these populations in terms of the critical markers involved is an important step, as this can help to both better understand the biology of these populations and aid in designing simpler marker panels to identify them on simpler instruments and with fewer reagents (i.e., in resource poor or highly regulated clinical settings). However, current tools to design panels based on the biological characteristics of the target cell populations work exclusively based on technical parameters (e.g., instrument configurations, spectral overlap, and reagent availability). To address this shortcoming, we developed RchyOptimyx (cellular hieraRCHY OPTIMization), a computational tool that constructs cellular hierarchies by combining automated gating with dynamic programming and graph theory to provide the best gating strategies to identify a target population to a desired level of purity or correlation with a clinical outcome, using the simplest possible marker panels. RchyOptimyx can assess and graphically present the trade-offs between marker choice and population specificity in high-dimensional flow or mass cytometry datasets. We present three proof-of-concept use cases for RchyOptimyx that involve 1) designing a panel of surface markers for identification of rare populations that are primarily characterized using their intracellular signature; 2) simplifying the gating strategy for identification of a target cell population; 3) identification of a non-redundant marker set to identify a target cell population. PMID:23044634

In Vivo Biochemistry: Single-Cell Dynamics of Cyclic Di-GMP in Escherichia coli in Response to Zinc Overload.

PubMed

Yeo, Jongchan; Dippel, Andrew B; Wang, Xin C; Hammond, Ming C

2018-01-09

Intracellular signaling enzymes drive critical changes in cellular physiology and gene expression, but their endogenous activities in vivo remain highly challenging to study in real time and for individual cells. Here we show that flow cytometry can be performed in complex media to monitor single-cell population distributions and dynamics of cyclic di-GMP signaling, which controls the bacterial colonization program. These in vivo biochemistry experiments are enabled by our second-generation RNA-based fluorescent (RBF) biosensors, which exhibit high fluorescence turn-on in response to cyclic di-GMP. Specifically, we demonstrate that intracellular levels of cyclic di-GMP in Escherichia coli are repressed with excess zinc, but not with other divalent metals. Furthermore, in both flow cytometry and fluorescence microscopy setups, we monitor the dynamic increase in cellular cyclic di-GMP levels upon zinc depletion and show that this response is due to de-repression of the endogenous diguanylate cyclase DgcZ. In the presence of zinc, cells exhibit enhanced cell motility and increased sensitivity to antibiotics due to inhibited biofilm formation. Taken together, these results showcase the application of RBF biosensors in visualizing single-cell dynamic changes in cyclic di-GMP signaling in direct response to environmental cues such as zinc and highlight our ability to assess whether observed phenotypes are related to specific signaling enzymes and pathways.

Modeling Protective Anti-Tumor Immunity via Preventative Cancer Vaccines Using a Hybrid Agent-based and Delay Differential Equation Approach

PubMed Central

Kim, Peter S.; Lee, Peter P.

2012-01-01

A next generation approach to cancer envisions developing preventative vaccinations to stimulate a person's immune cells, particularly cytotoxic T lymphocytes (CTLs), to eliminate incipient tumors before clinical detection. The purpose of our study is to quantitatively assess whether such an approach would be feasible, and if so, how many anti-cancer CTLs would have to be primed against tumor antigen to provide significant protection. To understand the relevant dynamics, we develop a two-compartment model of tumor-immune interactions at the tumor site and the draining lymph node. We model interactions at the tumor site using an agent-based model (ABM) and dynamics in the lymph node using a system of delay differential equations (DDEs). We combine the models into a hybrid ABM-DDE system and investigate dynamics over a wide range of parameters, including cell proliferation rates, tumor antigenicity, CTL recruitment times, and initial memory CTL populations. Our results indicate that an anti-cancer memory CTL pool of 3% or less can successfully eradicate a tumor population over a wide range of model parameters, implying that a vaccination approach is feasible. In addition, sensitivity analysis of our model reveals conditions that will result in rapid tumor destruction, oscillation, and polynomial rather than exponential decline in the tumor population due to tumor geometry. PMID:23133347

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 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.

Clonotype and repertoire changes drive the functional improvement of HIV-specific CD8 T cell populations under conditions of limited antigenic stimulation

PubMed Central

Janbazian, Loury; Price, David A.; Canderan, Glenda; Filali-Mouhim, Abdelali; Asher, Tedi E.; Ambrozak, David R.; Scheinberg, Phillip; Boulassel, Mohamad Rachid; Routy, Jean-Pierre; Koup, Richard A.; Douek, Daniel C.; Sekaly, Rafick-Pierre; Trautmann, Lydie

2011-01-01

Persistent exposure to cognate antigen leads to the functional impairment and exhaustion of HIV-specific CD8 T cells. Antigen withdrawal, due either to antiretroviral treatment or the emergence of epitope escape mutations, causes HIV-specific CD8 T cell responses to wane over time. However, this process does not continue to extinction, and residual CD8 T cells likely play an important role in the control of HIV replication. Here, we conducted a longitudinal analysis of clonality, phenotype and function to define the characteristics of HIV-specific CD8 T cell populations that persist under conditions of limited antigenic stimulation. Antigen decay was associated with dynamic changes in the TCR repertoire, increased expression of CD45RA and CD127, decreased expression of PD-1 and the emergence of poly-functional HIV-specific CD8 T cells. High definition analysis of individual clonotypes revealed that the antigen loss-induced gain of function within HIV-specific CD8 T cell populations could be attributed to two non-exclusive mechanisms: (i) functional improvement of persisting clonotypes; and, (ii) recruitment of particular clonotypes endowed with superior functional capabilities. PMID:22210916

Single-Cell Microfluidics to Study the Effects of Genome Deletion on Bacterial Growth Behavior.

PubMed

Yuan, Xiaofei; Couto, Jillian M; Glidle, Andrew; Song, Yanqing; Sloan, William; Yin, Huabing

2017-12-15

By directly monitoring single cell growth in a microfluidic platform, we interrogated genome-deletion effects in Escherichia coli strains. We compared the growth dynamics of a wild type strain with a clean genome strain, and their derived mutants at the single-cell level. A decreased average growth rate and extended average lag time were found for the clean genome strain, compared to those of the wild type strain. Direct correlation between the growth rate and lag time of individual cells showed that the clean genome population was more heterogeneous. Cell culturability (the ratio of growing cells to the sum of growing and nongrowing cells) of the clean genome population was also lower. Interestingly, after the random mutations induced by a glucose starvation treatment, for the clean genome population mutants that had survived the competition of chemostat culture, each parameter markedly improved (i.e., the average growth rate and cell culturability increased, and the lag time and heterogeneity decreased). However, this effect was not seen in the wild type strain; the wild type mutants cultured in a chemostat retained a high diversity of growth phenotypes. These results suggest that quasi-essential genes that were deleted in the clean genome might be required to retain a diversity of growth characteristics at the individual cell level under environmental stress. These observations highlight that single-cell microfluidics can reveal subtle individual cellular responses, enabling in-depth understanding of the population.

Epigenetic Marks Define the Lineage and Differentiation Potential of Two Distinct Neural Crest-Derived Intermediate Odontogenic Progenitor Populations

PubMed Central

Gopinathan, Gokul; Kolokythas, Antonia

2013-01-01

Epigenetic mechanisms, such as histone modifications, play an active role in the differentiation and lineage commitment of mesenchymal stem cells. In the present study, epigenetic states and differentiation profiles of two odontogenic neural crest-derived intermediate progenitor populations were compared: dental pulp (DP) and dental follicle (DF). ChIP on chip assays revealed substantial H3K27me3-mediated repression of odontoblast lineage genes DSPP and dentin matrix protein 1 (DMP1) in DF cells, but not in DP cells. Mineralization inductive conditions caused steep increases of mineralization and patterning gene expression levels in DP cells when compared to DF cells. In contrast, mineralization induction resulted in a highly dynamic histone modification response in DF cells, while there was only a subdued effect in DP cells. Both DF and DP progenitors featured H3K4me3-active marks on the promoters of early mineralization genes RUNX2, MSX2, and DLX5, while OSX, IBSP, and BGLAP promoters were enriched for H3K9me3 or H3K27me3. Compared to DF cells, DP cells expressed higher levels of three pluripotency-associated genes, OCT4, NANOG, and SOX2. Finally, gene ontology comparison of bivalent marks unique for DP and DF cells highlighted cell–cell attachment genes in DP cells and neurogenesis genes in DF cells. In conclusion, the present study indicates that the DF intermediate odontogenic neural crest lineage is distinguished from its DP counterpart by epigenetic repression of DSPP and DMP1 genes and through dynamic histone enrichment responses to mineralization induction. Findings presented here highlight the crucial role of epigenetic regulatory mechanisms in the terminal differentiation of odontogenic neural crest lineages. PMID:23379639

Interplay between population firing stability and single neuron dynamics in hippocampal networks

PubMed Central

Slomowitz, Edden; Styr, Boaz; Vertkin, Irena; Milshtein-Parush, Hila; Nelken, Israel; Slutsky, Michael; Slutsky, Inna

2015-01-01

Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi.org/10.7554/eLife.04378.001 PMID:25556699

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.

Population dynamics in vasopressin cells.

PubMed

Leng, Gareth; Brown, Colin; Sabatier, Nancy; Scott, Victoria

2008-01-01

Most neurons sense and code change, and when presented with a constant stimulus they adapt, so as to be able to detect a fresh change. However, for some things it is important to know their absolute level; to encode such information, neurons must sustain their response to an unchanging stimulus while remaining able to respond to a change in that stimulus. One system that encodes the absolute level of a stimulus is the vasopressin system, which generates a hormonal signal that is proportional to plasma osmolality. Vasopressin cells sense plasma osmolality and secrete appropriate levels of vasopressin from the neurohypophysis as needed to control water excretion; this requires sustained secretion under basal conditions and the ability to increase (or decrease) secretion should plasma osmolality change. Here we explore the mechanisms that enable vasopressin cells to fulfill this function, and consider how coordination between the cells might distribute the secretory load across the population of vasopressin cells. 2008 S. Karger AG, Basel.

Deciphering the landscape of host barriers to Listeria monocytogenes infection.

PubMed

Zhang, Ting; Abel, Sören; Abel Zur Wiesch, Pia; Sasabe, Jumpei; Davis, Brigid M; Higgins, Darren E; Waldor, Matthew K

2017-06-13

Listeria monocytogenes is a common food-borne pathogen that can disseminate from the intestine and infect multiple organs. Here, we used sequence tag-based analysis of microbial populations (STAMP) to investigate L monocytogenes population dynamics during infection. We created a genetically barcoded library of murinized L monocytogenes and then used deep sequencing to track the pathogen's dissemination routes and quantify its founding population ( N b ) sizes in different organs. We found that the pathogen disseminates from the gastrointestinal tract to distal sites through multiple independent routes and that N b sizes vary greatly among tissues, indicative of diverse host barriers to infection. Unexpectedly, comparative analyses of sequence tags revealed that fecally excreted organisms are largely derived from the very small number of L. monocytogenes cells that colonize the gallbladder. Immune depletion studies suggest that distinct innate immune cells restrict the pathogen's capacity to establish replicative niches in the spleen and liver. Finally, studies in germ-free mice suggest that the microbiota plays a critical role in the development of the splenic, but not the hepatic, barriers that prevent L. monocytogenes from seeding these organs. Collectively, these observations illustrate the potency of the STAMP approach to decipher the impact of host factors on population dynamics of pathogens during infection.

Deciphering the landscape of host barriers to Listeria monocytogenes infection

PubMed Central

Zhang, Ting; Abel, Sören; Abel zur Wiesch, Pia; Sasabe, Jumpei; Davis, Brigid M.; Higgins, Darren E.; Waldor, Matthew K.

2017-01-01

Listeria monocytogenes is a common food-borne pathogen that can disseminate from the intestine and infect multiple organs. Here, we used sequence tag-based analysis of microbial populations (STAMP) to investigate L. monocytogenes population dynamics during infection. We created a genetically barcoded library of murinized L. monocytogenes and then used deep sequencing to track the pathogen’s dissemination routes and quantify its founding population (Nb) sizes in different organs. We found that the pathogen disseminates from the gastrointestinal tract to distal sites through multiple independent routes and that Nb sizes vary greatly among tissues, indicative of diverse host barriers to infection. Unexpectedly, comparative analyses of sequence tags revealed that fecally excreted organisms are largely derived from the very small number of L. monocytogenes cells that colonize the gallbladder. Immune depletion studies suggest that distinct innate immune cells restrict the pathogen’s capacity to establish replicative niches in the spleen and liver. Finally, studies in germ-free mice suggest that the microbiota plays a critical role in the development of the splenic, but not the hepatic, barriers that prevent L. monocytogenes from seeding these organs. Collectively, these observations illustrate the potency of the STAMP approach to decipher the impact of host factors on population dynamics of pathogens during infection. PMID:28559314

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.

Connecting mitochondrial dynamics and life-or-death events via Bcl-2 family proteins.

PubMed

Aouacheria, Abdel; Baghdiguian, Stephen; Lamb, Heather M; Huska, Jason D; Pineda, Fernando J; Hardwick, J Marie

2017-10-01

The morphology of a population of mitochondria is the result of several interacting dynamical phenomena, including fission, fusion, movement, elimination and biogenesis. Each of these phenomena is controlled by underlying molecular machinery, and when defective can cause disease. New understanding of the relationships between form and function of mitochondria in health and disease is beginning to be unraveled on several fronts. Studies in mammals and model organisms have revealed that mitochondrial morphology, dynamics and function appear to be subject to regulation by the same proteins that regulate apoptotic cell death. One protein family that influences mitochondrial dynamics in both healthy and dying cells is the Bcl-2 protein family. Connecting mitochondrial dynamics with life-death pathway forks may arise from the intersection of Bcl-2 family proteins with the proteins and lipids that determine mitochondrial shape and function. Bcl-2 family proteins also have multifaceted influences on cells and mitochondria, including calcium handling, autophagy and energetics, as well as the subcellular localization of mitochondrial organelles to neuronal synapses. The remarkable range of physical or functional interactions by Bcl-2 family proteins is challenging to assimilate into a cohesive understanding. Most of their effects may be distinct from their direct roles in apoptotic cell death and are particularly apparent in the nervous system. Dual roles in mitochondrial dynamics and cell death extend beyond BCL-2 family proteins. In this review, we discuss many processes that govern mitochondrial structure and function in health and disease, and how Bcl-2 family proteins integrate into some of these processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

BRET-monitoring of the dynamic changes of inositol lipid pools in living cells reveals a PKC-dependent PtdIns4P increase upon EGF and M3 receptor activation.

PubMed

Tóth, József T; Gulyás, Gergő; Tóth, Dániel J; Balla, András; Hammond, Gerald R V; Hunyady, László; Balla, Tamás; Várnai, Péter

2016-03-01

Deciphering many roles played by inositol lipids in signal transduction and membrane function demands experimental approaches that can detect their dynamic accumulation with subcellular accuracy and exquisite sensitivity. The former criterion is met by imaging of fluorescence biosensors in living cells, whereas the latter is facilitated by biochemical measurements from populations. Here, we introduce BRET-based biosensors able to detect rapid changes in inositol lipids in cell populations with both high sensitivity and subcellular resolution in a single, convenient assay. We demonstrate robust and sensitive measurements of PtdIns4P, PtdIns(4,5)P2 and PtdIns(3,4,5)P3 dynamics, as well as changes in cytoplasmic Ins(1,4,5)P3 levels. Measurements were made during either experimental activation of lipid degradation, or PI 3-kinase and phospholipase C mediated signal transduction. Our results reveal a previously unappreciated synthesis of PtdIns4P that accompanies moderate activation of phospholipase C signaling downstream of both EGF and muscarinic M3 receptor activation. This signaling-induced PtdIns4P synthesis relies on protein kinase C, and implicates a feedback mechanism in the control of inositol lipid metabolism during signal transduction. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Ecological feedback in quorum-sensing microbial populations can induce heterogeneous production of autoinducers

PubMed Central

Bauer, Matthias; Knebel, Johannes; Lechner, Matthias; Pickl, Peter; Frey, Erwin

2017-01-01

Autoinducers are small signaling molecules that mediate intercellular communication in microbial populations and trigger coordinated gene expression via ‘quorum sensing’. Elucidating the mechanisms that control autoinducer production is, thus, pertinent to understanding collective microbial behavior, such as virulence and bioluminescence. Recent experiments have shown a heterogeneous promoter activity of autoinducer synthase genes, suggesting that some of the isogenic cells in a population might produce autoinducers, whereas others might not. However, the mechanism underlying this phenotypic heterogeneity in quorum-sensing microbial populations has remained elusive. In our theoretical model, cells synthesize and secrete autoinducers into the environment, up-regulate their production in this self-shaped environment, and non-producers replicate faster than producers. We show that the coupling between ecological and population dynamics through quorum sensing can induce phenotypic heterogeneity in microbial populations, suggesting an alternative mechanism to stochastic gene expression in bistable gene regulatory circuits. DOI: http://dx.doi.org/10.7554/eLife.25773.001 PMID:28741470

Final Report: DOE award: ER64516-1031199-0013966 2007-2011 Genomic Structure, Metagenomics, Horizontal Gene Transfer, and Natural Diversity of Prochlorococcus and Vibrio

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

Chisholm, Sally; Polz, Martin F.; Alm, Eric J

Our overarching goal with this proposal was to develop a deep understanding of the design of Prochlorococcus and Vibrio cells, the variations in their designs, and the constraints that have shaped this variation at the cell-environment interface. That is, we wanted to develop our understanding of the biology of these microbes at all scales of biological organization, from individual cell design to the dynamics of large populations.

Spatio-temporal morphology changes in and quenching effects on the 2D spreading dynamics of cell colonies in both plain and methylcellulose-containing culture media.

PubMed

Muzzio, N E; Pasquale, M A; Huergo, M A C; Bolzán, A E; González, P H; Arvia, A J

2016-06-01

To deal with complex systems, microscopic and global approaches become of particular interest. Our previous results from the dynamics of large cell colonies indicated that their 2D front roughness dynamics is compatible with the standard Kardar-Parisi-Zhang (KPZ) or the quenched KPZ equations either in plain or methylcellulose (MC)-containing gel culture media, respectively. In both cases, the influence of a non-uniform distribution of the colony constituents was significant. These results encouraged us to investigate the overall dynamics of those systems considering the morphology and size, the duplication rate, and the motility of single cells. For this purpose, colonies with different cell populations (N) exhibiting quasi-circular and quasi-linear growth fronts in plain and MC-containing culture media are investigated. For small N, the average radial front velocity and its change with time depend on MC concentration. MC in the medium interferes with cell mitosis, contributes to the local enlargement of cells, and increases the distribution of spatio-temporal cell density heterogeneities. Colony spreading in MC-containing media proceeds under two main quenching effects, I and II; the former mainly depending on the culture medium composition and structure and the latter caused by the distribution of enlarged local cell domains. For large N, colony spreading occurs at constant velocity. The characteristics of cell motility, assessed by measuring their trajectories and the corresponding velocity field, reflect the effect of enlarged, slow-moving cells and the structure of the medium. Local average cell size distribution and individual cell motility data from plain and MC-containing media are qualitatively consistent with the predictions of both the extended cellular Potts models and the observed transition of the front roughness dynamics from a standard KPZ to a quenched KPZ. In this case, quenching effects I and II cooperate and give rise to the quenched-KPZ equation. Seemingly, these results show a possible way of linking the cellular Potts models and the 2D colony front roughness dynamics.

Dynamical mechanism of circadian singularity behavior in Neurospora

NASA Astrophysics Data System (ADS)

Sun, Maorong; Wang, Yi; Xu, Xin; Yang, Ling

2016-09-01

Many organisms have oscillators with a period of about 24 hours, called "circadian clocks". They employ negative biochemical feedback loops that are self-contained within a single cell (requiring no cell-to-cell interaction). Circadian singularity behavior is a phenomenon of the abolishment of circadian rhythmicities by a critical stimulus. These behaviors have been found experimentally in Neurospora, human and hamster, by temperature step-up or light pulse. Two alternative models have been proposed to explain this phenomenon: desynchronization of cell populations, and loss of oscillations in all cells by resetting each cell close to a steady state. In this work, we use a mathematical model to investigate the dynamical mechanism of circadian singularity behavior in Neurospora. Our findings suggest that the arrhythmic behavior after the critical stimulus is caused by the collaboration of the desynchronization and the loss of oscillation amplitude. More importantly, we found that the stable manifold of the unstable equilibrium point, instead of the steady state itself, plays a crucial role in circadian singularity behavior.

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.

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.

Active tissue stiffness modulation controls valve interstitial cell phenotype and osteogenic potential in 3D culture.

PubMed

Duan, Bin; Yin, Ziying; Hockaday Kang, Laura; Magin, Richard L; Butcher, Jonathan T

2016-05-01

Calcific aortic valve disease (CAVD) progression is a highly dynamic process whereby normally fibroblastic valve interstitial cells (VIC) undergo osteogenic differentiation, maladaptive extracellular matrix (ECM) composition, structural remodeling, and tissue matrix stiffening. However, how VIC with different phenotypes dynamically affect matrix properties and how the altered matrix further affects VIC phenotypes in response to physiological and pathological conditions have not yet been determined. In this study, we develop 3D hydrogels with tunable matrix stiffness to investigate the dynamic interplay between VIC phenotypes and matrix biomechanics. We find that VIC populated within hydrogels with valve leaflet like stiffness differentiate towards myofibroblasts in osteogenic media, but surprisingly undergo osteogenic differentiation when cultured within lower initial stiffness hydrogels. VIC differentiation progressively stiffens the hydrogel microenvironment, which further upregulates both early and late osteogenic markers. These findings identify a dynamic positive feedback loop that governs acceleration of VIC calcification. Temporal stiffening of pathologically lower stiffness matrix back to normal level, or blocking the mechanosensitive RhoA/ROCK signaling pathway, delays the osteogenic differentiation process. Therefore, direct ECM biomechanical modulation can affect VIC phenotypes towards and against osteogenic differentiation in 3D culture. These findings highlight the importance of the homeostatic maintenance of matrix stiffness to restrict pathological VIC differentiation. We implement 3D hydrogels with tunable matrix stiffness to investigate the dynamic interaction between valve interstitial cells (VIC, major cell population in heart valve) and matrix biomechanics. This work focuses on how human VIC responses to changing 3D culture environments. Our findings identify a dynamic positive feedback loop that governs acceleration of VIC calcification, which is the hallmark of calcific aortic valve disease. Temporal stiffening of pathologically lower stiffness matrix back to normal level, or blocking the mechanosensitive signaling pathway, delays VIC osteogenic differentiation. Our findings provide an improved understanding of VIC-matrix interactions to aid in interpretation of VIC calcification studies in vitro and suggest that ECM disruption resulting in local tissue stiffness decreases may promote calcific aortic valve disease. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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

Stochastic Simulation of Biomolecular Networks in Dynamic Environments

PubMed Central

Voliotis, Margaritis; Thomas, Philipp; Grima, Ramon; Bowsher, Clive G.

2016-01-01

Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate—using decision-making by a large population of quorum sensing bacteria—that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits. PMID:27248512

Isolation and Culture of Neural Crest Cells from Embryonic Murine Neural Tube

PubMed Central

Pfaltzgraff, Elise R.; Mundell, Nathan A.; Labosky, Patricia A.

2012-01-01

The embryonic neural crest (NC) is a multipotent progenitor population that originates at the dorsal aspect of the neural tube, undergoes an epithelial to mesenchymal transition (EMT) and migrates throughout the embryo, giving rise to diverse cell types 1-3. NC also has the unique ability to influence the differentiation and maturation of target organs4-6. When explanted in vitro, NC progenitors undergo self-renewal, migrate and differentiate into a variety of tissue types including neurons, glia, smooth muscle cells, cartilage and bone. NC multipotency was first described from explants of the avian neural tube7-9. In vitro isolation of NC cells facilitates the study of NC dynamics including proliferation, migration, and multipotency. Further work in the avian and rat systems demonstrated that explanted NC cells retain their NC potential when transplanted back into the embryo10-13. Because these inherent cellular properties are preserved in explanted NC progenitors, the neural tube explant assay provides an attractive option for studying the NC in vitro. To attain a better understanding of the mammalian NC, many methods have been employed to isolate NC populations. NC-derived progenitors can be cultured from post-migratory locations in both the embryo and adult to study the dynamics of post-migratory NC progenitors11,14-20, however isolation of NC progenitors as they emigrate from the neural tube provides optimal preservation of NC cell potential and migratory properties13,21,22. Some protocols employ fluorescence activated cell sorting (FACS) to isolate a NC population enriched for particular progenitors11,13,14,17. However, when starting with early stage embryos, cell numbers adequate for analyses are difficult to obtain with FACS, complicating the isolation of early NC populations from individual embryos. Here, we describe an approach that does not rely on FACS and results in an approximately 96% pure NC population based on a Wnt1-Cre activated lineage reporter23. The method presented here is adapted from protocols optimized for the culture of rat NC11,13. The advantages of this protocol compared to previous methods are that 1) the cells are not grown on a feeder layer, 2) FACS is not required to obtain a relatively pure NC population, 3) premigratory NC cells are isolated and 4) results are easily quantified. Furthermore, this protocol can be used for isolation of NC from any mutant mouse model, facilitating the study of NC characteristics with different genetic manipulations. The limitation of this approach is that the NC is removed from the context of the embryo, which is known to influence the survival, migration and differentiation of the NC2,24-28. PMID:22688801

Compartmental genomics in living cells revealed by single-cell nanobiopsy.

PubMed

Actis, Paolo; Maalouf, Michelle M; Kim, Hyunsung John; Lohith, Akshar; Vilozny, Boaz; Seger, R Adam; Pourmand, Nader

2014-01-28

The ability to study the molecular biology of living single cells in heterogeneous cell populations is essential for next generation analysis of cellular circuitry and function. Here, we developed a single-cell nanobiopsy platform based on scanning ion conductance microscopy (SICM) for continuous sampling of intracellular content from individual cells. The nanobiopsy platform uses electrowetting within a nanopipette to extract cellular material from living cells with minimal disruption of the cellular milieu. We demonstrate the subcellular resolution of the nanobiopsy platform by isolating small subpopulations of mitochondria from single living cells, and quantify mutant mitochondrial genomes in those single cells with high throughput sequencing technology. These findings may provide the foundation for dynamic subcellular genomic analysis.

Decellularized adipose tissue microcarriers as a dynamic culture platform for human adipose-derived stem/stromal cell expansion.

PubMed

Yu, Claire; Kornmuller, Anna; Brown, Cody; Hoare, Todd; Flynn, Lauren E

2017-03-01

With the goal of designing a clinically-relevant expansion strategy for human adipose-derived stem/stromal cells (ASCs), methods were developed to synthesize porous microcarriers derived purely from human decellularized adipose tissue (DAT). An electrospraying approach was applied to generate spherical DAT microcarriers with an average diameter of 428 ± 41 μm, which were soft, compliant, and stable in long-term culture without chemical crosslinking. Human ASCs demonstrated enhanced proliferation on the DAT microcarriers relative to commercially-sourced Cultispher-S microcarriers within a spinner culture system over 1 month. ASC immunophenotype was maintained post expansion, with a trend for reduced expression of the cell adhesion receptors CD73, CD105, and CD29 under dynamic conditions. Upregulation of the early lineage-specific genes PPARγ, LPL, and COMP was observed in the ASCs expanded on the DAT microcarriers, but the cells retained their multilineage differentiation capacity. Comparison of adipogenic and osteogenic differentiation in 2-D cultures prepared with ASCs pre-expanded on the DAT microcarriers or Cultispher-S microcarriers revealed similar adipogenic and enhanced osteogenic marker expression in the DAT microcarrier group, which had undergone a higher population fold change. Further, histological staining results suggested a more homogeneous differentiation response in the ASCs expanded on the DAT microcarriers as compared to either Cultispher-S microcarriers or tissue culture polystyrene. A pilot chondrogenesis study revealed higher levels of chondrogenic gene and protein expression in the ASCs expanded on the DAT microcarriers relative to all other groups, including the baseline controls. Overall, this study demonstrates the promise of applying dynamic culture with tissue-specific DAT microcarriers as a means of deriving regenerative cell populations. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

PubMed Central

McDonnell, Mark D.; Ward, Lawrence M.

2014-01-01

Abstract Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity. PMID:24743633

Propagating gene expression fronts in a one-dimensional coupled system of artificial cells

NASA Astrophysics Data System (ADS)

Tayar, Alexandra M.; Karzbrun, Eyal; Noireaux, Vincent; Bar-Ziv, Roy H.

2015-12-01

Living systems employ front propagation and spatiotemporal patterns encoded in biochemical reactions for communication, self-organization and computation. Emulating such dynamics in minimal systems is important for understanding physical principles in living cells and in vitro. Here, we report a one-dimensional array of DNA compartments in a silicon chip as a coupled system of artificial cells, offering the means to implement reaction-diffusion dynamics by integrated genetic circuits and chip geometry. Using a bistable circuit we programmed a front of protein synthesis propagating in the array as a cascade of signal amplification and short-range diffusion. The front velocity is maximal at a saddle-node bifurcation from a bistable regime with travelling fronts to a monostable regime that is spatially homogeneous. Near the bifurcation the system exhibits large variability between compartments, providing a possible mechanism for population diversity. This demonstrates that on-chip integrated gene circuits are dynamical systems driving spatiotemporal patterns, cellular variability and symmetry breaking.

Compartmentalized microchannel array for high-throughput analysis of single cell polarized growth and dynamics

DOE PAGES

Geng, Tao; Bredeweg, Erin L.; Szymanski, Craig J.; ...

2015-11-04

Here, interrogating polarized growth is technologically challenging due to extensive cellular branching and uncontrollable environmental conditions in conventional assays. Here we present a robust and high-performance microfluidic system that enables observations of polarized growth with enhanced temporal and spatial control over prolonged periods. The system has built-in tunability and versatility to accommodate a variety of science applications requiring precisely controlled environments. Using the model filamentous fungus, Neurospora crassa, this microfluidic system enabled direct visualization and analysis of cellular heterogeneity in a clonal fungal cell population, nuclear distribution and dynamics at the subhyphal level, and quantitative dynamics of gene expression withmore » single hyphal compartment resolution in response to carbon source starvation and exchange experiments. Although the microfluidic device is demonstrated on filamentous fungi, our technology is immediately extensible to a wide array of other biosystems that exhibit similar polarized cell growth with applications ranging from bioenergy production to human health.« less

Evidence for mesenchymal-like sub-populations within squamous cell carcinomas possessing chemoresistance and phenotypic plasticity.

PubMed

Basu, D; Nguyen, T-T K; Montone, K T; Zhang, G; Wang, L-P; Diehl, J A; Rustgi, A K; Lee, J T; Weinstein, G S; Herlyn, M

2010-07-22

Variable drug responses among malignant cells within individual tumors may represent a barrier to their eradication using chemotherapy. Carcinoma cells expressing mesenchymal markers resist conventional and epidermal growth factor receptor (EGFR)-targeted chemotherapy. In this study, we evaluated whether mesenchymal-like sub-populations within human squamous cell carcinomas (SCCs) with predominantly epithelial features contribute to overall therapy resistance. We identified a mesenchymal-like subset expressing low E-cadherin (Ecad-lo) and high vimentin within the upper aerodigestive tract SCCs. This subset was both isolated from the cell lines and was identified in xenografts and primary clinical specimens. The Ecad-lo subset contained more low-turnover cells, correlating with resistance to the conventional chemotherapeutic paclitaxel in vitro. Epidermal growth factor induced less stimulation of the mitogen-activated protein kinase and phosphatidylinositol-3-kinase pathways in Ecad-lo cells, which was likely due to lower EGFR expression in this subset and correlated with in vivo resistance to the EGFR-targeted antibody, cetuximab. The Ecad-lo and high E-cadherin subsets were dynamic in phenotype, showing the capacity to repopulate each other from single-cell clones. Taken together, these results provide evidence for a low-turnover, mesenchymal-like sub-population in SCCs with diminished EGFR pathway function and intrinsic resistance to conventional and EGFR-targeted chemotherapies.

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.

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.

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.

Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns.

PubMed

Norred, S Elizabeth; Caveney, Patrick M; Chauhan, Gaurav; Collier, Lauren K; Collier, C Patrick; Abel, Steven M; Simpson, Michael L

2018-05-18

Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting-the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increase in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA ("spatial noise") that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. These results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.

Functional connectivity and dynamics of cortical-thalamic networks co-cultured in a dual compartment device

NASA Astrophysics Data System (ADS)

Kanagasabapathi, Thirukumaran T.; Massobrio, Paolo; Barone, Rocco Andrea; Tedesco, Mariateresa; Martinoia, Sergio; Wadman, Wytse J.; Decré, Michel M. J.

2012-06-01

Co-cultures containing dissociated cortical and thalamic cells may provide a unique model for understanding the pathophysiology in the respective neuronal sub-circuitry. In addition, developing an in vitro dissociated co-culture model offers the possibility of studying the system without influence from other neuronal sub-populations. Here we demonstrate a dual compartment system coupled to microelectrode arrays (MEAs) for co-culturing and recording spontaneous activities from neuronal sub-populations. Propagation of electrical activities between cortical and thalamic regions and their interdependence in connectivity is verified by means of a cross-correlation algorithm. We found that burst events originate in the cortical region and drive the entire cortical-thalamic network bursting behavior while mutually weak thalamic connections play a relevant role in sustaining longer burst events in cortical cells. To support these experimental findings, a neuronal network model was developed and used to investigate the interplay between network dynamics and connectivity in the cortical-thalamic system.

Regulation of DM-20 mRNA expression and intracellular translocation of glutathione-S-transferase pi isoform during oligodendrocyte differentiation in the adult rat spinal cord.

PubMed

Kitada, Masaaki; Takeda, Kazuya; Dezawa, Mari

2016-07-01

We previously demonstrated that NG2-positive oligodendrocyte precursor cells (OPCs) do not express DM-20 mRNA and identified a distinct DM-20 mRNA-positive cell population expressing glutathione-S-transferase pi isoform (GST-pi) in the nucleus (GST-pi(Nuc)) of the adult rat spinal cord. As GST-pi intranuclear localization correlates with progenitor cell properties, we examined the differentiation status of this cell population under the intensive 5-bromo-2'-deoxyuridine (BrdU) administration method, consisting of intraperitoneal BrdU injections every 2 h for 48 h. We observed that a certain population of proliferating/proliferated cells expressed DM-20 mRNA, and sometimes two proliferating/proliferated cells were observed still attached to each other. We performed triple staining for BrdU, DM-20 mRNA, and NG2 and found pairs of neighboring BrdU-positive cells, which were considered to originate from the same progenitor cells and where both cells expressed DM-20 mRNA. Triple staining for BrdU, DM-20 mRNA, and GST-pi detected proliferating/proliferated cells exhibiting the GST-pi(Nuc)/DM-20 mRNA-positive expression pattern. These findings suggested the presence of a GST-pi(Nuc)/DM-20 mRNA-positive oligodendrocyte-lineage progenitor cell population in the adult rat spinal cord. However, we did not find any pair of neighboring BrdU-positive cells with this expression pattern. These observations collectively support the idea that GST-pi(Nuc)/DM-20 mRNA-expressing cells are the progeny of NG2-positive OPCs rather than a novel type of oligodendrocyte-lineage progenitor cells and that DM-20 mRNA expression is dynamically regulated during differentiation of OPCs into oligodendrocytes.

Measuring mitotic spindle dynamics in budding yeast

NASA Astrophysics Data System (ADS)

Plumb, Kemp

In order to carry out its life cycle and produce viable progeny through cell division, a cell must successfully coordinate and execute a number of complex processes with high fidelity, in an environment dominated by thermal noise. One important example of such a process is the assembly and positioning of the mitotic spindle prior to chromosome segregation. The mitotic spindle is a modular structure composed of two spindle pole bodies, separated in space and spanned by filamentous proteins called microtubules, along which the genetic material of the cell is held. The spindle is responsible for alignment and subsequent segregation of chromosomes into two equal parts; proper spindle positioning and timing ensure that genetic material is appropriately divided amongst mother and daughter cells. In this thesis, I describe fluorescence confocal microscopy and automated image analysis algorithms, which I have used to observe and analyze the real space dynamics of the mitotic spindle in budding yeast. The software can locate structures in three spatial dimensions and track their movement in time. By selecting fluorescent proteins which specifically label the spindle poles and cell periphery, mitotic spindle dynamics have been measured in a coordinate system relevant to the cell division. I describe how I have characterised the accuracy and precision of the algorithms by simulating fluorescence data for both spindle poles and the budding yeast cell surface. In this thesis I also describe the construction of a microfluidic apparatus that allows for the measurement of long time-scale dynamics of individual cells and the development of a cell population. The tools developed in this thesis work will facilitate in-depth quantitative analysis of the non-equilibrium processes in living cells.

Ultimate dynamics of the Kirschner-Panetta model: Tumor eradication and related problems

NASA Astrophysics Data System (ADS)

Starkov, Konstantin E.; Krishchenko, Alexander P.

2017-10-01

In this paper we consider the ultimate dynamics of the Kirschner-Panetta model which was created for studying the immune response to tumors under special types of immunotherapy. New ultimate upper bounds for compact invariant sets of this model are given, as well as sufficient conditions for the existence of a positively invariant polytope. We establish three types of conditions for the nonexistence of compact invariant sets in the domain of the tumor-cell population. Our main results are two types of conditions for global tumor elimination depending on the ratio between the proliferation rate of the immune cells and their mortality rate. These conditions are described in terms of simple algebraic inequalities imposed on model parameters and treatment parameters. Our theoretical studies of ultimate dynamics are complemented by numerical simulation results.

Copper-free click chemistry for dynamic in vivo imaging

PubMed Central

Baskin, Jeremy M.; Prescher, Jennifer A.; Laughlin, Scott T.; Agard, Nicholas J.; Chang, Pamela V.; Miller, Isaac A.; Lo, Anderson; Codelli, Julian A.; Bertozzi, Carolyn R.

2007-01-01

Dynamic imaging of proteins in live cells is routinely performed by using genetically encoded reporters, an approach that cannot be extended to other classes of biomolecules such as glycans and lipids. Here, we report a Cu-free variant of click chemistry that can label these biomolecules rapidly and selectively in living systems, overcoming the intrinsic toxicity of the canonical Cu-catalyzed reaction. The critical reagent, a substituted cyclooctyne, possesses ring strain and electron-withdrawing fluorine substituents that together promote the [3 + 2] dipolar cycloaddition with azides installed metabolically into biomolecules. This Cu-free click reaction possesses comparable kinetics to the Cu-catalyzed reaction and proceeds within minutes on live cells with no apparent toxicity. With this technique, we studied the dynamics of glycan trafficking and identified a population of sialoglycoconjugates with unexpectedly rapid internalization kinetics. PMID:17942682

Intestinal Escherichia coli colonization in a mallard duck population over four consecutive winter seasons.

PubMed

Rödiger, Stefan; Kramer, Toni; Frömmel, Ulrike; Weinreich, Jörg; Roggenbuck, Dirk; Guenther, Sebastian; Schaufler, Katharina; Schröder, Christian; Schierack, Peter

2015-09-01

We report the population structure and dynamics of one Escherichia coli population of wild mallard ducks in their natural environment over four winter seasons, following the characterization of 100 isolates each consecutive season. Macro-restriction analysis was used to define isolates variously as multi- or 1-year pulsed-field gel electrophoresis (PFGE) types. Isolates were characterized genotypically based on virulence-associated genes (VAGs), phylogenetic markers, and phenotypically based on haemolytic activity, antimicrobial resistance, adhesion to epithelial cells, microcin production, motility and carbohydrate metabolism. Only 12 out of 220 PFGE types were detectable over more than one winter, and classified as multi-year PFGE types. There was a dramatic change of PFGE types within two winter seasons. Nevertheless, the genetic pool (VAGs) and antimicrobial resistance pattern remained remarkably stable. The high diversity and dynamics of this E. coli population were also demonstrated by the occurrence of PFGE subtypes and differences between isolates of one PFGE type (based on VAGs, antimicrobial resistance and adhesion rates). Multi- and 1-year PFGE types differed in antimicrobial resistance, VAGs and adhesion. Other parameters were not prominent colonization factors. In conclusion, the high diversity, dynamics and stable genetic pool of an E. coli population seem to enable their successful colonization of host animal population over time. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

Categorizing Cells on the Basis of their Chemical Profiles: Progress in Single-Cell Mass Spectrometry.

PubMed

Comi, Troy J; Do, Thanh D; Rubakhin, Stanislav S; Sweedler, Jonathan V

2017-03-22

The chemical differences between individual cells within large cellular populations provide unique information on organisms' homeostasis and the development of diseased states. Even genetically identical cell lineages diverge due to local microenvironments and stochastic processes. The minute sample volumes and low abundance of some constituents in cells hinder our understanding of cellular heterogeneity. Although amplification methods facilitate single-cell genomics and transcriptomics, the characterization of metabolites and proteins remains challenging both because of the lack of effective amplification approaches and the wide diversity in cellular constituents. Mass spectrometry has become an enabling technology for the investigation of individual cellular metabolite profiles with its exquisite sensitivity, large dynamic range, and ability to characterize hundreds to thousands of compounds. While advances in instrumentation have improved figures of merit, acquiring measurements at high throughput and sampling from large populations of cells are still not routine. In this Perspective, we highlight the current trends and progress in mass-spectrometry-based analysis of single cells, with a focus on the technologies that will enable the next generation of single-cell measurements.

Cytoskeletal actin dynamics shape a ramifying actin network underpinning immunological synapse formation

PubMed Central

Fritzsche, Marco; Fernandes, Ricardo A.; Chang, Veronica T.; Colin-York, Huw; Clausen, Mathias P.; Felce, James H.; Galiani, Silvia; Erlenkämper, Christoph; Santos, Ana M.; Heddleston, John M.; Pedroza-Pacheco, Isabela; Waithe, Dominic; de la Serna, Jorge Bernardino; Lagerholm, B. Christoffer; Liu, Tsung-li; Chew, Teng-Leong; Betzig, Eric; Davis, Simon J.; Eggeling, Christian

2017-01-01

T cell activation and especially trafficking of T cell receptor microclusters during immunological synapse formation are widely thought to rely on cytoskeletal remodeling. However, important details on the involvement of actin in the latter transport processes are missing. Using a suite of advanced optical microscopes to analyze resting and activated T cells, we show that, following contact formation with activating surfaces, these cells sequentially rearrange their cortical actin across the entire cell, creating a previously unreported ramifying actin network above the immunological synapse. This network shows all the characteristics of an inward-growing transportation network and its dynamics correlating with T cell receptor rearrangements. This actin reorganization is accompanied by an increase in the nanoscale actin meshwork size and the dynamic adjustment of the turnover times and filament lengths of two differently sized filamentous actin populations, wherein formin-mediated long actin filaments support a very flat and stiff contact at the immunological synapse interface. The initiation of immunological synapse formation, as highlighted by calcium release, requires markedly little contact with activating surfaces and no cytoskeletal rearrangements. Our work suggests that incipient signaling in T cells initiates global cytoskeletal rearrangements across the whole cell, including a stiffening process for possibly mechanically supporting contact formation at the immunological synapse interface as well as a central ramified transportation network apparently directed at the consolidation of the contact and the delivery of effector functions. PMID:28691087

A diverse and intricate signalling network regulates stem cell fate in the shoot apical meristem.

PubMed

Dodsworth, Steven

2009-12-01

At the shoot apex of plants is a small region known as the shoot apical meristem (SAM) that maintains a population of undifferentiated (stem) cells whilst providing cells for developing lateral organs and the stem. All aerial structures of the plant develop from the SAM post-embryogenesis, enabling plants to grow in a characteristic modular fashion with great phenotypic and developmental plasticity throughout their lifetime. The maintenance of the stem cell population is intimately balanced with cell recruitment into differentiating tissues through intercellular communication involving a complex signalling network. Recent studies have shown that diverse regulators function in SAM maintenance, many of which converge on the WUSCHEL (WUS) gene. In this review the diverse regulatory modules that function in SAM maintenance are discussed: transcriptional and epigenetic control, hormonal regulation, and the balance with organogenesis. The central role of WUS as an integrator of multiple signals is highlighted; in addition, accessory feedback loops emerge as a feature enabling dynamic regulation of the stem cell niche.

Phospholipase C-β1 and β4 Contribute to Non-Genetic Cell-to-Cell Variability in Histamine-Induced Calcium Signals in HeLa Cells

PubMed Central

Ishida, Sachiko; Matsu-ura, Toru; Fukami, Kiyoko; Michikawa, Takayuki; Mikoshiba, Katsuhiko

2014-01-01

A uniform extracellular stimulus triggers cell-specific patterns of Ca2+ signals, even in genetically identical cell populations. However, the underlying mechanism that generates the cell-to-cell variability remains unknown. We monitored cytosolic inositol 1,4,5-trisphosphate (IP3) concentration changes using a fluorescent IP3 sensor in single HeLa cells showing different patterns of histamine-induced Ca2+ oscillations in terms of the time constant of Ca2+ spike amplitude decay and the Ca2+ oscillation frequency. HeLa cells stimulated with histamine exhibited a considerable variation in the temporal pattern of Ca2+ signals and we found that there were cell-specific IP3 dynamics depending on the patterns of Ca2+ signals. RT-PCR and western blot analyses showed that phospholipase C (PLC)-β1, -β3, -β4, -γ1, -δ3 and -ε were expressed at relatively high levels in HeLa cells. Small interfering RNA-mediated silencing of PLC isozymes revealed that PLC-β1 and PLC-β4 were specifically involved in the histamine-induced IP3 increases in HeLa cells. Modulation of IP3 dynamics by knockdown or overexpression of the isozymes PLC-β1 and PLC-β4 resulted in specific changes in the characteristics of Ca2+ oscillations, such as the time constant of the temporal changes in the Ca2+ spike amplitude and the Ca2+ oscillation frequency, within the range of the cell-to-cell variability found in wild-type cell populations. These findings indicate that the heterogeneity in the process of IP3 production, rather than IP3-induced Ca2+ release, can cause cell-to-cell variability in the patterns of Ca2+ signals and that PLC-β1 and PLC-β4 contribute to generate cell-specific Ca2+ signals evoked by G protein-coupled receptor stimulation. PMID:24475116

Effectiveness of nanoencapsulated methotrexate against osteosarcoma cells: in vitro cytotoxicity under dynamic conditions.

PubMed

Mitxelena-Iribarren, O; Hisey, C L; Errazquin-Irigoyen, M; González-Fernández, Y; Imbuluzqueta, E; Mujika, M; Blanco-Prieto, M J; Arana, S

2017-06-01

Cancer is a leading cause of mortality in the world, with osteosarcoma being one of the most common types among children between 1 and 14 years old. Current treatments including preoperative chemotherapy, surgery and postoperative chemotherapy produce several side effects with limited effectiveness. The use of lipid nanoparticles as biodegradable shells for controlled drug delivery shows promise as a more effective and targeted tumor treatment. However, in vitro validation of these vehicles is limited due to fluid stagnation in current techniques, in which nanoparticles sediment onto the bottom of the wells killing the cells by asphyxiation. In the current series of experiments, results obtained with methotrexate-lipid nanoparticles under dynamic assay conditions are presented as a promising alternative to current free drug based therapies. Effects on the viability of the U-2 OS osteosarcoma cell line of recirculation of cell media, free methotrexate and blank and methotrexate containing lipid nanoparticles in a 11 μM concentration were successfully assessed. In addition, several designs for the microfluidic platform used were simulated using COMSOL-Multiphysics, optimized devices were fabricated using soft-lithography and simulated parameters were experimentally validated. Nanoparticles did not sediment to the bottom of the platform, demonstrating the effectiveness of the proposed system. Moreover, encapsulated methotrexate was the most effective treatment, as after 72 h the cell population was reduced nearly 40% while under free methotrexate circulation the cell population doubled. Overall, these results indicate that methotrexate-lipid nanoparticles are a promising targeted therapy for osteosarcoma treatment.

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.

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.

Periodic Pattern of Genetic and Fitness Diversity during Evolution of an Artificial Cell-Like System.

PubMed

Ichihashi, Norikazu; Aita, Takuyo; Motooka, Daisuke; Nakamura, Shota; Yomo, Tetsuya

2015-12-01

Genetic and phenotypic diversity are the basis of evolution. Despite their importance, however, little is known about how they change over the course of evolution. In this study, we analyzed the dynamics of the adaptive evolution of a simple evolvable artificial cell-like system using single-molecule real-time sequencing technology that reads an entire single artificial genome. We found that the genomic RNA population increases in fitness intermittently, correlating with a periodic pattern of genetic and fitness diversity produced by repeated diversification and domination. In the diversification phase, a genomic RNA population spreads within a genetic space by accumulating mutations until mutants with higher fitness are generated, resulting in an increase in fitness diversity. In the domination phase, the mutants with higher fitness dominate, decreasing both the fitness and genetic diversity. This study reveals the dynamic nature of genetic and fitness diversity during adaptive evolution and demonstrates the utility of a simplified artificial cell-like system to study evolution at an unprecedented resolution. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Polymer models of interphase chromosomes

PubMed Central

Vasquez, Paula A; Bloom, Kerry

2014-01-01

Clear organizational patterns on the genome have emerged from the statistics of population studies of fixed cells. However, how these results translate into the dynamics of individual living cells remains unexplored. We use statistical mechanics models derived from polymer physics to inquire into the effects that chromosome properties and dynamics have in the temporal and spatial behavior of the genome. Overall, changes in the properties of individual chains affect the behavior of all other chains in the domain. We explore two modifications of chain behavior: single chain motion and chain-chain interactions. We show that there is not a direct relation between these effects, as increase in motion, doesn’t necessarily translate into an increase on chain interaction. PMID:25482191

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

Virus genome dynamics under different propagation pressures: reconstruction of whole genome haplotypes of West Nile viruses from NGS data.

PubMed

Kortenhoeven, Cornell; Joubert, Fourie; Bastos, Armanda D S; Abolnik, Celia

2015-02-22

Extensive focus is placed on the comparative analyses of consensus genotypes in the study of West Nile virus (WNV) emergence. Few studies account for genetic change in the underlying WNV quasispecies population variants. These variants are not discernable in the consensus genome at the time of emergence, and the maintenance of mutation-selection equilibria of population variants is greatly underestimated. The emergence of lineage 1 WNV strains has been studied extensively, but recent epidemics caused by lineage 2 WNV strains in Hungary, Austria, Greece and Italy emphasizes the increasing importance of this lineage to public health. In this study we explored the quasispecies dynamics of minority variants that contribute to cell-tropism and host determination, i.e. the ability to infect different cell types or cells from different species from Next Generation Sequencing (NGS) data of a historic lineage 2 WNV strain. Minority variants contributing to host cell membrane association persist in the viral population without contributing to the genetic change in the consensus genome. Minority variants are shown to maintain a stable mutation-selection equilibrium under positive selection, particularly in the capsid gene region. This study is the first to infer positive selection and the persistence of WNV haplotype variants that contribute to viral fitness without accompanying genetic change in the consensus genotype, documented solely from NGS sequence data. The approach used in this study streamlines the experimental design seeking viral minority variants accurately from NGS data whilst minimizing the influence of associated sequence error.

Automatic detection and analysis of cell motility in phase-contrast time-lapse images using a combination of maximally stable extremal regions and Kalman filter approaches.

PubMed

Kaakinen, M; Huttunen, S; Paavolainen, L; Marjomäki, V; Heikkilä, J; Eklund, L

2014-01-01

Phase-contrast illumination is simple and most commonly used microscopic method to observe nonstained living cells. Automatic cell segmentation and motion analysis provide tools to analyze single cell motility in large cell populations. However, the challenge is to find a sophisticated method that is sufficiently accurate to generate reliable results, robust to function under the wide range of illumination conditions encountered in phase-contrast microscopy, and also computationally light for efficient analysis of large number of cells and image frames. To develop better automatic tools for analysis of low magnification phase-contrast images in time-lapse cell migration movies, we investigated the performance of cell segmentation method that is based on the intrinsic properties of maximally stable extremal regions (MSER). MSER was found to be reliable and effective in a wide range of experimental conditions. When compared to the commonly used segmentation approaches, MSER required negligible preoptimization steps thus dramatically reducing the computation time. To analyze cell migration characteristics in time-lapse movies, the MSER-based automatic cell detection was accompanied by a Kalman filter multiobject tracker that efficiently tracked individual cells even in confluent cell populations. This allowed quantitative cell motion analysis resulting in accurate measurements of the migration magnitude and direction of individual cells, as well as characteristics of collective migration of cell groups. Our results demonstrate that MSER accompanied by temporal data association is a powerful tool for accurate and reliable analysis of the dynamic behaviour of cells in phase-contrast image sequences. These techniques tolerate varying and nonoptimal imaging conditions and due to their relatively light computational requirements they should help to resolve problems in computationally demanding and often time-consuming large-scale dynamical analysis of cultured cells. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Evolutionary dynamics of incubation periods

PubMed Central

Ottino-Loffler, Bertrand; Scott, Jacob G

2017-01-01

The incubation period for typhoid, polio, measles, leukemia and many other diseases follows a right-skewed, approximately lognormal distribution. Although this pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here, we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease. PMID:29266000

Evolutionary dynamics of incubation periods.

PubMed

Ottino-Loffler, Bertrand; Scott, Jacob G; Strogatz, Steven H

2017-12-21

The incubation period for typhoid, polio, measles, leukemia and many other diseases follows a right-skewed, approximately lognormal distribution. Although this pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here, we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease.

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

Universal Features of Electron Dynamics in Solar Cells with TiO2 Contact: From Dye Solar Cells to Perovskite Solar Cells.

PubMed

Todinova, Anna; Idígoras, Jesús; Salado, Manuel; Kazim, Samrana; Anta, Juan A

2015-10-01

The electron dynamics of solar cells with mesoporous TiO2 contact is studied by electrochemical small-perturbation techniques. The study involved dye solar cells (DSC), solid-state perovskite solar cells (SSPSC), and devices where the perovskite acts as sensitizer in a liquid-junction device. Using a transport-recombination continuity equation we found that mid-frequency time constants are proper lifetimes that determine the current-voltage curve. This is not the case for the SSPSC, where a lifetime of ∼1 μs, 1 order of magnitude longer, is required to reproduce the current-voltage curve. This mismatch is attributed to the dielectric response on the mid-frequency component. Correcting for this effect, lifetimes lie on a common exponential trend with respect to open-circuit voltage. Electron transport times share a common trend line too. This universal behavior of lifetimes and transport times suggests that the main difference between the cells is the power to populate the mesoporous TiO2 contact with electrons.

Kinetic theory of age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Greenman, Chris D.; Chou, Tom

2016-01-01

Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but are unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Stochastic theories that treat semi-Markov age-dependent processes using, e.g., the Bellman-Harris equation do not resolve a population's age structure and are unable to quantify population-size dependencies. Conversely, current theories that include size-dependent population dynamics (e.g., mathematical models that include carrying capacity such as the logistic equation) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new, fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a Bogoliubov--Born--Green--Kirkwood--Yvon-like hierarchy. Explicit solutions are derived in three limits: no birth, no death, and steady state. These are then compared with their corresponding mean-field results. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution.

Memory and obesity affect the population dynamics of asexual freshwater planarians

NASA Astrophysics Data System (ADS)

Dunkel, Jörn; Talbot, Jared; Schötz, Eva-Maria

2011-04-01

Asexual reproduction in multicellular organisms is a complex biophysical process that is not yet well understood quantitatively. Here, we report a detailed population study for the asexual freshwater planarian Schmidtea mediterranea, which can reproduce via transverse fission due to a large stem cell contingent. Our long-term observations of isolated non-interacting planarian populations reveal that the characteristic fission waiting time distributions for head and tail fragments differ significantly from each other. The stochastic fission dynamics of tail fragments exhibits non-negligible memory effects, implying that an accurate mathematical description of future data should be based on non-Markovian tree models. By comparing the effective growth of non-interacting planarian populations with those of self-interacting populations, we are able to quantify the influence of interactions between flatworms and physical conditions on the population growth. A surprising result is the non-monotonic relationship between effective population growth rate and nutrient supply: planarians exhibit a tendency to become 'obese' if the feeding frequency exceeds a critical level, resulting in a decreased reproduction activity. This suggests that these flatworms, which possess many genes homologous to those of humans, could become a new model system for studying dietary effects on reproduction and regeneration in multicellular organisms.

The technology and biology of single-cell RNA sequencing.

PubMed

Kolodziejczyk, Aleksandra A; Kim, Jong Kyoung; Svensson, Valentine; Marioni, John C; Teichmann, Sarah A

2015-05-21

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications. Copyright © 2015 Elsevier Inc. All rights reserved.

Functional heterogeneity and heritability in CHO cell populations.

PubMed

Davies, Sarah L; Lovelady, Clare S; Grainger, Rhian K; Racher, Andrew J; Young, Robert J; James, David C

2013-01-01

In this study, we address the hypothesis that it is possible to exploit genetic/functional variation in parental Chinese hamster ovary (CHO) cell populations to isolate clonal derivatives that exhibit superior, heritable attributes for biomanufacturing--new parental cell lines which are inherently more "fit for purpose." One-hundred and ninety-nine CHOK1SV clones were isolated from a donor CHOK1SV parental population by limiting dilution cloning and microplate image analysis, followed by primary analysis of variation in cell-specific proliferation rate during extended deep-well microplate suspension culture of individual clones to accelerate genetic drift in isolated cultures. A subset of 100 clones were comparatively evaluated for transient production of a recombinant monoclonal antibody (Mab) and green fluorescent protein following transfection of a plasmid vector encoding both genes. The heritability of both cell-specific proliferation rate and Mab production was further assessed using a subset of 23 clones varying in functional capability that were subjected to cell culture regimes involving both cryopreservation and extended sub-culture. These data showed that whilst differences in transient Mab production capability were not heritable per se, clones exhibiting heritable variation in specific proliferation rate, endocytotic transfectability and N-glycan processing were identified. Finally, for clonal populations most "evolved" by extended sub-culture in vitro we investigated the relationship between cellular protein biomass content, specific proliferation rate and cell surface N-glycosylation. Rapid-specific proliferation rate was inversely correlated to CHO cell size and protein content, and positively correlated to cell surface glycan content, although substantial clone-specific variation in ability to accumulate cell biomass was evident. Taken together, our data reveal the dynamic nature of the CHO cell functional genome and the potential to evolve and isolate CHO cell variants with improved functional properties in vitro. Copyright © 2012 Wiley Periodicals, Inc.

Yeast population dynamics of industrial fuel-ethanol fermentation process assessed by PCR-fingerprinting.

PubMed

da Silva-Filho, Eurípedes Alves; Brito dos Santos, Scheila Karina; Resende, Alecsandra do Monte; de Morais, José Otamar Falcão; de Morais, Marcos Antonio; Ardaillon Simões, Diogo

2005-07-01

Yeast population used in industrial production of fuel-ethanol may vary according to the plant process condition and to the environmental stresses imposed to yeast cells. Therefore, yeast strains isolated from a particular industrial process may be adapted to such conditions and should be used as starter strain instead of less adapted commercial strains. This work reports the use of PCR-fingerprinting method based on microsatellite primer (GTG)5 to characterize the yeast population dynamics along the fermentation period in six distilleries. The results show that indigenous fermenting strains present in the crude substrate can be more adapted to the industrial process than commercial strains. We also identified new strains that dominate the yeast population and were more present either in molasses or sugar cane fermenting distilleries. Those strains were proposed to be used as starters in those industrial processes. This is the first report on the use of molecular markers to discriminate Saccharomyces cerevisiae strains from fuel-ethanol producing process.

CD71(high) population represents primitive erythroblasts derived from mouse embryonic stem cells.

PubMed

Chao, Ruihua; Gong, Xueping; Wang, Libo; Wang, Pengxiang; Wang, Yuan

2015-01-01

The CD71/Ter119 combination has been widely used to reflect dynamic maturation of erythrocytes in vivo. However, because CD71 is expressed on all proliferating cells, it is unclear whether it can be utilized as an erythrocyte-specific marker during differentiation of embryonic stem cells (ESCs). In this study, we revealed that a population expressing high level of CD71 (CD71(high)) during mouse ESC differentiation represented an in vitro counterpart of yolk sac-derived primitive erythroblasts (EryPs) isolated at 8.5days post coitum. In addition, these CD71(high) cells went through "maturational globin switching" and enucleated during terminal differentiation in vitro that were similar to the yolk sac-derived EryPs in vivo. We further demonstrated that the formation of CD71(high) population was regulated differentially by key factors including Scl, HoxB4, Eaf1, and Klf1. Taken together, our study provides a technical advance that allows efficient segregation of EryPs from differentiated ESCs in vitro for further understanding molecular regulation during primitive erythropoiesis. Copyright © 2014. Published by Elsevier B.V.

Transition to organized behavior on suspensions of concentrated bacteria

NASA Astrophysics Data System (ADS)

Ganguly, Sujoy; Cisneros, Luis; Kessler, John; Goldstein, Raymond

2008-11-01

Concentrated populations of the swimming bacterium Bacillus subtilis develop a collective phase, the Zooming BioNematic, that exhibits large-scale coherence analogous to the molecular alignment of nematic liquid crystals. Bacterial suspensions were prepared in order to experimentally measure the transition to organized behavior as a function of the cell number concentration. PIV analysis was used to obtain cell velocities and define an order parameter in order to characterize the dynamics of the system.

Bacterial Biofilms as Complex Communities

NASA Astrophysics Data System (ADS)

Vlamakis, Hera

2010-03-01

Many microbial populations form surface-associated multicellular communities known as biofilms. These multicellular communities are encased in a self-produced extracellular matrix composed of polysaccharides and proteins. Division of labor is a key feature of these communities and different cells serve distinct functions. We have found that in biofilms of the bacterium Bacillus subtilis, different cell types including matrix-producing and sporulating cells coexist and localize to distinct regions within the structured community. We were interested in understanding how these different cell types arise. Using fluorescence reporters under the control of promoters that are specific for distinct cell types we were able to follow the dynamics of differentiation throughout biofilm development. We found that a series of extracellular signals leads to differentiation of distinct cell types during biofilm formation. In addition, we found that extracellular matrix functions as a differentiation signal for timely sporulation within a biofilm and mutants unable to produce matrix were delayed in sporulation. Our results indicate that within a biofilm, cell-cell signaling is directional in that one cell type produces a signal that is sensed by another distinct cell type. Furthermore, once differentiated, cells become resistant to the action of other signaling molecules making it possible to maintain distinct cell populations over prolonged periods.

Stable and dynamic microtubules coordinately shape the myosin activation zone during cytokinetic furrow formation

PubMed Central

Foe, Victoria E.; von Dassow, George

2008-01-01

The cytokinetic furrow arises from spatial and temporal regulation of cortical contractility. To test the role microtubules play in furrow specification, we studied myosin II activation in echinoderm zygotes by assessing serine19-phosphorylated regulatory light chain (pRLC) localization after precisely timed drug treatments. Cortical pRLC was globally depressed before cytokinesis, then elevated only at the equator. We implicated cell cycle biochemistry (not microtubules) in pRLC depression, and differential microtubule stability in localizing the subsequent myosin activation. With no microtubules, pRLC accumulation occurred globally instead of equatorially, and loss of just dynamic microtubules increased equatorial pRLC recruitment. Nocodazole treatment revealed a population of stable astral microtubules that formed during anaphase; among these, those aimed toward the equator grew longer, and their tips coincided with cortical pRLC accumulation. Shrinking the mitotic apparatus with colchicine revealed pRLC suppression near dynamic microtubule arrays. We conclude that opposite effects of stable versus dynamic microtubules focuses myosin activation to the cell equator during cytokinesis. PMID:18955555

Population-wide distributions of neural activity during perceptual decision-making

PubMed Central

Machens, Christian

2018-01-01

Cortical activity involves large populations of neurons, even when it is limited to functionally coherent areas. Electrophysiological recordings, on the other hand, involve comparatively small neural ensembles, even when modern-day techniques are used. Here we review results which have started to fill the gap between these two scales of inquiry, by shedding light on the statistical distributions of activity in large populations of cells. We put our main focus on data recorded in awake animals that perform simple decision-making tasks and consider statistical distributions of activity throughout cortex, across sensory, associative, and motor areas. We transversally review the complexity of these distributions, from distributions of firing rates and metrics of spike-train structure, through distributions of tuning to stimuli or actions and of choice signals, and finally the dynamical evolution of neural population activity and the distributions of (pairwise) neural interactions. This approach reveals shared patterns of statistical organization across cortex, including: (i) long-tailed distributions of activity, where quasi-silence seems to be the rule for a majority of neurons; that are barely distinguishable between spontaneous and active states; (ii) distributions of tuning parameters for sensory (and motor) variables, which show an extensive extrapolation and fragmentation of their representations in the periphery; and (iii) population-wide dynamics that reveal rotations of internal representations over time, whose traces can be found both in stimulus-driven and internally generated activity. We discuss how these insights are leading us away from the notion of discrete classes of cells, and are acting as powerful constraints on theories and models of cortical organization and population coding. PMID:23123501

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

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

Geng, Tao; Smallwood, Chuck R.; Bredeweg, Erin L.

Modern live-cell imaging approaches permit real-time visualization of biological processes, yet limitations exist for unicellular organism isolation, culturing and long-term imaging that preclude fully understanding how cells sense and respond to environmental perturbations and the link between single-cell variability and whole-population dynamics. Here we present a microfluidic platform that provides fine control over the local environment with the capacity to replace media components at any experimental time point, and provides both perfused and compartmentalized cultivation conditions depending on the valve configuration. The functionality and flexibility of the platform were validated using both bacteria and yeast having different sizes, motility andmore » growth media. The demonstrated ability to track the growth and dynamics of both motile and non-motile prokaryotic and eukaryotic organisms emphasizes the versatility of the devices, which with further scale-up should enable studies in bioenergy and environmental research.« less

Compartmental Genomics in Living Cells Revealed by Single-Cell Nanobiopsy

PubMed Central

Actis, Paolo; Maalouf, Michelle; Kim, Hyunsung John; Lohith, Akshar; Vilozny, Boaz; Seger, R. Adam; Pourmand, Nader

2014-01-01

The ability to study the molecular biology of living single cells in heterogeneous cell populations is essential for next generation analysis of cellular circuitry and function. Here, we developed a single-cell nanobiopsy platform based on scanning ion conductance microscopy (SICM) for continuous sampling of intracellular content from individual cells. The nanobiopsy platform uses electrowetting within a nanopipette to extract cellular material from living cells with minimal disruption of the cellular milieu. We demonstrate the subcellular resolution of the nanobiopsy platform by isolating small subpopulations of mitochondria from single living cells, and quantify mutant mitochondrial genomes in those single cells with high throughput sequencing technology. These findings may provide the foundation for dynamic subcellular genomic analysis. PMID:24279711

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.

Quantifying the contribution of chromatin dynamics to stochastic gene expression reveals long, locus-dependent periods between transcriptional bursts.

PubMed

Viñuelas, José; Kaneko, Gaël; Coulon, Antoine; Vallin, Elodie; Morin, Valérie; Mejia-Pous, Camila; Kupiec, Jean-Jacques; Beslon, Guillaume; Gandrillon, Olivier

2013-02-25

A number of studies have established that stochasticity in gene expression may play an important role in many biological phenomena. This therefore calls for further investigations to identify the molecular mechanisms at stake, in order to understand and manipulate cell-to-cell variability. In this work, we explored the role played by chromatin dynamics in the regulation of stochastic gene expression in higher eukaryotic cells. For this purpose, we generated isogenic chicken-cell populations expressing a fluorescent reporter integrated in one copy per clone. Although the clones differed only in the genetic locus at which the reporter was inserted, they showed markedly different fluorescence distributions, revealing different levels of stochastic gene expression. Use of chromatin-modifying agents showed that direct manipulation of chromatin dynamics had a marked effect on the extent of stochastic gene expression. To better understand the molecular mechanism involved in these phenomena, we fitted these data to a two-state model describing the opening/closing process of the chromatin. We found that the differences between clones seemed to be due mainly to the duration of the closed state, and that the agents we used mainly seem to act on the opening probability. In this study, we report biological experiments combined with computational modeling, highlighting the importance of chromatin dynamics in stochastic gene expression. This work sheds a new light on the mechanisms of gene expression in higher eukaryotic cells, and argues in favor of relatively slow dynamics with long (hours to days) periods of quiet state.

Poisson-event-based analysis of cell proliferation.

PubMed

Summers, Huw D; Wills, John W; Brown, M Rowan; Rees, Paul

2015-05-01

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture. © 2015 International Society for Advancement of Cytometry.

Decoherence in yeast cell populations and its implications for genome-wide expression noise.

PubMed

Briones, M R S; Bosco, F

2009-01-20

Gene expression "noise" is commonly defined as the stochastic variation of gene expression levels in different cells of the same population under identical growth conditions. Here, we tested whether this "noise" is amplified with time, as a consequence of decoherence in global gene expression profiles (genome-wide microarrays) of synchronized cells. The stochastic component of transcription causes fluctuations that tend to be amplified as time progresses, leading to a decay of correlations of expression profiles, in perfect analogy with elementary relaxation processes. Measuring decoherence, defined here as a decay in the auto-correlation function of yeast genome-wide expression profiles, we found a slowdown in the decay of correlations, opposite to what would be expected if, as in mixing systems, correlations decay exponentially as the equilibrium state is reached. Our results indicate that the populational variation in gene expression (noise) is a consequence of temporal decoherence, in which the slow decay of correlations is a signature of strong interdependence of the transcription dynamics of different genes.

Evolutionary Games with Randomly Changing Payoff Matrices

NASA Astrophysics Data System (ADS)

Yakushkina, Tatiana; Saakian, David B.; Bratus, Alexander; Hu, Chin-Kun

2015-06-01

Evolutionary games are used in various fields stretching from economics to biology. In most of these games a constant payoff matrix is assumed, although some works also consider dynamic payoff matrices. In this article we assume a possibility of switching the system between two regimes with different sets of payoff matrices. Potentially such a model can qualitatively describe the development of bacterial or cancer cells with a mutator gene present. A finite population evolutionary game is studied. The model describes the simplest version of annealed disorder in the payoff matrix and is exactly solvable at the large population limit. We analyze the dynamics of the model, and derive the equations for both the maximum and the variance of the distribution using the Hamilton-Jacobi equation formalism.

Cancer Evolution: Mathematical Models and Computational Inference

PubMed Central

Beerenwinkel, Niko; Schwarz, Roland F.; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. PMID:25293804

Single cell RNA Seq reveals dynamic paracrine control of cellular variation

PubMed Central

Shalek, Alex K.; Satija, Rahul; Shuga, Joe; Trombetta, John J.; Gennert, Dave; Lu, Diana; Chen, Peilin; Gertner, Rona S.; Gaublomme, Jellert T.; Yosef, Nir; Schwartz, Schraga; Fowler, Brian; Weaver, Suzanne; Wang, Jing; Wang, Xiaohui; Ding, Ruihua; Raychowdhury, Raktima; Friedman, Nir; Hacohen, Nir; Park, Hongkun; May, Andrew P.; Regev, Aviv

2014-01-01

High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis, and function of gene expression variation between seemingly identical cells. Here, we sequence single-cell RNA-Seq libraries prepared from over 1,700 primary mouse bone marrow derived dendritic cells (DCs) spanning several experimental conditions. We find substantial variation between identically stimulated DCs, in both the fraction of cells detectably expressing a given mRNA and the transcript’s level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a “core” module of antiviral genes is expressed very early by a few “precocious” cells, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analyzing DCs from knockout mice, and modulating secretion and extracellular signaling, we show that this response is coordinated via interferon-mediated paracrine signaling. Surprisingly, preventing cell-to-cell communication also substantially reduces variability in the expression of an early-induced “peaked” inflammatory module, suggesting that paracrine signaling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations use to establish complex dynamic responses. PMID:24919153

PhOTO Zebrafish: A Transgenic Resource for In Vivo Lineage Tracing during Development and Regeneration

PubMed Central

Dempsey, William P.; Fraser, Scott E.; Pantazis, Periklis

2012-01-01

Background Elucidating the complex cell dynamics (divisions, movement, morphological changes, etc.) underlying embryonic development and adult tissue regeneration requires an efficient means to track cells with high fidelity in space and time. To satisfy this criterion, we developed a transgenic zebrafish line, called PhOTO, that allows photoconvertible optical tracking of nuclear and membrane dynamics in vivo. Methodology PhOTO zebrafish ubiquitously express targeted blue fluorescent protein (FP) Cerulean and photoconvertible FP Dendra2 fusions, allowing for instantaneous, precise targeting and tracking of any number of cells using Dendra2 photoconversion while simultaneously monitoring global cell behavior and morphology. Expression persists through adulthood, making the PhOTO zebrafish an excellent tool for studying tissue regeneration: after tail fin amputation and photoconversion of a ∼100µm stripe along the cut area, marked differences seen in how cells contribute to the new tissue give detailed insight into the dynamic process of regeneration. Photoconverted cells that contributed to the regenerate were separated into three distinct populations corresponding to the extent of cell division 7 days after amputation, and a subset of cells that divided the least were organized into an evenly spaced, linear orientation along the length of the newly regenerating fin. Conclusions/Significance PhOTO zebrafish have wide applicability for lineage tracing at the systems-level in the early embryo as well as in the adult, making them ideal candidate tools for future research in development, traumatic injury and regeneration, cancer progression, and stem cell behavior. PMID:22431986

The availability of filament ends modulates actin stochastic dynamics in live plant cells

PubMed Central

Li, Jiejie; Staiger, Benjamin H.; Henty-Ridilla, Jessica L.; Abu-Abied, Mohamad; Sadot, Einat; Blanchoin, Laurent; Staiger, Christopher J.

2014-01-01

A network of individual filaments that undergoes incessant remodeling through a process known as stochastic dynamics comprises the cortical actin cytoskeleton in plant epidermal cells. From images at high spatial and temporal resolution, it has been inferred that the regulation of filament barbed ends plays a central role in choreographing actin organization and turnover. How this occurs at a molecular level, whether different populations of ends exist in the array, and how individual filament behavior correlates with the overall architecture of the array are unknown. Here we develop an experimental system to modulate the levels of heterodimeric capping protein (CP) and examine the consequences for actin dynamics, architecture, and cell expansion. Significantly, we find that all phenotypes are the opposite for CP-overexpression (OX) cells compared with a previously characterized cp-knockdown line. Specifically, CP OX lines have fewer filament–filament annealing events, as well as reduced filament lengths and lifetimes. Further, cp-knockdown and OX lines demonstrate the existence of a subpopulation of filament ends sensitive to CP concentration. Finally, CP levels correlate with the biological process of axial cell expansion; for example, epidermal cells from hypocotyls with reduced CP are longer than wild-type cells, whereas CP OX lines have shorter cells. On the basis of these and other genetic studies in this model system, we hypothesize that filament length and lifetime positively correlate with the extent of axial cell expansion in dark-grown hypocotyls. PMID:24523291

GENOME ENABLED ECOLOGY OF PSEUDO-NITZSCHIA INFECTING VIRUSES AND THEIR IMPACT ON PSEUDO-NITZSCHIA COMMUNITIES

EPA Science Inventory

With short infection cycles and large burst sizes (viruses per cell), the infection dynamics of diatom viruses appear to be optimized for rapidly growing diatom populations. On the timescale of bloom events, total Pseudo-nitzschia virus abundance should increase rapidly ove...

Dynamics of the antibody-T.cruzi competition during Chagas infection: Prognostic relevance of intracellular replication

NASA Astrophysics Data System (ADS)

Sibona, G. J.; Condat, C. A.; Isasi, S. Cossy

2005-02-01

A recently proposed model for the competitive parasite-antibody interactions in Chagas disease is extended by separately describing the parasitic intracellular and extracellular phases. The model solutions faithfully reproduce available population data and yield predictions for parasite-induced cardiac cell damage.

High-throughput analysis of spatio-temporal dynamics in Dictyostelium

PubMed Central

Sawai, Satoshi; Guan, Xiao-Juan; Kuspa, Adam; Cox, Edward C

2007-01-01

We demonstrate a time-lapse video approach that allows rapid examination of the spatio-temporal dynamics of Dictyostelium cell populations. Quantitative information was gathered by sampling life histories of more than 2,000 mutant clones from a large mutagenesis collection. Approximately 4% of the clonal lines showed a mutant phenotype at one stage. Many of these could be ordered by clustering into functional groups. The dataset allows one to search and retrieve movies on a gene-by-gene and phenotype-by-phenotype basis. PMID:17659086

Fitness-Balanced Escape Determines Resolution of Dynamic Founder Virus Escape Processes in HIV-1 Infection

PubMed Central

Sunshine, Justine E.; Larsen, Brendan B.; Maust, Brandon; Casey, Ellie; Deng, Wenje; Chen, Lennie; Westfall, Dylan H.; Kim, Moon; Zhao, Hong; Ghorai, Suvankar; Lanxon-Cookson, Erinn; Rolland, Morgane; Collier, Ann C.; Maenza, Janine; Mullins, James I.

2015-01-01

ABSTRACT To understand the interplay between host cytotoxic T-lymphocyte (CTL) responses and the mechanisms by which HIV-1 evades them, we studied viral evolutionary patterns associated with host CTL responses in six linked transmission pairs. HIV-1 sequences corresponding to full-length p17 and p24 gag were generated by 454 pyrosequencing for all pairs near the time of transmission, and seroconverting partners were followed for a median of 847 days postinfection. T-cell responses were screened by gamma interferon/interleukin-2 (IFN-γ/IL-2) FluoroSpot using autologous peptide sets reflecting any Gag variant present in at least 5% of sequence reads in the individual's viral population. While we found little evidence for the occurrence of CTL reversions, CTL escape processes were found to be highly dynamic, with multiple epitope variants emerging simultaneously. We found a correlation between epitope entropy and the number of epitope variants per response (r = 0.43; P = 0.05). In cases in which multiple escape mutations developed within a targeted epitope, a variant with no fitness cost became fixed in the viral population. When multiple mutations within an epitope achieved fitness-balanced escape, these escape mutants were each maintained in the viral population. Additional mutations found to confer escape but undetected in viral populations incurred high fitness costs, suggesting that functional constraints limit the available sites tolerable to escape mutations. These results further our understanding of the impact of CTL escape and reversion from the founder virus in HIV infection and contribute to the identification of immunogenic Gag regions most vulnerable to a targeted T-cell attack. IMPORTANCE Rapid diversification of the viral population is a hallmark of HIV-1 infection, and understanding the selective forces driving the emergence of viral variants can provide critical insight into the interplay between host immune responses and viral evolution. We used deep sequencing to comprehensively follow viral evolution over time in six linked HIV transmission pairs. We then mapped T-cell responses to explore if mutations arose due to adaption to the host and found that escape processes were often highly dynamic, with multiple mutations arising within targeted epitopes. When we explored the impact of these mutations on replicative capacity, we found that dynamic escape processes only resolve with the selection of mutations that conferred escape with no fitness cost to the virus. These results provide further understanding of the complicated viral-host interactions that occur during early HIV-1 infection and may help inform the design of future vaccine immunogens. PMID:26223634

Keeping abreast of the mammary epithelial hierarchy and breast tumorigenesis.

PubMed

Visvader, Jane E

2009-11-15

The epithelium of the mammary gland exists in a highly dynamic state, undergoing dramatic morphogenetic changes during puberty, pregnancy, lactation, and regression. The recent identification of stem and progenitor populations in mouse and human mammary tissue has provided evidence that the mammary epithelium is organized in a hierarchical manner. Characterization of these normal epithelial subtypes is an important step toward understanding which cells are predisposed to oncogenesis. This review summarizes progress in the field toward defining constituent cells and key molecular regulators of the mammary epithelial hierarchy. Potential relationships between normal epithelial populations and breast tumor subtypes are discussed, with implications for understanding the cellular etiology underpinning breast tumor heterogeneity.

The dynamics of neuronal redundancy in decision making

NASA Astrophysics Data System (ADS)

Daniels, Bryan; Flack, Jessica; Krakauer, David

We propose two temporal phases of collective computation in a visual motion direction discrimination task by analyzing recordings from 169 neural channels in the prefrontal cortex of macaque monkeys. Phase I is a distributed phase in which uncertainty is substantially reduced by pooling information from many cells. Phase II is a redundant phase in which numerous single cells contain all the information present at the population level in Phase I. A dynamic distributed model connects low redundancy to a slow timescale of information aggregation, and provides a common explanation for both behaviors that differs only in the degree of recurrent excitation. We attribute the slow timescale of information accumulation to critical slowing down near the transition to a memory-carrying collective state. We suggest that this dynamic of slow distributed accumulation followed by fast collective propagation is a generic feature of robust collective computing systems related to consensus formation.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

NASA Astrophysics Data System (ADS)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy.

PubMed

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-09

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Critical telomerase activity for uncontrolled cell growth

NASA Astrophysics Data System (ADS)

Wesch, Neil L.; Burlock, Laura J.; Gooding, Robert J.

2016-08-01

The lengths of the telomere regions of chromosomes in a population of cells are modelled using a chemical master equation formalism, from which the evolution of the average number of cells of each telomere length is extracted. In particular, the role of the telomere-elongating enzyme telomerase on these dynamics is investigated. We show that for biologically relevant rates of cell birth and death, one finds a critical rate, R crit, of telomerase activity such that the total number of cells diverges. Further, R crit is similar in magnitude to the rates of mitosis and cell death. The possible relationship of this result to replicative immortality and its associated hallmark of cancer is discussed.

NF-κB dynamics show digital activation and analog information processing in cells

NASA Astrophysics Data System (ADS)

Tay, Savas; Hughey, Jake; Lee, Timothy; Lipniacki, Tomasz; Covert, Markus; Quake, Stephen

2010-03-01

Cells operate in ever changing environments using extraordinary communication capabilities. Cell-to-cell communication is mediated by signaling molecules that form spatiotemporal concentration gradients, which requires cells to respond to a wide range of signal intensities. We used high-throughput microfluidic cell culture, quantitative gene expression analysis and mathematical modeling to investigate how single mammalian cells respond to different concentrations of the signaling molecule TNF-α via the transcription factor NF-κB. We measured NF-κB activity in thousands of live cells under TNF-α doses covering four orders of magnitude. In contrast to population studies, the activation is a stochastic, switch-like process at the single cell level with fewer cells responding at lower doses. The activated cells respond fully and express early genes independent of the TNF-α concentration, while only high dose stimulation results in the expression of late genes. Cells also encode a set of analog parameters such as the NF-κB peak intensity, response time and number of oscillations to modulate the outcome. We developed a stochastic model that reproduces both the digital and analog dynamics as well as the gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-α induced NF-κB signaling in various types of cells.

Targeting stem cell niches and trafficking for cardiovascular therapy

PubMed Central

Kränkel, Nicolle; Spinetti, Gaia; Amadesi, Silvia; Madeddu, Paolo

2010-01-01

Regenerative cardiovascular medicine is the frontline of 21st-century health care. Cell therapy trials using bone marrow progenitor cells documented that the approach is feasible, safe and potentially beneficial in patients with ischemic disease. However, cardiovascular prevention and rehabilitation strategies should aim to conserve the pristine healing capacity of a healthy organism as well as reactivate it under disease conditions. This requires an increased understanding of stem cell microenvironment and trafficking mechanisms. Engagement and disengagement of stem cells of the osteoblastic niche is a dynamic process, finely tuned to allow low amounts of cells move out of the bone marrow and into the circulation on a regular basis. The balance is altered under stress situations, like tissue injury or ischemia, leading to remarkably increased cell egression. Individual populations of circulating progenitor cells could give rise to mature tissue cells (e.g. endothelial cells or cardiomyocytes), while the majority may differentiate to leukocytes, affecting the environment of homing sites in a paracrine way, e.g. promoting endothelial survival, proliferation and function, as well as attenuating or enhancing inflammation. This review focuses on the dynamics of the stem cell niche in healthy and disease conditions and on therapeutic means to direct stem cell/progenitor cell mobilization and recruitment into improved tissue repair. PMID:20965213

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.

Kinetics of T-cell receptor-dependent antigen recognition determined in vivo by multi-spectral normalized epifluorescence laser scanning

NASA Astrophysics Data System (ADS)

Favicchio, Rosy; Zacharakis, Giannis; Oikonomaki, Katerina; Zacharopoulos, Athanasios; Mamalaki, Clio; Ripoll, Jorge

2012-07-01

Detection of multiple fluorophores in conditions of low signal represents a limiting factor for the application of in vivo optical imaging techniques in immunology where fluorescent labels report for different functional characteristics. A noninvasive in vivo Multi-Spectral Normalized Epifluorescence Laser scanning (M-SNELS) method was developed for the simultaneous and quantitative detection of multiple fluorophores in low signal to noise ratios and used to follow T-cell activation and clonal expansion. Colocalized DsRed- and GFP-labeled T cells were followed in tandem during the mounting of an immune response. Spectral unmixing was used to distinguish the overlapping fluorescent emissions representative of the two distinct cell populations and longitudinal data reported the discrete pattern of antigen-driven proliferation. Retrieved values were validated both in vitro and in vivo with flow cytometry and significant correlation between all methodologies was achieved. Noninvasive M-SNELS successfully quantified two colocalized fluorescent populations and provides a valid alternative imaging approach to traditional invasive methods for detecting T cell dynamics.

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.

Novel Quantitative Autophagy Analysis by Organelle Flow Cytometry after Cell Sonication

PubMed Central

Degtyarev, Michael; Reichelt, Mike; Lin, Kui

2014-01-01

Autophagy is a dynamic process of bulk degradation of cellular proteins and organelles in lysosomes. Current methods of autophagy measurement include microscopy-based counting of autophagic vacuoles (AVs) in cells. We have developed a novel method to quantitatively analyze individual AVs using flow cytometry. This method, OFACS (organelle flow after cell sonication), takes advantage of efficient cell disruption with a brief sonication, generating cell homogenates with fluorescently labeled AVs that retain their integrity as confirmed with light and electron microscopy analysis. These AVs could be detected directly in the sonicated cell homogenates on a flow cytometer as a distinct population of expected organelle size on a cytometry plot. Treatment of cells with inhibitors of autophagic flux, such as chloroquine or lysosomal protease inhibitors, increased the number of particles in this population under autophagy inducing conditions, while inhibition of autophagy induction with 3-methyladenine or knockdown of ATG proteins prevented this accumulation. This assay can be easily performed in a high-throughput format and opens up previously unexplored avenues for autophagy analysis. PMID:24489953

Dynamic interactions between dermal macrophages and Staphylococcus aureus.

PubMed

Feuerstein, Reinhild; Kolter, Julia; Henneke, Philipp

2017-01-01

The dermis, a major reservoir of immune cells in immediate vicinity to the colonizing skin microflora, serves as an important site of host-pathogen interactions. Macrophages (Mϕ) are the most frequent resident immune cell type in the dermis. They protect the host from invasive infections by highly adapted bacteria, such as staphylococci via pattern recognition of bacterial effectors, phagocytosis, and recruitment of other myeloid cells from the blood. Already under homeostatic conditions, the dermal Mϕ population receives a dynamic input of monocytes invading from the bloodstream. This quantitative renewal is promoted further at the beginning of life, when prenatally seeded cells are rapidly replaced and in healing phases after injuries or infections. Here, we discuss the potential implications of the dynamic dermal Mϕ biology on the establishment and maintenance of immunity against Staphylococcus aureus, which can either be a harmless colonizer or an invasive pathogen. The understanding of the heterogeneity of the "mature" dermal Mϕ compartment driven both by the influx of differentiating monocytes and by a bone marrow-independent Mϕ persistence and expansion may help to explain failing immunity and immunopathology originating from the skin, the important interface between host and environment. © Society for Leukocyte Biology.

Detecting cells in time varying intensity images in confocal microscopy for gene expression studies in living cells

NASA Astrophysics Data System (ADS)

Mitra, Debasis; Boutchko, Rostyslav; Ray, Judhajeet; Nilsen-Hamilton, Marit

2015-03-01

In this work we present a time-lapsed confocal microscopy image analysis technique for an automated gene expression study of multiple single living cells. Fluorescence Resonance Energy Transfer (FRET) is a technology by which molecule-to-molecule interactions are visualized. We analyzed a dynamic series of ~102 images obtained using confocal microscopy of fluorescence in yeast cells containing RNA reporters that give a FRET signal when the gene promoter is activated. For each time frame, separate images are available for three spectral channels and the integrated intensity snapshot of the system. A large number of time-lapsed frames must be analyzed to identify each cell individually across time and space, as it is moving in and out of the focal plane of the microscope. This makes it a difficult image processing problem. We have proposed an algorithm here, based on scale-space technique, which solves the problem satisfactorily. The algorithm has multiple directions for even further improvement. The ability to rapidly measure changes in gene expression simultaneously in many cells in a population will open the opportunity for real-time studies of the heterogeneity of genetic response in a living cell population and the interactions between cells that occur in a mixed population, such as the ones found in the organs and tissues of multicellular organisms.

Toward single-cell analysis by plume collimation in laser ablation electrospray ionization mass spectrometry.

PubMed

Stolee, Jessica A; Vertes, Akos

2013-04-02

Ambient ionization methods for mass spectrometry have enabled the in situ and in vivo analysis of biological tissues and cells. When an etched optical fiber is used to deliver laser energy to a sample in laser ablation electrospray ionization (LAESI) mass spectrometry, the analysis of large single cells becomes possible. However, because in this arrangement the ablation plume expands in three dimensions, only a small portion of it is ionized by the electrospray. Here we show that sample ablation within a capillary helps to confine the radial expansion of the plume. Plume collimation, due to the altered expansion dynamics, leads to greater interaction with the electrospray plume resulting in increased ionization efficiency, reduced limit of detection (by a factor of ~13, reaching 600 amol for verapamil), and extended dynamic range (6 orders of magnitude) compared to conventional LAESI. This enhanced sensitivity enables the analysis of a range of metabolites from small cell populations and single cells in the ambient environment. This technique has the potential to be integrated with flow cytometry for high-throughput metabolite analysis of sorted cells.

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.

Population dynamics of Vibrio fischeri during infection of Euprymna scolopes.

PubMed

McCann, Jessica; Stabb, Eric V; Millikan, Deborah S; Ruby, Edward G

2003-10-01

The luminous bacterium Vibrio fischeri colonizes a specialized light-emitting organ within its squid host, Euprymna scolopes. Newly hatched juvenile squid must acquire their symbiont from ambient seawater, where the bacteria are present at low concentrations. To understand the population dynamics of V. fischeri during colonization more fully, we used mini-Tn7 transposons to mark bacteria with antibiotic resistance so that the growth of their progeny could be monitored. When grown in culture, there was no detectable metabolic burden on V. fischeri cells carrying the transposon, which inserts in single copy in a specific intergenic region of the V. fischeri genome. Strains marked with mini-Tn7 also appeared to be equivalent to the wild type in their ability to infect and multiply within the host during coinoculation experiments. Studies of the early stages of colonization suggested that only a few bacteria became associated with symbiotic tissue when animals were exposed for a discrete period (3 h) to an inoculum of V. fischeri cells equivalent to natural population levels; nevertheless, all these hosts became infected. When three differentially marked strains of V. fischeri were coincubated with juvenile squid, the number of strains recovered from an individual symbiotic organ was directly dependent on the size of the inoculum. Further, these results indicated that, when exposed to low numbers of V. fischeri, the host may become colonized by only one or a few bacterial cells, suggesting that symbiotic infection is highly efficient.

Oxygen Consumption Rates of Bacteria under Nutrient-Limited Conditions

PubMed Central

Riedel, Timothy E.; Nealson, Kenneth H.; Finkel, Steven E.

2013-01-01

Many environments on Earth experience nutrient limitation and as a result have nongrowing or very slowly growing bacterial populations. To better understand bacterial respiration under environmentally relevant conditions, the effect of nutrient limitation on respiration rates of heterotrophic bacteria was measured. The oxygen consumption and population density of batch cultures of Escherichia coli K-12, Shewanella oneidensis MR-1, and Marinobacter aquaeolei VT8 were tracked for up to 200 days. The oxygen consumption per CFU (QO2) declined by more than 2 orders of magnitude for all three strains as they transitioned from nutrient-abundant log-phase growth to the nutrient-limited early stationary phase. The large reduction in QO2 from growth to stationary phase suggests that nutrient availability is an important factor in considering environmental respiration rates. Following the death phase, during the long-term stationary phase (LTSP), QO2 values of the surviving population increased with time and more cells were respiring than formed colonies. Within the respiring population, a subpopulation of highly respiring cells increased in abundance with time. Apparently, as cells enter LTSP, there is a viable but not culturable population whose bulk community and per cell respiration rates are dynamic. This result has a bearing on how minimal energy requirements are met, especially in nutrient-limited environments. The minimal QO2 rates support the extension of Kleiber's law to the mass of a bacterium (100-fg range). PMID:23770901

Probing the stochastic property of endoreduplication in cell size determination of Arabidopsis thaliana leaf epidermal tissue

PubMed Central

2017-01-01

Cell size distribution is highly reproducible, whereas the size of individual cells often varies greatly within a tissue. This is obvious in a population of Arabidopsis thaliana leaf epidermal cells, which ranged from 1,000 to 10,000 μm2 in size. Endoreduplication is a specialized cell cycle in which nuclear genome size (ploidy) is doubled in the absence of cell division. Although epidermal cells require endoreduplication to enhance cellular expansion, the issue of whether this mechanism is sufficient for explaining cell size distribution remains unclear due to a lack of quantitative understanding linking the occurrence of endoreduplication with cell size diversity. Here, we addressed this question by quantitatively summarizing ploidy profile and cell size distribution using a simple theoretical framework. We first found that endoreduplication dynamics is a Poisson process through cellular maturation. This finding allowed us to construct a mathematical model to predict the time evolution of a ploidy profile with a single rate constant for endoreduplication occurrence in a given time. We reproduced experimentally measured ploidy profile in both wild-type leaf tissue and endoreduplication-related mutants with this analytical solution, further demonstrating the probabilistic property of endoreduplication. We next extended the mathematical model by incorporating the element that cell size is determined according to ploidy level to examine cell size distribution. This analysis revealed that cell size is exponentially enlarged 1.5 times every endoreduplication round. Because this theoretical simulation successfully recapitulated experimentally observed cell size distributions, we concluded that Poissonian endoreduplication dynamics and exponential size-boosting are the sources of the broad cell size distribution in epidermal tissue. More generally, this study contributes to a quantitative understanding whereby stochastic dynamics generate steady-state biological heterogeneity. PMID:28926847

Shape matters: Lifecycle of cooperative patches promotes cooperation in bulky populations

PubMed Central

Misevic, Dusan; Frénoy, Antoine; Lindner, Ariel B; Taddei, François

2015-01-01

Natural cooperative systems take many forms, ranging from one-dimensional cyanobacteria arrays to fractal-like biofilms. We use in silico experimental systems to study a previously overlooked factor in the evolution of cooperation, physical shape of the population. We compare the emergence and maintenance of cooperation in populations of digital organisms that inhabit bulky (100 × 100 cells) or slender (4 × 2500) toroidal grids. Although more isolated subpopulations of secretors in a slender population could be expected to favor cooperation, we find the opposite: secretion evolves to higher levels in bulky populations. We identify the mechanistic explanation for the shape effect by analyzing the lifecycle and dynamics of cooperator patches, from their emergence and growth, to invasion by noncooperators and extinction. Because they are constrained by the population shape, the cooperator patches expand less in slender than in bulky populations, leading to fewer cooperators, less public good secretion, and generally lower cooperation. The patch dynamics and mechanisms of shape effect are robust across several digital cooperation systems and independent of the underlying basis for cooperation (public good secretion or a cooperation game). Our results urge for a greater consideration of population shape in the study of the evolution of cooperation across experimental and modeling systems. PMID:25639379

Morphology and dynamics of tumor cell colonies propagating in epidermal growth factor supplemented media

NASA Astrophysics Data System (ADS)

Muzzio, N. E.; Carballido, M.; Pasquale, M. A.; González, P. H.; Azzaroni, O.; Arvia, A. J.

2018-07-01

The epidermal growth factor (EGF) plays a key role in physiological and pathological processes. This work reports on the influence of EGF concentration (c EGF) on the modulation of individual cell phenotype and cell colony kinetics with the aim of perturbing the colony front roughness fluctuations. For this purpose, HeLa cell colonies that remain confluent along the whole expansion process with initial quasi-radial geometry and different initial cell populations, as well as colonies with initial quasi-linear geometry and large cell population, are employed. Cell size and morphology as well as its adhesive characteristics depend on c EGF. Quasi-radial colonies (QRC) expansion kinetics in EGF-containing medium exhibits a complex behavior. Namely, at the first stages of growth, the average QRC radius evolution can be described by a t 1/2 diffusion term coupled with exponential growth kinetics up to a critical time, and afterwards a growth regime approaching constant velocity. The extension of each regime depends on c EGF and colony history. In the presence of EGF, the initial expansion of quasi-linear colonies (QLCs) also exhibits morphological changes at both the cell and the colony levels. In these cases, the cell density at the colony border region becomes smaller than in the absence of EGF and consequently, the extension of the effective rim where cell duplication and motility contribute to the colony expansion increases. QLC front displacement velocity increases with c EGF up to a maximum value in the 2–10 ng ml‑1 range. Individual cell velocity is increased by EGF, and an enhancement in both the persistence and the ballistic characteristics of cell trajectories can be distinguished. For an intermediate c EGF, collective cell displacements contribute to the roughening of the colony contours. This global dynamics becomes compatible with the standard Kardar–Parisi–Zhang growth model, although a faster colony roughness saturation in EGF-containing medium than in the control medium is observed.

Cell-Division Behavior in a Heterogeneous Swarm Environment.

PubMed

Erskine, Adam; Herrmann, J Michael

2015-01-01

We present a system of virtual particles that interact using simple kinetic rules. It is known that heterogeneous mixtures of particles can produce particularly interesting behaviors. Here we present a two-species three-dimensional swarm in which a behavior emerges that resembles cell division. We show that the dividing behavior exists across a narrow but finite band of parameters and for a wide range of population sizes. When executed in a two-dimensional environment the swarm's characteristics and dynamism manifest differently. In further experiments we show that repeated divisions can occur if the system is extended by a biased equilibrium process to control the split of populations. We propose that this repeated division behavior provides a simple model for cell-division mechanisms and is of interest for the formation of morphological structure and to swarm robotics.

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 New Model for the Estimation of Cell Proliferation Dynamics Using CFSE Data

DTIC Science & Technology

2011-08-20

cells, and hence into the resulting division and death rates . Alternatively, we propose that there is information to be learned not only from...meaningful estimation of population proliferation and death rates in a manner which is unbiased and mechanistically sound. Significantly, this new model is...change in permitting the dependence of the proliferation and death rates (α and β) and the label loss rate (v) on both time t and measured FI x. This

Basal Forebrain Gating by Somatostatin Neurons Drives Prefrontal Cortical Activity.

PubMed

Espinosa, Nelson; Alonso, Alejandra; Morales, Cristian; Espinosa, Pedro; Chávez, Andrés E; Fuentealba, Pablo

2017-11-17

The basal forebrain provides modulatory input to the cortex regulating brain states and cognitive processing. Somatostatin-expressing neurons constitute a heterogeneous GABAergic population known to functionally inhibit basal forebrain cortically projecting cells thus favoring sleep and cortical synchronization. However, it remains unclear if somatostatin cells can regulate population activity patterns in the basal forebrain and modulate cortical dynamics. Here, we demonstrate that somatostatin neurons regulate the corticopetal synaptic output of the basal forebrain impinging on cortical activity and behavior. Optogenetic inactivation of somatostatin neurons in vivo rapidly modified neural activity in the basal forebrain, with the consequent enhancement and desynchronization of activity in the prefrontal cortex, reflected in both neuronal spiking and network oscillations. Cortical activation was partially dependent on cholinergic transmission, suppressing slow waves and potentiating gamma oscillations. In addition, recruitment dynamics was cell type-specific, with interneurons showing similar temporal profiles, but stronger responses than pyramidal cells. Finally, optogenetic stimulation of quiescent animals during resting periods prompted locomotor activity, suggesting generalized cortical activation and increased arousal. Altogether, we provide physiological and behavioral evidence indicating that somatostatin neurons are pivotal in gating the synaptic output of the basal forebrain, thus indirectly controlling cortical operations via both cholinergic and non-cholinergic mechanisms. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Charge carrier dynamics and surface plasmon interaction in gold nanorod-blended organic solar cell

NASA Astrophysics Data System (ADS)

Rana, Aniket; Gupta, Neeraj; Lochan, Abhiram; Sharma, G. D.; Chand, Suresh; Kumar, Mahesh; Singh, Rajiv K.

2016-08-01

The inclusion of plasmonic nanoparticles into organic solar cell enhances the light harvesting properties that lead to higher power conversion efficiency without altering the device configuration. This work defines the consequences of the nanoparticle overloading amount and energy transfer process between gold nanorod and polymer (active matrix) in organic solar cells. We have studied the hole population decay dynamics coupled with gold nanorods loading amount which provides better understanding about device performance limiting factors. The exciton and plasmon together act as an interacting dipole; however, the energy exchange between these two has been elucidated via plasmon resonance energy transfer (PRET) mechanism. Further, the charge species have been identified specifically with respect to their energy levels appearing in ultrafast time domain. The specific interaction of these charge species with respective surface plasmon resonance mode, i.e., exciton to transverse mode of oscillation and polaron pair to longitudinal mode of oscillations, has been explained. Thus, our analysis reveals that PRET enhances the carrier population density in polymer via non-radiative process beyond the concurrence of a particular plasmon resonance oscillation mode and polymer absorption range. These findings give new insight and reveal specifically the factors that enhance and control the performance of gold nanorods blended organic solar cells. This work would lead in the emergence of future plasmon based efficient organic electronic devices.

Mathematical modelling of the antibiotic-induced morphological transition of Pseudomonas aeruginosa

PubMed Central

Keen, Emma; Smith, David J.

2018-01-01

Here we formulate a mechanistic mathematical model to describe the growth dynamics of P. aeruginosa in the presence of the β-lactam antibiotic meropenem. The model is mechanistic in the sense that carrying capacity is taken into account through the dynamics of nutrient availability rather than via logistic growth. In accordance with our experimental results we incorporate a sub-population of cells, differing in morphology from the normal bacillary shape of P. aeruginosa bacteria, which we assume have immunity from direct antibiotic action. By fitting this model to experimental data we obtain parameter values that give insight into the growth of a bacterial population that includes different cell morphologies. The analysis of two parameters sets, that produce different long term behaviour, allows us to manipulate the system theoretically in order to explore the advantages of a shape transition that may potentially be a mechanism that allows P. aeruginosa to withstand antibiotic effects. Our results suggest that inhibition of this shape transition may be detrimental to bacterial growth and thus suggest that the transition may be a defensive mechanism implemented by bacterial machinery. In addition to this we provide strong theoretical evidence for the potential therapeutic strategy of using antimicrobial peptides (AMPs) in combination with meropenem. This proposed combination therapy exploits the shape transition as AMPs induce cell lysis by forming pores in the cytoplasmic membrane, which becomes exposed in the spherical cells. PMID:29481562

Charge carrier dynamics and surface plasmon interaction in gold nanorod-blended organic solar cell

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

Rana, Aniket; Lochan, Abhiram; Chand, Suresh

The inclusion of plasmonic nanoparticles into organic solar cell enhances the light harvesting properties that lead to higher power conversion efficiency without altering the device configuration. This work defines the consequences of the nanoparticle overloading amount and energy transfer process between gold nanorod and polymer (active matrix) in organic solar cells. We have studied the hole population decay dynamics coupled with gold nanorods loading amount which provides better understanding about device performance limiting factors. The exciton and plasmon together act as an interacting dipole; however, the energy exchange between these two has been elucidated via plasmon resonance energy transfer (PRET)more » mechanism. Further, the charge species have been identified specifically with respect to their energy levels appearing in ultrafast time domain. The specific interaction of these charge species with respective surface plasmon resonance mode, i.e., exciton to transverse mode of oscillation and polaron pair to longitudinal mode of oscillations, has been explained. Thus, our analysis reveals that PRET enhances the carrier population density in polymer via non-radiative process beyond the concurrence of a particular plasmon resonance oscillation mode and polymer absorption range. These findings give new insight and reveal specifically the factors that enhance and control the performance of gold nanorods blended organic solar cells. This work would lead in the emergence of future plasmon based efficient organic electronic devices.« less

Mast cell dynamics in the house rat (Rattus rattus) ovary during estrus cycle, pregnancy and lactation.

PubMed

Batth, B K; Parshad, R K

2000-02-01

The distribution of mast cells in various ovarian compartments was studied during different stages of the reproductive cycles in Rattus rattus. Two types of mast cell populations were recognized with light microscopy i.e., light purple and deep purple, the latter also includes deeply stained cells with extruded granules. Mast cells identified by electron microscopy showed the ultrastructural features during granule formation and release of their content. Significantly higher numbers of mast cells per unit area of ovary were seen at estrus and diestrus. Numbers of mast cells also remained high during pregnancy with possible involvement of mast cell products in vascularization of corpora lutea. A positive correlation existed between mast cell counts and embryo number during pregnancy. However, numbers of mast cells declined significantly after parturition.

Downregulation of endothelial adhesion molecules by dimethylfumarate, but not monomethylfumarate, and impairment of dynamic lymphocyte-endothelial cell interactions.

PubMed

Wallbrecht, Katrin; Drick, Nora; Hund, Anna-Carina; Schön, Michael P

2011-12-01

Although fumaric acid esters (FAE) have a decade-long firm place in the therapeutic armamentarium for psoriasis, their pleiotropic mode of action is not yet fully understood. While most previous studies have focused on the effects of FAE on leucocytes, we have addressed their activity on macro- and microvascular endothelial cells. As detected both on mRNA and protein levels, dimethylfumarate effected a profound reduction of TNFα-induced expression of E-selectin (CD62E), ICAM-1 (CD54) and VCAM-1 (CD106) on two different endothelial cell populations in a concentration-dependent manner. This reduction of several endothelial adhesion molecules was accompanied by a dramatic diminution of both rolling and firm adhesive interactions between endothelial cells and lymphocytes in a dynamic flow chamber system. Dimethylfumarate, at a concentration of 50 μm, reduced lymphocyte rolling on endothelial cells by 85.9% (P<0.001 compared to untreated controls), and it diminished the number of adherent cells by 88% (P<0.001). In contrast, monomethylfumarate (MMF) influenced neither surface expression of adhesion molecules nor interactions between endothelial cells and lymphocytes. These observations demonstrate that endothelial cells, in addition to the known effects on leucocytes, undergo profound functional changes in response to dimethylfumarate. These changes are accompanied by severely impaired dynamic interactions with lymphocytes, which constitute the critical initial step of leucocyte recruitment to inflamed tissues in psoriasis and other TNF-related inflammatory disorders. © 2011 John Wiley & Sons A/S.

The Neural Mechanism Exploration of Adaptive Motor Control: Dynamical Economic Cell Allocation in the Primary Motor Cortex.

PubMed

Li, Wei; Guo, Yangyang; Fan, Jing; Ma, Chaolin; Ma, Xuan; Chen, Xi; He, Jiping

2017-05-01

Adaptive flexibility is of significance for the smooth and efficient movements in goal attainment. However, the underlying work mechanism of the cerebral cortex in adaptive motor control still remains unclear. How does the cerebral cortex organize and coordinate the activity of a large population of cells in the implementation of various motor strategies? To explore this issue, single-unit activities from the M1 region and kinematic data were recorded simultaneously in monkeys performing 3D reach-to-grasp tasks with different perturbations. Varying motor control strategies were employed and achieved in different perturbed tasks, via the dynamic allocation of cells to modulate specific movement parameters. An economic principle was proposed for the first time to describe a basic rule for cell allocation in the primary motor cortex. This principle, defined as the Dynamic Economic Cell Allocation Mechanism (DECAM), guarantees benefit maximization in cell allocation under limited neuronal resources, and avoids committing resources to uneconomic investments for unreliable factors with no or little revenue. That is to say, the cells recruited are always preferentially allocated to those factors with reliable return; otherwise, the cells are dispatched to respond to other factors about task. The findings of this study might partially reveal the working mechanisms underlying the role of the cerebral cortex in adaptive motor control, wherein is also of significance for the design of future intelligent brain-machine interfaces and rehabilitation device.

Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns

DOE PAGES

Norred, Sarah Elizabeth; Caveney, Patrick M.; Chauhan, Gaurav; ...

2018-04-24

Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting—the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increasemore » in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA (“spatial noise”) that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. Furthermore, these results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.« less

Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns

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

Norred, Sarah Elizabeth; Caveney, Patrick M.; Chauhan, Gaurav

Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting—the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increasemore » in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA (“spatial noise”) that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. Furthermore, these results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.« less

Seasonal cycle of inbreeding and recombination of the parasitic mite Varroa destructor in honeybee colonies and its implications for the selection of acaricide resistance.

PubMed

Beaurepaire, Alexis L; Krieger, Klemens J; Moritz, Robin F A

2017-06-01

Varroa destructor is the most devastating parasite of the Western honeybee, Apis mellifera. In the light of the arm race opposing the host and its parasite, the population dynamics and genetic diversity of these organisms are key parameters. However, the life cycle of V. destructor is characterized by extreme inbreeding due to full sibling mating in the host brood cells. We here present an equation reflecting the evolution of inbreeding in such a clonal system, and compare our predictions with empirical data based on the analysis of seven microsatellite markers. This comparison revealed that the mites perform essentially incestuous mating in the beginning of the brood season. However, this pattern changes with the development of mite infestation. Despite the fact that the overall level of genetic diversity of the mites remained low through the season, multiple inbred lineages were identified in the mites we sampled in June. As a response to the decrease of brood availability and the increase of the parasite population in parallel in the colonies, these lineages recombined towards the end of the season as mites co-infest brood cells. Our results suggest that the ratio of the number of mite per brood cell in the colony determines the genetic structure of the populations of V. destructor. This intracolonial population dynamics has great relevance for the selection of acaricide resistance in V. destructor. If chemical treatments occur before the recombination phase, inbreeding will greatly enhance the fixation of resistance alleles at the colony level. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Quorum-Sensing Synchronization of Synthetic Toggle Switches: A Design Based on Monotone Dynamical Systems Theory

PubMed Central

Nikolaev, Evgeni V.

2016-01-01

Synthetic constructs in biotechnology, biocomputing, and modern gene therapy interventions are often based on plasmids or transfected circuits which implement some form of “on-off” switch. For example, the expression of a protein used for therapeutic purposes might be triggered by the recognition of a specific combination of inducers (e.g., antigens), and memory of this event should be maintained across a cell population until a specific stimulus commands a coordinated shut-off. The robustness of such a design is hampered by molecular (“intrinsic”) or environmental (“extrinsic”) noise, which may lead to spontaneous changes of state in a subset of the population and is reflected in the bimodality of protein expression, as measured for example using flow cytometry. In this context, a “majority-vote” correction circuit, which brings deviant cells back into the required state, is highly desirable, and quorum-sensing has been suggested as a way for cells to broadcast their states to the population as a whole so as to facilitate consensus. In this paper, we propose what we believe is the first such a design that has mathematically guaranteed properties of stability and auto-correction under certain conditions. Our approach is guided by concepts and theory from the field of “monotone” dynamical systems developed by M. Hirsch, H. Smith, and others. We benchmark our design by comparing it to an existing design which has been the subject of experimental and theoretical studies, illustrating its superiority in stability and self-correction of synchronization errors. Our stability analysis, based on dynamical systems theory, guarantees global convergence to steady states, ruling out unpredictable (“chaotic”) behaviors and even sustained oscillations in the limit of convergence. These results are valid no matter what are the values of parameters, and are based only on the wiring diagram. The theory is complemented by extensive computational bifurcation analysis, performed for a biochemically-detailed and biologically-relevant model that we developed. Another novel feature of our approach is that our theorems on exponential stability of steady states for homogeneous or mixed populations are valid independently of the number N of cells in the population, which is usually very large (N ≫ 1) and unknown. We prove that the exponential stability depends on relative proportions of each type of state only. While monotone systems theory has been used previously for systems biology analysis, the current work illustrates its power for synthetic biology design, and thus has wider significance well beyond the application to the important problem of coordination of toggle switches. PMID:27128344

Mathematical Models of the Impact of IL2 Modulation Therapies on T Cell Dynamics

PubMed Central

León, Kalet; García-Martínez, Karina; Carmenate, Tania

2013-01-01

Several reports in the literature have drawn a complex picture of the effect of treatments aiming to modulate IL2 activity in vivo. They seem to promote either immunity or tolerance, probably depending on the specific context, dose, and timing of their application. Such complexity might derive from the pleiotropic role of IL2 in T cell dynamics. To theoretically address the latter possibility, our group has developed several mathematical models for Helper, Regulatory, and Memory T cell population dynamics, which account for most well-known facts concerning their relationship with IL2. We have simulated the effect of several types of therapies, including the injection of: IL2; antibodies anti-IL2; IL2/anti-IL2 immune-complexes; and mutant variants of IL2. We studied the qualitative and quantitative conditions of dose and timing for these treatments which allow them to potentiate either immunity or tolerance. Our results provide reasonable explanations for the existent pre-clinical and clinical data, predict some novel treatments, and further provide interesting practical guidelines to optimize the future application of these types of treatments. PMID:24376444

Adaptation in Coding by Large Populations of Neurons in the Retina

NASA Astrophysics Data System (ADS)

Ioffe, Mark L.

A comprehensive theory of neural computation requires an understanding of the statistical properties of the neural population code. The focus of this work is the experimental study and theoretical analysis of the statistical properties of neural activity in the tiger salamander retina. This is an accessible yet complex system, for which we control the visual input and record from a substantial portion--greater than a half--of the ganglion cell population generating the spiking output. Our experiments probe adaptation of the retina to visual statistics: a central feature of sensory systems which have to adjust their limited dynamic range to a far larger space of possible inputs. In Chapter 1 we place our work in context with a brief overview of the relevant background. In Chapter 2 we describe the experimental methodology of recording from 100+ ganglion cells in the tiger salamander retina. In Chapter 3 we first present the measurements of adaptation of individual cells to changes in stimulation statistics and then investigate whether pairwise correlations in fluctuations of ganglion cell activity change across different stimulation conditions. We then transition to a study of the population-level probability distribution of the retinal response captured with maximum-entropy models. Convergence of the model inference is presented in Chapter 4. In Chapter 5 we first test the empirical presence of a phase transition in such models fitting the retinal response to different experimental conditions, and then proceed to develop other characterizations which are sensitive to complexity in the interaction matrix. This includes an analysis of the dynamics of sampling at finite temperature, which demonstrates a range of subtle attractor-like properties in the energy landscape. These are largely conserved when ambient illumination is varied 1000-fold, a result not necessarily apparent from the measured low-order statistics of the distribution. Our results form a consistent picture which is discussed at the end of Chapter 5. We conclude with a few future directions related to this thesis.

Simultaneous fast measurement of circuit dynamics at multiple sites across the mammalian brain

PubMed Central

Kim, Christina K; Yang, Samuel J; Pichamoorthy, Nandini; Young, Noah P; Kauvar, Isaac; Jennings, Joshua H; Lerner, Talia N; Berndt, Andre; Lee, Soo Yeun; Ramakrishnan, Charu; Davidson, Thomas J; Inoue, Masatoshi; Bito, Haruhiko; Deisseroth, Karl

2017-01-01

Real-time activity measurements from multiple specific cell populations and projections are likely to be important for understanding the brain as a dynamical system. Here we developed frame-projected independent-fiber photometry (FIP), which we used to record fluorescence activity signals from many brain regions simultaneously in freely behaving mice. We explored the versatility of the FIP microscope by quantifying real-time activity relationships among many brain regions during social behavior, simultaneously recording activity along multiple axonal pathways during sensory experience, performing simultaneous two-color activity recording, and applying optical perturbation tuned to elicit dynamics that match naturally occurring patterns observed during behavior. PMID:26878381

Early Dynamics of Cerebrospinal CD14+ Monocytes and CD15+ Granulocytes in Patients after Severe Traumatic Brain Injury: A Cohort Study

PubMed Central

Postl, Lukas Kurt; Bogner, Viktoria; Beirer, Marc; Kanz, Karl Georg; Egginger, Christoph; Schmitt-Sody, Markus; Biberthaler, Peter; Kirchhoff, Chlodwig

2015-01-01

In traumatic brain injury (TBI) the analysis of neuroinflammatory mechanisms gained increasing interest. In this context certain immunocompetent cells might play an important role. Interestingly, in the actual literature there exist only a few studies focusing on the role of monocytes and granulocytes in TBI patients. In this regard it has recently reported that the choroid plexus represents an early, selective barrier for leukocytes after brain injury. Therefore the aim of this study was to evaluate the very early dynamics of CD14+ monocytes and CD15+ granulocyte in CSF of patients following severe TBI with regard to the integrity of the BBB. Cytometric flow analysis was performed to analyze the CD14+ monocyte and CD15+ granulocyte population in CSF of TBI patients. The ratio of CSF and serum albumin as a measure for the BBB's integrity was assessed in parallel. CSF samples of patients receiving lumbar puncture for elective surgery were obtained as controls. Overall 15 patients following severe TBI were enrolled. 10 patients were examined as controls. In patients, the monocyte population as well as the granulocyte population was significantly increased within 72 hours after TBI. The BBB's integrity did not have a significant influence on the cell count in the CSF. PMID:26568661

HU content and dynamics in Escherichia coli during the cell cycle and at different growth rates.

PubMed

Abebe, Anteneh Hailu; Aranovich, Alexander; Fishov, Itzhak

2017-10-16

DNA-binding proteins play an important role in maintaining bacterial chromosome structure and functions. Heat-unstable (HU) histone-like protein is one of the most abundant of these proteins and participates in all major chromosome-related activities. Owing to its low sequence specificity, HU fusions with fluorescent proteins were used for general staining of the nucleoid, aiming to reveal its morphology and dynamics. We have exploited a single chromosomal copy of hupA-egfp fusion under the native promoter and used quantitative microscopy imaging to investigate the amount and dynamics of HUα in Escherichia coli cells. We found that in steady-state growing populations the cellular HUα content is proportional to the cell size, whereas its concentration is size independent. Single-cell live microscopy imaging confirmed that the amount of HUα exponentially increases during the cell cycle, but its concentration is maintained constant. This supports the existence of an auto-regulatory mechanism underlying the HUα cellular level, in addition to reflecting the gene copy number. Both the HUα amount and concentration strongly increase with the cell growth rate in different culture media. Unexpectedly, the HU/DNA stoichiometry also remarkably increases with the growth rate. This last finding may be attributed to a higher requirement for maintaining the chromosome structure in nucleoids with higher complexity. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Cellular plasticity enables adaptation to unforeseen cell-cycle rewiring challenges.

PubMed

Katzir, Yair; Stolovicki, Elad; Stern, Shay; Braun, Erez

2012-01-01

The fundamental dynamics of the cell cycle, underlying cell growth and reproduction, were previously found to be robust under a wide range of environmental and internal perturbations. This property was commonly attributed to its network structure, which enables the coordinated interactions among hundreds of proteins. Despite significant advances in deciphering the components and autonomous interactions of this network, understanding the interfaces of the cell cycle with other major cellular processes is still lacking. To gain insight into these interfaces, we used the process of genome-rewiring in yeast by placing an essential metabolic gene HIS3 from the histidine biosynthesis pathway, under the exclusive regulation of different cell-cycle promoters. In a medium lacking histidine and under partial inhibition of the HIS3p, the rewired cells encountered an unforeseen multitasking challenge; the cell-cycle regulatory genes were required to regulate the essential histidine-pathway gene in concert with the other metabolic demands, while simultaneously driving the cell cycle through its proper temporal phases. We show here that chemostat cell populations with rewired cell-cycle promoters adapted within a short time to accommodate the inhibition of HIS3p and stabilized a new phenotypic state. Furthermore, a significant fraction of the population was able to adapt and grow into mature colonies on plates under such inhibiting conditions. The adapted state was shown to be stably inherited across generations. These adaptation dynamics were accompanied by a non-specific and irreproducible genome-wide transcriptional response. Adaptation of the cell-cycle attests to its multitasking capabilities and flexible interface with cellular metabolic processes and requirements. Similar adaptation features were found in our previous work when rewiring HIS3 to the GAL system and switching cells from galactose to glucose. Thus, at the basis of cellular plasticity is the emergence of a yet-unknown general, non-specific mechanism allowing fast inherited adaptation to unforeseen challenges.

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

Fas/APO-1 protein is increased in spaceflown lymphocytes (Jurkat)

NASA Technical Reports Server (NTRS)

Cubano, L. A.; Lewis, M. L.

2000-01-01

Human lymphocytes flown on the Space Shuttle respond poorly to mitogen stimulation and populations of the lymphoblastoid T cell line, Jurkat, manifest growth arrest, increase in apoptosis and time- and microgravity-dependent increases in the soluble form of the cell death factor, Fas/APO-1 (sFas). The potential role of apoptosis in population dynamics of space-flown lymphocytes has not been investigated previously. We flew Jurkat cells on Space Transportation System (STS)-80 and STS-95 to determine whether apoptosis and the apparent microgravity-related release of sFas are characteristic of lymphocytes in microgravity. The effects of spaceflight and ground-based tests simulating spaceflight experimental conditions, including high cell density and low serum concentration, were assessed. Immunofluorescence microscopy showed increased cell associated Fas in flown cells. Results of STS-80 and STS-95 confirmed increase in apoptosis during spaceflight and the release of sFas as a repeatable, time-dependent and microgravity-related response. Ground-based tests showed that holding cells at 1.5 million/ml in medium containing 2% serum before launch did not increase sFas. Reports of increased Fas in cells of the elderly and the increases in spaceflown cells suggest possible similarities between aging and spaceflight effects on lymphocytes.

Multimodal microfluidic platform for controlled culture and analysis of unicellular organisms.

PubMed

Geng, Tao; Smallwood, Chuck R; Bredeweg, Erin L; Pomraning, Kyle R; Plymale, Andrew E; Baker, Scott E; Evans, James E; Kelly, Ryan T

2017-09-01

Modern live-cell imaging approaches permit real-time visualization of biological processes, yet limitations exist for unicellular organism isolation, culturing, and long-term imaging that preclude fully understanding how cells sense and respond to environmental perturbations and the link between single-cell variability and whole-population dynamics. Here, we present a microfluidic platform that provides fine control over the local environment with the capacity to replace media components at any experimental time point, and provides both perfused and compartmentalized cultivation conditions depending on the valve configuration. The functionality and flexibility of the platform were validated using both bacteria and yeast having different sizes, motility, and growth media. The demonstrated ability to track the growth and dynamics of both motile and non-motile prokaryotic and eukaryotic organisms emphasizes the versatility of the devices, which should enable studies in bioenergy and environmental research.

Mechanism of biphasic charge recombination and accumulation in TiO2 mesoporous structured perovskite solar cells.

PubMed

Wang, Hao-Yi; Wang, Yi; Yu, Man; Han, Jun; Guo, Zhi-Xin; Ai, Xi-Cheng; Zhang, Jian-Ping; Qin, Yujun

2016-04-28

Organic-inorganic halide perovskite solar cells are becoming the next big thing in the photovoltaic field owing to their rapidly developing photoelectric conversion performance. Herein, mesoporous structured perovskite devices with various perovskite grain sizes are fabricated by a sequential dropping method, and the charge recombination dynamics is investigated by transient optical-electric measurements. All devices exhibit an overall power conversion efficiency around 15%. More importantly, a biphasic trap-limited charge recombination process is proposed and interpreted by taking into account the specific charge accumulation mechanism in perovskite solar cells. At low Fermi levels, photo-generated electrons predominately populate in the perovskite phase, while at high Fermi levels, most electrons occupy traps in mesoporous TiO2. As a result, the dynamics of charge recombination is, respectively, dominated by the perovskite phase and mesoporous TiO2 in these two cases. The present work would give a new perspective on the charge recombination process in meso-structured perovskite solar cells.

Monitoring the dynamics of clonal tumour evolution in vivo using secreted luciferases.

PubMed

Charles, Joël P; Fuchs, Jeannette; Hefter, Mirjam; Vischedyk, Jonas B; Kleint, Maximilian; Vogiatzi, Fotini; Schäfer, Jonas A; Nist, Andrea; Timofeev, Oleg; Wanzel, Michael; Stiewe, Thorsten

2014-06-03

Tumours are heterogeneous cell populations that undergo clonal evolution during tumour progression, metastasis and response to therapy. Short hairpin RNAs (shRNAs) generate stable loss-of-function phenotypes and are versatile experimental tools to explore the contribution of individual genetic alterations to clonal evolution. In these experiments tumour cells carrying shRNAs are commonly tracked with fluorescent reporters. While this works well for cell culture studies and leukaemia mouse models, fluorescent reporters are poorly suited for animals with solid tumours--the most common tumour types in cancer patients. Here we develop a toolkit that uses secreted luciferases to track the fate of two different shRNA-expressing tumour cell clones competitively, both in vitro and in vivo. We demonstrate that secreted luciferase activities can be measured robustly in the blood stream of tumour-bearing mice to accurately quantify, in a minimally invasive manner, the dynamic evolution of two genetically distinct tumour subclones in preclinical mouse models of tumour development, metastasis and therapy.

The role of spatial dynamics in modulating metabolic interactions in biofilm development

NASA Astrophysics Data System (ADS)

Bocci, Federico; Lu, Mingyang; Suzuki, Yoko; Onuchic, Jose

Cell phenotypic expression is substantially affected by the presence of environmental stresses and cell-cell communication mechanisms. We study the metabolic interactions of the glutamate synthesis pathway to explain the oscillation of growth rate observed in a B. Subtilis colony. Previous modelling schemes had failed in fully reproducing quantitative experimental observations as they did not explicitly address neither the diffusion of small metabolites nor the spatial distribution of phenotypically distinct bacteria inside the colony. We introduce a continuous space-temporal framework to explain how biofilm development dynamics is influenced by the metabolic interplay between two bacterial phenotypes composing the interior and the peripheral layer of the biofilm. Growth oscillations endorse the preservation of a high level of nutrients in the interior through diffusion and colony expansion in the periphery altogether. Our findings point out that perturbations of environmental conditions can result in the interruption of the interplay between cell populations and advocate alternative approaches to biofilm control strategies.

Dynamics of Salmonella infection of macrophages at the single cell level.

PubMed

Gog, Julia R; Murcia, Alicia; Osterman, Natan; Restif, Olivier; McKinley, Trevelyan J; Sheppard, Mark; Achouri, Sarra; Wei, Bin; Mastroeni, Pietro; Wood, James L N; Maskell, Duncan J; Cicuta, Pietro; Bryant, Clare E

2012-10-07

Salmonella enterica causes a range of diseases. Salmonellae are intracellular parasites of macrophages, and the control of bacteria within these cells is critical to surviving an infection. The dynamics of the bacteria invading, surviving, proliferating in and killing macrophages are central to disease pathogenesis. Fundamentally important parameters, however, such as the cellular infection rate, have not previously been calculated. We used two independent approaches to calculate the macrophage infection rate: mathematical modelling of Salmonella infection experiments, and analysis of real-time video microscopy of infection events. Cells repeatedly encounter salmonellae, with the bacteria often remain associated with the macrophage for more than ten seconds. Once Salmonella encounters a macrophage, the probability of that bacterium infecting the cell is remarkably low: less than 5%. The macrophage population is heterogeneous in terms of its susceptibility to the first infection event. Once infected, a macrophage can undergo further infection events, but these reinfection events occur at a lower rate than that of the primary infection.

Monitoring the dynamics of clonal tumour evolution in vivo using secreted luciferases

PubMed Central

Charles, Joël P.; Fuchs, Jeannette; Hefter, Mirjam; Vischedyk, Jonas B.; Kleint, Maximilian; Vogiatzi, Fotini; Schäfer, Jonas A.; Nist, Andrea; Timofeev, Oleg; Wanzel, Michael; Stiewe, Thorsten

2014-01-01

Tumours are heterogeneous cell populations that undergo clonal evolution during tumour progression, metastasis and response to therapy. Short hairpin RNAs (shRNAs) generate stable loss-of-function phenotypes and are versatile experimental tools to explore the contribution of individual genetic alterations to clonal evolution. In these experiments tumour cells carrying shRNAs are commonly tracked with fluorescent reporters. While this works well for cell culture studies and leukaemia mouse models, fluorescent reporters are poorly suited for animals with solid tumours—the most common tumour types in cancer patients. Here we develop a toolkit that uses secreted luciferases to track the fate of two different shRNA-expressing tumour cell clones competitively, both in vitro and in vivo. We demonstrate that secreted luciferase activities can be measured robustly in the blood stream of tumour-bearing mice to accurately quantify, in a minimally invasive manner, the dynamic evolution of two genetically distinct tumour subclones in preclinical mouse models of tumour development, metastasis and therapy. PMID:24889111

Blood CXCR3+ CD4 T Cells Are Enriched in Inducible Replication Competent HIV in Aviremic Antiretroviral Therapy-Treated Individuals

PubMed Central

Banga, Riddhima; Procopio, Francesco A.; Ruggiero, Alessandra; Noto, Alessandra; Ohmiti, Khalid; Cavassini, Matthias; Corpataux, Jean-Marc; Paxton, William A.; Pollakis, Georgios; Perreau, Matthieu

2018-01-01

We recently demonstrated that lymph nodes (LNs) PD-1+/T follicular helper (Tfh) cells from antiretroviral therapy (ART)-treated HIV-infected individuals were enriched in cells containing replication competent virus. However, the distribution of cells containing inducible replication competent virus has been only partially elucidated in blood memory CD4 T-cell populations including the Tfh cell counterpart circulating in blood (cTfh). In this context, we have investigated the distribution of (1) total HIV-infected cells and (2) cells containing replication competent and infectious virus within various blood and LN memory CD4 T-cell populations of conventional antiretroviral therapy (cART)-treated HIV-infected individuals. In the present study, we show that blood CXCR3-expressing memory CD4 T cells are enriched in cells containing inducible replication competent virus and contributed the most to the total pool of cells containing replication competent and infectious virus in blood. Interestingly, subsequent proviral sequence analysis did not indicate virus compartmentalization between blood and LN CD4 T-cell populations, suggesting dynamic interchanges between the two compartments. We then investigated whether the composition of blood HIV reservoir may reflect the polarization of LN CD4 T cells at the time of reservoir seeding and showed that LN PD-1+ CD4 T cells of viremic untreated HIV-infected individuals expressed significantly higher levels of CXCR3 as compared to CCR4 and/or CCR6, suggesting that blood CXCR3-expressing CD4 T cells may originate from LN PD-1+ CD4 T cells. Taken together, these results indicate that blood CXCR3-expressing CD4 T cells represent the major blood compartment containing inducible replication competent virus in treated aviremic HIV-infected individuals. PMID:29459864

Blood CXCR3+ CD4 T Cells Are Enriched in Inducible Replication Competent HIV in Aviremic Antiretroviral Therapy-Treated Individuals.

PubMed

Banga, Riddhima; Procopio, Francesco A; Ruggiero, Alessandra; Noto, Alessandra; Ohmiti, Khalid; Cavassini, Matthias; Corpataux, Jean-Marc; Paxton, William A; Pollakis, Georgios; Perreau, Matthieu

2018-01-01

We recently demonstrated that lymph nodes (LNs) PD-1 + /T follicular helper (Tfh) cells from antiretroviral therapy (ART)-treated HIV-infected individuals were enriched in cells containing replication competent virus. However, the distribution of cells containing inducible replication competent virus has been only partially elucidated in blood memory CD4 T-cell populations including the Tfh cell counterpart circulating in blood (cTfh). In this context, we have investigated the distribution of (1) total HIV-infected cells and (2) cells containing replication competent and infectious virus within various blood and LN memory CD4 T-cell populations of conventional antiretroviral therapy (cART)-treated HIV-infected individuals. In the present study, we show that blood CXCR3-expressing memory CD4 T cells are enriched in cells containing inducible replication competent virus and contributed the most to the total pool of cells containing replication competent and infectious virus in blood. Interestingly, subsequent proviral sequence analysis did not indicate virus compartmentalization between blood and LN CD4 T-cell populations, suggesting dynamic interchanges between the two compartments. We then investigated whether the composition of blood HIV reservoir may reflect the polarization of LN CD4 T cells at the time of reservoir seeding and showed that LN PD-1 + CD4 T cells of viremic untreated HIV-infected individuals expressed significantly higher levels of CXCR3 as compared to CCR4 and/or CCR6, suggesting that blood CXCR3-expressing CD4 T cells may originate from LN PD-1 + CD4 T cells. Taken together, these results indicate that blood CXCR3-expressing CD4 T cells represent the major blood compartment containing inducible replication competent virus in treated aviremic HIV-infected individuals.

Georges Bank: a leaky incubator of Alexandrium fundyense blooms

PubMed Central

McGillicuddy, D.J.; Townsend, D.W.; Keafer, B.A.; Thomas, M.A.; Anderson, D.M.

2012-01-01

A series of oceanographic surveys on Georges Bank document variability of populations of the toxic dinoflagellate Alexandrium fundyense on time scales ranging from synoptic to seasonal to interannual. Blooms of A. fundyense on Georges Bank can reach concentrations on the order of 104 cells l−1, and are generally bank-wide in extent. Georges Bank populations of A. fundyense appear to be quasi-independent of those in the adjacent coastal Gulf of Maine, insofar as they occupy a hydrographic niche that is colder and saltier than their coastal counterparts. In contrast to coastal populations that rely on abundant resting cysts for bloom initiation, very few cysts are present in the sediments on Georges Bank. Bloom dynamics must therefore be largely controlled by the balance between growth and mortality processes, which are at present largely unknown for this population. Based on correlations between cell abundance and nutrient distributions, ammonium appears to be an important source of nitrogen for A. fundyense blooms on Georges Bank. PMID:24976691

Georges Bank: a leaky incubator of Alexandrium fundyense blooms.

PubMed

McGillicuddy, D J; Townsend, D W; Keafer, B A; Thomas, M A; Anderson, D M

2014-05-01

A series of oceanographic surveys on Georges Bank document variability of populations of the toxic dinoflagellate Alexandrium fundyense on time scales ranging from synoptic to seasonal to interannual. Blooms of A. fundyense on Georges Bank can reach concentrations on the order of 10 4 cells l -1 , and are generally bank-wide in extent. Georges Bank populations of A. fundyense appear to be quasi-independent of those in the adjacent coastal Gulf of Maine, insofar as they occupy a hydrographic niche that is colder and saltier than their coastal counterparts. In contrast to coastal populations that rely on abundant resting cysts for bloom initiation, very few cysts are present in the sediments on Georges Bank. Bloom dynamics must therefore be largely controlled by the balance between growth and mortality processes, which are at present largely unknown for this population. Based on correlations between cell abundance and nutrient distributions, ammonium appears to be an important source of nitrogen for A. fundyense blooms on Georges Bank.

A correlative and quantitative imaging approach enabling characterization of primary cell-cell communication: Case of human CD4+ T cell-macrophage immunological synapses.

PubMed

Kasprowicz, Richard; Rand, Emma; O'Toole, Peter J; Signoret, Nathalie

2018-05-22

Cell-to-cell communication engages signaling and spatiotemporal reorganization events driven by highly context-dependent and dynamic intercellular interactions, which are difficult to capture within heterogeneous primary cell cultures. Here, we present a straightforward correlative imaging approach utilizing commonly available instrumentation to sample large numbers of cell-cell interaction events, allowing qualitative and quantitative characterization of rare functioning cell-conjugates based on calcium signals. We applied this approach to examine a previously uncharacterized immunological synapse, investigating autologous human blood CD4 + T cells and monocyte-derived macrophages (MDMs) forming functional conjugates in vitro. Populations of signaling conjugates were visualized, tracked and analyzed by combining live imaging, calcium recording and multivariate statistical analysis. Correlative immunofluorescence was added to quantify endogenous molecular recruitments at the cell-cell junction. By analyzing a large number of rare conjugates, we were able to define calcium signatures associated with different states of CD4 + T cell-MDM interactions. Quantitative image analysis of immunostained conjugates detected the propensity of endogenous T cell surface markers and intracellular organelles to polarize towards cell-cell junctions with high and sustained calcium signaling profiles, hence defining immunological synapses. Overall, we developed a broadly applicable approach enabling detailed single cell- and population-based investigations of rare cell-cell communication events with primary cells.

Evolutionarily stable disequilibrium: endless dynamics of evolution in a stationary population.

PubMed

Takeuchi, Nobuto; Kaneko, Kunihiko; Hogeweg, Paulien

2016-05-11

Evolution is often conceived as changes in the properties of a population over generations. Does this notion exhaust the possible dynamics of evolution? Life is hierarchically organized, and evolution can operate at multiple levels with conflicting tendencies. Using a minimal model of such conflicting multilevel evolution, we demonstrate the possibility of a novel mode of evolution that challenges the above notion: individuals ceaselessly modify their genetically inherited phenotype and fitness along their lines of descent, without involving apparent changes in the properties of the population. The model assumes a population of primitive cells (protocells, for short), each containing a population of replicating catalytic molecules. Protocells are selected towards maximizing the catalytic activity of internal molecules, whereas molecules tend to evolve towards minimizing it in order to maximize their relative fitness within a protocell. These conflicting evolutionary tendencies at different levels and genetic drift drive the lineages of protocells to oscillate endlessly between high and low intracellular catalytic activity, i.e. high and low fitness, along their lines of descent. This oscillation, however, occurs independently in different lineages, so that the population as a whole appears stationary. Therefore, ongoing evolution can be hidden behind an apparently stationary population owing to conflicting multilevel evolution. © 2016 The Authors.

Introduction of a Framework for Dynamic Knowledge Representation of the Control Structure of Transplant Immunology: Employing the Power of Abstraction with a Solid Organ Transplant Agent-Based Model

PubMed Central

An, Gary

2015-01-01

Agent-based modeling has been used to characterize the nested control loops and non-linear dynamics associated with inflammatory and immune responses, particularly as a means of visualizing putative mechanistic hypotheses. This process is termed dynamic knowledge representation and serves a critical role in facilitating the ability to test and potentially falsify hypotheses in the current data- and hypothesis-rich biomedical research environment. Importantly, dynamic computational modeling aids in identifying useful abstractions, a fundamental scientific principle that pervades the physical sciences. Recognizing the critical scientific role of abstraction provides an intellectual and methodological counterweight to the tendency in biology to emphasize comprehensive description as the primary manifestation of biological knowledge. Transplant immunology represents yet another example of the challenge of identifying sufficient understanding of the inflammatory/immune response in order to develop and refine clinically effective interventions. Advances in immunosuppressive therapies have greatly improved solid organ transplant (SOT) outcomes, most notably by reducing and treating acute rejection. The end goal of these transplant immune strategies is to facilitate effective control of the balance between regulatory T cells and the effector/cytotoxic T-cell populations in order to generate, and ideally maintain, a tolerant phenotype. Characterizing the dynamics of immune cell populations and the interactive feedback loops that lead to graft rejection or tolerance is extremely challenging, but is necessary if rational modulation to induce transplant tolerance is to be accomplished. Herein is presented the solid organ agent-based model (SOTABM) as an initial example of an agent-based model (ABM) that abstractly reproduces the cellular and molecular components of the immune response to SOT. Despite its abstract nature, the SOTABM is able to qualitatively reproduce acute rejection and the suppression of acute rejection by immunosuppression to generate transplant tolerance. The SOTABM is intended as an initial example of how ABMs can be used to dynamically represent mechanistic knowledge concerning transplant immunology in a scalable and expandable form and can thus potentially serve as useful adjuncts to the investigation and development of control strategies to induce transplant tolerance. PMID:26594211

Introduction of a Framework for Dynamic Knowledge Representation of the Control Structure of Transplant Immunology: Employing the Power of Abstraction with a Solid Organ Transplant Agent-Based Model.

PubMed

An, Gary

2015-01-01

Agent-based modeling has been used to characterize the nested control loops and non-linear dynamics associated with inflammatory and immune responses, particularly as a means of visualizing putative mechanistic hypotheses. This process is termed dynamic knowledge representation and serves a critical role in facilitating the ability to test and potentially falsify hypotheses in the current data- and hypothesis-rich biomedical research environment. Importantly, dynamic computational modeling aids in identifying useful abstractions, a fundamental scientific principle that pervades the physical sciences. Recognizing the critical scientific role of abstraction provides an intellectual and methodological counterweight to the tendency in biology to emphasize comprehensive description as the primary manifestation of biological knowledge. Transplant immunology represents yet another example of the challenge of identifying sufficient understanding of the inflammatory/immune response in order to develop and refine clinically effective interventions. Advances in immunosuppressive therapies have greatly improved solid organ transplant (SOT) outcomes, most notably by reducing and treating acute rejection. The end goal of these transplant immune strategies is to facilitate effective control of the balance between regulatory T cells and the effector/cytotoxic T-cell populations in order to generate, and ideally maintain, a tolerant phenotype. Characterizing the dynamics of immune cell populations and the interactive feedback loops that lead to graft rejection or tolerance is extremely challenging, but is necessary if rational modulation to induce transplant tolerance is to be accomplished. Herein is presented the solid organ agent-based model (SOTABM) as an initial example of an agent-based model (ABM) that abstractly reproduces the cellular and molecular components of the immune response to SOT. Despite its abstract nature, the SOTABM is able to qualitatively reproduce acute rejection and the suppression of acute rejection by immunosuppression to generate transplant tolerance. The SOTABM is intended as an initial example of how ABMs can be used to dynamically represent mechanistic knowledge concerning transplant immunology in a scalable and expandable form and can thus potentially serve as useful adjuncts to the investigation and development of control strategies to induce transplant tolerance.

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.

The ecology of cancer from an evolutionary game theory perspective.

PubMed

Pacheco, Jorge M; Santos, Francisco C; Dingli, David

2014-08-06

The accumulation of somatic mutations, to which the cellular genome is permanently exposed, often leads to cancer. Analysis of any tumour shows that, besides the malignant cells, one finds other 'supporting' cells such as fibroblasts, immune cells of various types and even blood vessels. Together, these cells generate the microenvironment that enables the malignant cell population to grow and ultimately lead to disease. Therefore, understanding the dynamics of tumour growth and response to therapy is incomplete unless the interactions between the malignant cells and normal cells are investigated in the environment in which they take place. The complex interactions between cells in such an ecosystem result from the exchange of information in the form of cytokines- and adhesion-dependent interactions. Such processes impose costs and benefits to the participating cells that may be conveniently recast in the form of a game pay-off matrix. As a result, tumour progression and dynamics can be described in terms of evolutionary game theory (EGT), which provides a convenient framework in which to capture the frequency-dependent nature of ecosystem dynamics. Here, we provide a tutorial review of the central aspects of EGT, establishing a relation with the problem of cancer. Along the way, we also digress on fitness and of ways to compute it. Subsequently, we show how EGT can be applied to the study of the various manifestations and dynamics of multiple myeloma bone disease and its preceding condition known as monoclonal gammopathy of undetermined significance. We translate the complex biochemical signals into costs and benefits of different cell types, thus defining a game pay-off matrix. Then we use the well-known properties of the EGT equations to reduce the number of core parameters that characterize disease evolution. Finally, we provide an interpretation of these core parameters in terms of what their function is in the ecosystem we are describing and generate predictions on the type and timing of interventions that can alter the natural history of these two conditions.

Optimal balance of the striatal medium spiny neuron network.

PubMed

Ponzi, Adam; Wickens, Jeffery R

2013-04-01

Slowly varying activity in the striatum, the main Basal Ganglia input structure, is important for the learning and execution of movement sequences. Striatal medium spiny neurons (MSNs) form cell assemblies whose population firing rates vary coherently on slow behaviourally relevant timescales. It has been shown that such activity emerges in a model of a local MSN network but only at realistic connectivities of 10 ~ 20% and only when MSN generated inhibitory post-synaptic potentials (IPSPs) are realistically sized. Here we suggest a reason for this. We investigate how MSN network generated population activity interacts with temporally varying cortical driving activity, as would occur in a behavioural task. We find that at unrealistically high connectivity a stable winners-take-all type regime is found where network activity separates into fixed stimulus dependent regularly firing and quiescent components. In this regime only a small number of population firing rate components interact with cortical stimulus variations. Around 15% connectivity a transition to a more dynamically active regime occurs where all cells constantly switch between activity and quiescence. In this low connectivity regime, MSN population components wander randomly and here too are independent of variations in cortical driving. Only in the transition regime do weak changes in cortical driving interact with many population components so that sequential cell assemblies are reproducibly activated for many hundreds of milliseconds after stimulus onset and peri-stimulus time histograms display strong stimulus and temporal specificity. We show that, remarkably, this activity is maximized at striatally realistic connectivities and IPSP sizes. Thus, we suggest the local MSN network has optimal characteristics - it is neither too stable to respond in a dynamically complex temporally extended way to cortical variations, nor is it too unstable to respond in a consistent repeatable way. Rather, it is optimized to generate stimulus dependent activity patterns for long periods after variations in cortical excitation.

Optimal Balance of the Striatal Medium Spiny Neuron Network

PubMed Central

Ponzi, Adam; Wickens, Jeffery R.

2013-01-01

Slowly varying activity in the striatum, the main Basal Ganglia input structure, is important for the learning and execution of movement sequences. Striatal medium spiny neurons (MSNs) form cell assemblies whose population firing rates vary coherently on slow behaviourally relevant timescales. It has been shown that such activity emerges in a model of a local MSN network but only at realistic connectivities of and only when MSN generated inhibitory post-synaptic potentials (IPSPs) are realistically sized. Here we suggest a reason for this. We investigate how MSN network generated population activity interacts with temporally varying cortical driving activity, as would occur in a behavioural task. We find that at unrealistically high connectivity a stable winners-take-all type regime is found where network activity separates into fixed stimulus dependent regularly firing and quiescent components. In this regime only a small number of population firing rate components interact with cortical stimulus variations. Around connectivity a transition to a more dynamically active regime occurs where all cells constantly switch between activity and quiescence. In this low connectivity regime, MSN population components wander randomly and here too are independent of variations in cortical driving. Only in the transition regime do weak changes in cortical driving interact with many population components so that sequential cell assemblies are reproducibly activated for many hundreds of milliseconds after stimulus onset and peri-stimulus time histograms display strong stimulus and temporal specificity. We show that, remarkably, this activity is maximized at striatally realistic connectivities and IPSP sizes. Thus, we suggest the local MSN network has optimal characteristics – it is neither too stable to respond in a dynamically complex temporally extended way to cortical variations, nor is it too unstable to respond in a consistent repeatable way. Rather, it is optimized to generate stimulus dependent activity patterns for long periods after variations in cortical excitation. PMID:23592954

Chemotaxis in densely populated tissue determines germinal center anatomy and cell motility: a new paradigm for the development of complex tissues.

PubMed

Hawkins, Jared B; Jones, Mark T; Plassmann, Paul E; Thorley-Lawson, David A

2011-01-01

Germinal centers (GCs) are complex dynamic structures that form within lymph nodes as an essential process in the humoral immune response. They represent a paradigm for studying the regulation of cell movement in the development of complex anatomical structures. We have developed a simulation of a modified cyclic re-entry model of GC dynamics which successfully employs chemotaxis to recapitulate the anatomy of the primary follicle and the development of a mature GC, including correctly structured mantle, dark and light zones. We then show that correct single cell movement dynamics (including persistent random walk and inter-zonal crossing) arise from this simulation as purely emergent properties. The major insight of our study is that chemotaxis can only achieve this when constrained by the known biological properties that cells are incompressible, exist in a densely packed environment, and must therefore compete for space. It is this interplay of chemotaxis and competition for limited space that generates all the complex and biologically accurate behaviors described here. Thus, from a single simple mechanism that is well documented in the biological literature, we can explain both higher level structure and single cell movement behaviors. To our knowledge this is the first GC model that is able to recapitulate both correctly detailed anatomy and single cell movement. This mechanism may have wide application for modeling other biological systems where cells undergo complex patterns of movement to produce defined anatomical structures with sharp tissue boundaries.

Extracellular calcium controls the expression of two different forms of ripple-like hippocampal oscillations.

PubMed

Aivar, Paloma; Valero, Manuel; Bellistri, Elisa; Menendez de la Prida, Liset

2014-02-19

Hippocampal high-frequency oscillations (HFOs) are prominent in physiological and pathological conditions. During physiological ripples (100-200 Hz), few pyramidal cells fire together coordinated by rhythmic inhibitory potentials. In the epileptic hippocampus, fast ripples (>200 Hz) reflect population spikes (PSs) from clusters of bursting cells, but HFOs in the ripple and the fast ripple range are vastly intermixed. What is the meaning of this frequency range? What determines the expression of different HFOs? Here, we used different concentrations of Ca(2+) in a physiological range (1-3 mM) to record local field potentials and single cells in hippocampal slices from normal rats. Surprisingly, we found that this sole manipulation results in the emergence of two forms of HFOs reminiscent of ripples and fast ripples recorded in vivo from normal and epileptic rats, respectively. We scrutinized the cellular correlates and mechanisms underlying the emergence of these two forms of HFOs by combining multisite, single-cell and paired-cell recordings in slices prepared from a rat reporter line that facilitates identification of GABAergic cells. We found a major effect of extracellular Ca(2+) in modulating intrinsic excitability and disynaptic inhibition, two critical factors shaping network dynamics. Moreover, locally modulating the extracellular Ca(2+) concentration in an in vivo environment had a similar effect on disynaptic inhibition, pyramidal cell excitability, and ripple dynamics. Therefore, the HFO frequency band reflects a range of firing dynamics of hippocampal networks.

Controlling the Flow of Visual Information through the Lateral Geniculate Nucleus: From Single Cells to Neural Networks.

DTIC Science & Technology

1991-10-31

in my laboratory, Drs. Dan Kammen, Ernst Niebur and Florentin Worg6tter, as well as with three outside collaborators, Prof. John Kulli from the...also for experimentally observed cortical column structures ( Niebur and Worg6tter, 1990a,b). Temporal Dynamics of Interacting Neuronal Populations We...Connection Machine to simulate a 128 by 128 grid of 16,384 cells under a variety of stimulation patterns ( Niebur , Kammen & Koch, 1991). To explore

Meninges harbor cells expressing neural precursor markers during development and adulthood.

PubMed

Bifari, Francesco; Berton, Valeria; Pino, Annachiara; Kusalo, Marijana; Malpeli, Giorgio; Di Chio, Marzia; Bersan, Emanuela; Amato, Eliana; Scarpa, Aldo; Krampera, Mauro; Fumagalli, Guido; Decimo, Ilaria

2015-01-01

Brain and skull developments are tightly synchronized, allowing the cranial bones to dynamically adapt to the brain shape. At the brain-skull interface, meninges produce the trophic signals necessary for normal corticogenesis and bone development. Meninges harbor different cell populations, including cells forming the endosteum of the cranial vault. Recently, we and other groups have described the presence in meninges of a cell population endowed with neural differentiation potential in vitro and, after transplantation, in vivo. However, whether meninges may be a niche for neural progenitor cells during embryonic development and in adulthood remains to be determined. In this work we provide the first description of the distribution of neural precursor markers in rat meninges during development up to adulthood. We conclude that meninges share common properties with the classical neural stem cell niche, as they: (i) are a highly proliferating tissue; (ii) host cells expressing neural precursor markers such as nestin, vimentin, Sox2 and doublecortin; and (iii) are enriched in extracellular matrix components (e.g., fractones) known to bind and concentrate growth factors. This study underlines the importance of meninges as a potential niche for endogenous precursor cells during development and in adulthood.

Meninges harbor cells expressing neural precursor markers during development and adulthood

PubMed Central

Bifari, Francesco; Berton, Valeria; Pino, Annachiara; Kusalo, Marijana; Malpeli, Giorgio; Di Chio, Marzia; Bersan, Emanuela; Amato, Eliana; Scarpa, Aldo; Krampera, Mauro; Fumagalli, Guido; Decimo, Ilaria

2015-01-01

Brain and skull developments are tightly synchronized, allowing the cranial bones to dynamically adapt to the brain shape. At the brain-skull interface, meninges produce the trophic signals necessary for normal corticogenesis and bone development. Meninges harbor different cell populations, including cells forming the endosteum of the cranial vault. Recently, we and other groups have described the presence in meninges of a cell population endowed with neural differentiation potential in vitro and, after transplantation, in vivo. However, whether meninges may be a niche for neural progenitor cells during embryonic development and in adulthood remains to be determined. In this work we provide the first description of the distribution of neural precursor markers in rat meninges during development up to adulthood. We conclude that meninges share common properties with the classical neural stem cell niche, as they: (i) are a highly proliferating tissue; (ii) host cells expressing neural precursor markers such as nestin, vimentin, Sox2 and doublecortin; and (iii) are enriched in extracellular matrix components (e.g., fractones) known to bind and concentrate growth factors. This study underlines the importance of meninges as a potential niche for endogenous precursor cells during development and in adulthood. PMID:26483637

Connecting mechanics and bone cell activities in the bone remodeling process: an integrated finite element modeling.

PubMed

Hambli, Ridha

2014-01-01

Bone adaptation occurs as a response to external loadings and involves bone resorption by osteoclasts followed by the formation of new bone by osteoblasts. It is directly triggered by the transduction phase by osteocytes embedded within the bone matrix. The bone remodeling process is governed by the interactions between osteoblasts and osteoclasts through the expression of several autocrine and paracrine factors that control bone cell populations and their relative rate of differentiation and proliferation. A review of the literature shows that despite the progress in bone remodeling simulation using the finite element (FE) method, there is still a lack of predictive models that explicitly consider the interaction between osteoblasts and osteoclasts combined with the mechanical response of bone. The current study attempts to develop an FE model to describe the bone remodeling process, taking into consideration the activities of osteoclasts and osteoblasts. The mechanical behavior of bone is described by taking into account the bone material fatigue damage accumulation and mineralization. A coupled strain-damage stimulus function is proposed, which controls the level of autocrine and paracrine factors. The cellular behavior is based on Komarova et al.'s (2003) dynamic law, which describes the autocrine and paracrine interactions between osteoblasts and osteoclasts and computes cell population dynamics and changes in bone mass at a discrete site of bone remodeling. Therefore, when an external mechanical stress is applied, bone formation and resorption is governed by cells dynamic rather than adaptive elasticity approaches. The proposed FE model has been implemented in the FE code Abaqus (UMAT routine). An example of human proximal femur is investigated using the model developed. The model was able to predict final human proximal femur adaptation similar to the patterns observed in a human proximal femur. The results obtained reveal complex spatio-temporal bone adaptation. The proposed FEM model gives insight into how bone cells adapt their architecture to the mechanical and biological environment.

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.

Nondestructive nanostraw intracellular sampling for longitudinal cell monitoring

PubMed Central

Cao, Yuhong; Chen, Haodong; Birey, Fikri; Leal-Ortiz, Sergio A.; Han, Crystal M.; Santiago, Juan G.; Paşca, Sergiu P.; Wu, Joseph C.; Melosh, Nicholas A.

2017-01-01

Here, we report a method for time-resolved, longitudinal extraction and quantitative measurement of intracellular proteins and mRNA from a variety of cell types. Cytosolic contents were repeatedly sampled from the same cell or population of cells for more than 5 d through a cell-culture substrate, incorporating hollow 150-nm-diameter nanostraws (NS) within a defined sampling region. Once extracted, the cellular contents were analyzed with conventional methods, including fluorescence, enzymatic assays (ELISA), and quantitative real-time PCR. This process was nondestructive with >95% cell viability after sampling, enabling long-term analysis. It is important to note that the measured quantities from the cell extract were found to constitute a statistically significant representation of the actual contents within the cells. Of 48 mRNA sequences analyzed from a population of cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs), 41 were accurately quantified. The NS platform samples from a select subpopulation of cells within a larger culture, allowing native cell-to-cell contact and communication even during vigorous activity such as cardiomyocyte beating. This platform was applied both to cell lines and to primary cells, including CHO cells, hiPSC-CMs, and human astrocytes derived in 3D cortical spheroids. By tracking the same cell or group of cells over time, this method offers an avenue to understand dynamic cell behavior, including processes such as induced pluripotency and differentiation. PMID:28223521

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.

Modulation of Temporal Precision in Thalamic Population Responses to Natural Visual Stimuli

PubMed Central

Desbordes, Gaëlle; Jin, Jianzhong; Alonso, Jose-Manuel; Stanley, Garrett B.

2010-01-01

Natural visual stimuli have highly structured spatial and temporal properties which influence the way visual information is encoded in the visual pathway. In response to natural scene stimuli, neurons in the lateral geniculate nucleus (LGN) are temporally precise – on a time scale of 10–25 ms – both within single cells and across cells within a population. This time scale, established by non stimulus-driven elements of neuronal firing, is significantly shorter than that of natural scenes, yet is critical for the neural representation of the spatial and temporal structure of the scene. Here, a generalized linear model (GLM) that combines stimulus-driven elements with spike-history dependence associated with intrinsic cellular dynamics is shown to predict the fine timing precision of LGN responses to natural scene stimuli, the corresponding correlation structure across nearby neurons in the population, and the continuous modulation of spike timing precision and latency across neurons. A single model captured the experimentally observed neural response, across different levels of contrasts and different classes of visual stimuli, through interactions between the stimulus correlation structure and the nonlinearity in spike generation and spike history dependence. Given the sensitivity of the thalamocortical synapse to closely timed spikes and the importance of fine timing precision for the faithful representation of natural scenes, the modulation of thalamic population timing over these time scales is likely important for cortical representations of the dynamic natural visual environment. PMID:21151356

Impacts of land cover data selection and trait parameterisation on dynamic modelling of species' range expansion.

PubMed

Heikkinen, Risto K; Bocedi, Greta; Kuussaari, Mikko; Heliölä, Janne; Leikola, Niko; Pöyry, Juha; Travis, Justin M J

2014-01-01

Dynamic models for range expansion provide a promising tool for assessing species' capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina) and one generalist (Issoria lathonia). Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity), with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning.

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach

PubMed Central

2014-01-01

Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease. PMID:24725804

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease.

[Establishment of fibroblast cell line and its biological characteristics in Matou goat].

PubMed

Li, Tianda; Liu, Chousheng; Wang, Zhigang; Zhang, Liping; Sun, Xiuzhu; Zhao, Junjin; Meng, Fei; Luo, Guihe; Zhu, Jinqing

2008-12-01

Taking Matou goat ear margin as the study material, we succeeded in established a fibroblast cell line by the method of explant culture directly. Observations on morphology, dynamic growth, determination of viability, analysis of karyotype, test of microorganism and other characteristics were detected. Results showed: Population Doubling Time (PDT) of cells was approximately 36 h; Cell viability was 96.7% after thawing; The status of cell After passage was constant; Analysis of chromosomal karyotyps indicated that diploid (2n=60) account for 98% in the cell line. Every index in the cell line met all the standard quality controls of ATCC in USA. The established of Matou goat ear fibroblast cell line has not only important genetic resources preserved at the cell level, but also valuable material for genome, postgenome and somatic cell nuclear transfer research.

Single-Cell and Single-Molecule Analysis of Gene Expression Regulation.

PubMed

Vera, Maria; Biswas, Jeetayu; Senecal, Adrien; Singer, Robert H; Park, Hye Yoon

2016-11-23

Recent advancements in single-cell and single-molecule imaging technologies have resolved biological processes in time and space that are fundamental to understanding the regulation of gene expression. Observations of single-molecule events in their cellular context have revealed highly dynamic aspects of transcriptional and post-transcriptional control in eukaryotic cells. This approach can relate transcription with mRNA abundance and lifetimes. Another key aspect of single-cell analysis is the cell-to-cell variability among populations of cells. Definition of heterogeneity has revealed stochastic processes, determined characteristics of under-represented cell types or transitional states, and integrated cellular behaviors in the context of multicellular organisms. In this review, we discuss novel aspects of gene expression of eukaryotic cells and multicellular organisms revealed by the latest advances in single-cell and single-molecule imaging technology.

Population dynamics of hydrocarbon-oxidizing yeasts introduced into oil-contaminated soils

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

Kulichevskaya, I.S.; Panikov, N.S.; Guzev, V.S.

A pure culture of the yeastlike fungus Candida lipolytica, able to actively degrade crude oil, was isolated. In preliminary trials, an optimal dose for its introduction was adjusted (10{sup 8} cells/g soil) to ensure its predominance in contaminated soil. Laboratory incubation experiments in which the population dynamics of the introduced species and indigenous soil bacteria and the dynamics of soil respiration activity were followed showed that active proliferation of the introduced species in soil is accompanied by its elimination as a result of grazing by microfauna. The most favorable conditions for the development of introduced yeasts were found to bemore » provided in gray and gray forest soil, whereas in soddy-podzolic soil, their growth and oil degradation were retarded. The obtained results indicate that introduction of the tested culture can significantly increase the rate of oil degradation. In uncontaminated soil, the introduced species is rapidly eliminated. 9 refs., 5 figs.« less

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.

Extracellular Electrophysiological Measurements of Cooperative Signals in Astrocytes Populations

PubMed Central

Mestre, Ana L. G.; Inácio, Pedro M. C.; Elamine, Youssef; Asgarifar, Sanaz; Lourenço, Ana S.; Cristiano, Maria L. S.; Aguiar, Paulo; Medeiros, Maria C. R.; Araújo, Inês M.; Ventura, João; Gomes, Henrique L.

2017-01-01

Astrocytes are neuroglial cells that exhibit functional electrical properties sensitive to neuronal activity and capable of modulating neurotransmission. Thus, electrophysiological recordings of astroglial activity are very attractive to study the dynamics of glial signaling. This contribution reports on the use of ultra-sensitive planar electrodes combined with low noise and low frequency amplifiers that enable the detection of extracellular signals produced by primary cultures of astrocytes isolated from mouse cerebral cortex. Recorded activity is characterized by spontaneous bursts comprised of discrete signals with pronounced changes on the signal rate and amplitude. Weak and sporadic signals become synchronized and evolve with time to higher amplitude signals with a quasi-periodic behavior, revealing a cooperative signaling process. The methodology presented herewith enables the study of ionic fluctuations of population of cells, complementing the single cells observation by calcium imaging as well as by patch-clamp techniques. PMID:29109679

Macroenvironmental regulation of hair cycling and collective regenerative behavior.

PubMed

Plikus, Maksim V; Chuong, Cheng-Ming

2014-01-01

The hair follicle (HF) regeneration paradigm provides a unique opportunity for studying the collective behavior of stem cells in living animals. Activation of HF stem cells depends on the core inhibitory BMP and activating WNT signals operating within the HF microenvironment. Additionally, HFs receive multilayered signaling inputs from the extrafollicular macroenvironment, which includes dermis, adipocytes, neighboring HFs, hormones, and external stimuli. These activators/inhibitors are integrated across multiple stem-cell niches to produce dynamic hair growth patterns. Because of their pigmentation, these patterns can be easily studied on live shaved animals. Comparing to autonomous regeneration of one HF, populations of HFs display coupled decision making, allowing for more robust and adaptable regenerative behavior to occur collectively. The generic cellular automata model used to simulate coordinated HF cycling here can be extended to study population-level behavior of other complex biological systems made of cycling elements.

Macroenvironmental Regulation of Hair Cycling and Collective Regenerative Behavior

PubMed Central

Plikus, Maksim V.; Chuong, Cheng-Ming

2014-01-01

The hair follicle (HF) regeneration paradigm provides a unique opportunity for studying the collective behavior of stem cells in living animals. Activation of HF stem cells depends on the core inhibitory BMP and activating WNT signals operating within the HF microenvironment. Additionally, HFs receive multilayered signaling inputs from the extrafollicular macroenvironment, which includes dermis, adipocytes, neighboring HFs, hormones, and external stimuli. These activators/inhibitors are integrated across multiple stem-cell niches to produce dynamic hair growth patterns. Because of their pigmentation, these patterns can be easily studied on live shaved animals. Comparing to autonomous regeneration of one HF, populations of HFs display coupled decision making, allowing for more robust and adaptable regenerative behavior to occur collectively. The generic cellular automata model used to simulate coordinated HF cycling here can be extended to study population-level behavior of other complex biological systems made of cycling elements. PMID:24384813

Extracellular Electrophysiological Measurements of Cooperative Signals in Astrocytes Populations.

PubMed

Mestre, Ana L G; Inácio, Pedro M C; Elamine, Youssef; Asgarifar, Sanaz; Lourenço, Ana S; Cristiano, Maria L S; Aguiar, Paulo; Medeiros, Maria C R; Araújo, Inês M; Ventura, João; Gomes, Henrique L

2017-01-01

Astrocytes are neuroglial cells that exhibit functional electrical properties sensitive to neuronal activity and capable of modulating neurotransmission. Thus, electrophysiological recordings of astroglial activity are very attractive to study the dynamics of glial signaling. This contribution reports on the use of ultra-sensitive planar electrodes combined with low noise and low frequency amplifiers that enable the detection of extracellular signals produced by primary cultures of astrocytes isolated from mouse cerebral cortex. Recorded activity is characterized by spontaneous bursts comprised of discrete signals with pronounced changes on the signal rate and amplitude. Weak and sporadic signals become synchronized and evolve with time to higher amplitude signals with a quasi-periodic behavior, revealing a cooperative signaling process. The methodology presented herewith enables the study of ionic fluctuations of population of cells, complementing the single cells observation by calcium imaging as well as by patch-clamp techniques.

Recording High Resolution 3D Lagrangian Motions In Marine Dinoflagellates using Digital Holographic Microscopic Cinematography

NASA Astrophysics Data System (ADS)

Sheng, J.; Malkiel, E.; Katz, J.; Place, A. R.; Belas, R.

2006-11-01

Detailed data on swimming behavior and locomotion for dense population of dinoflagellates constitutes a key component to understanding cell migration, cell-cell interactions and predator-prey dynamics, all of which affect algae bloom dynamics. Due to the multi-dimensional nature of flagellated cell motions, spatial-temporal Lagrangian measurements of multiple cells in high concentration are very limited. Here we present detailed data on 3D Lagrangian motions for three marine dinoflagellates: Oxyrrhis marina, Karlodinium veneficum, and Pfiesteria piscicida, using digital holographic microscopic cinematography. The measurements are performed in a 5x5x25mm cuvette with cell densities varying from 50,000 ˜ 90,000 cells/ml. Approximately 200-500 cells are tracked simultaneously for 12s at 60fps in a sample volume of 1x1x5 mm at a spatial resolution of 0.4x0.4x2 μm. We fully resolve the longitudinal flagella (˜200nm) along with the Lagrangian trajectory of each organism. Species dependent swimming behavior are identified and categorized quantitatively by velocities, radii of curvature, and rotations of pitch. Statistics on locomotion, temporal & spatial scales, and diffusion rate show substantial differences between species. The scaling between turning radius and cell dimension can be explained by a distributed stokeslet model for a self-propelled body.

Environmental stress speeds up DNA replication in Pseudomonas putida in chemostat cultivations.

PubMed

Lieder, Sarah; Jahn, Michael; Koepff, Joachim; Müller, Susann; Takors, Ralf

2016-01-01

Cellular response to different types of stress is the hallmark of the cell's strategy for survival. How organisms adjust their cell cycle dynamics to compensate for changes in environmental conditions is an important unanswered question in bacterial physiology. A cell using binary fission for reproduction passes through three stages during its cell cycle: a stage from cell birth to initiation of replication, a DNA replication phase and a period of cell division. We present a detailed analysis of durations of cell cycle phases, investigating their dynamics under environmental stress conditions. Applying continuous steady state cultivations (chemostats), the DNA content of a Pseudomonas putida KT2440 population was quantified with flow cytometry at distinct growth rates. Data-driven modeling revealed that under stress conditions, such as oxygen deprivation, solvent exposure and decreased iron availability, DNA replication was accelerated correlated to the severity of the imposed stress (up to 1.9-fold). Cells maintained constant growth rates by balancing the shortened replication phase with extended cell cycle phases before and after replication. Transcriptome data underpin the transcriptional upregulation of crucial genes of the replication machinery. Hence adaption of DNA replication speed appears to be an important strategy to withstand environmental stress. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Task-phase-specific dynamics of basal forebrain neuronal ensembles

PubMed Central

Tingley, David; Alexander, Andrew S.; Kolbu, Sean; de Sa, Virginia R.; Chiba, Andrea A.; Nitz, Douglas A.

2014-01-01

Cortically projecting basal forebrain neurons play a critical role in learning and attention, and their degeneration accompanies age-related impairments in cognition. Despite the impressive anatomical and cell-type complexity of this system, currently available data suggest that basal forebrain neurons lack complexity in their response fields, with activity primarily reflecting only macro-level brain states such as sleep and wake, onset of relevant stimuli and/or reward obtainment. The current study examined the spiking activity of basal forebrain neuron populations across multiple phases of a selective attention task, addressing, in particular, the issue of complexity in ensemble firing patterns across time. Clustering techniques applied to the full population revealed a large number of distinct categories of task-phase-specific activity patterns. Unique population firing-rate vectors defined each task phase and most categories of task-phase-specific firing had counterparts with opposing firing patterns. An analogous set of task-phase-specific firing patterns was also observed in a population of posterior parietal cortex neurons. Thus, consistent with the known anatomical complexity, basal forebrain population dynamics are capable of differentially modulating their cortical targets according to the unique sets of environmental stimuli, motor requirements, and cognitive processes associated with different task phases. PMID:25309352

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.

Tumor-associated myeloid cells as guiding forces of cancer cell stemness.

PubMed

Sica, Antonio; Porta, Chiara; Amadori, Alberto; Pastò, Anna

2017-08-01

Due to their ability to differentiate into various cell types and to support tissue regeneration, stem cells simultaneously became the holy grail of regenerative medicine and the evil obstacle in cancer therapy. Several studies have investigated niche-related conditions that favor stemness properties and increasingly emphasized their association with an inflammatory environment. Tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs) are major orchestrators of cancer-related inflammation, able to dynamically express different polarized inflammatory programs that promote tumor outgrowth, including tumor angiogenesis, immunosuppression, tissue remodeling and metastasis formation. In addition, these myeloid populations support cancer cell stemness, favoring tumor maintenance and progression, as well as resistance to anticancer treatments. Here, we discuss inflammatory circuits and molecules expressed by TAMs and MDSCs as guiding forces of cancer cell stemness.

Density-dependence as a size-independent regulatory mechanism.

PubMed

de Vladar, Harold P

2006-01-21

The growth function of populations is central in biomathematics. The main dogma is the existence of density-dependence mechanisms, which can be modelled with distinct functional forms that depend on the size of the population. One important class of regulatory functions is the theta-logistic, which generalizes the logistic equation. Using this model as a motivation, this paper introduces a simple dynamical reformulation that generalizes many growth functions. The reformulation consists of two equations, one for population size, and one for the growth rate. Furthermore, the model shows that although population is density-dependent, the dynamics of the growth rate does not depend either on population size, nor on the carrying capacity. Actually, the growth equation is uncoupled from the population size equation, and the model has only two parameters, a Malthusian parameter rho and a competition coefficient theta. Distinct sign combinations of these parameters reproduce not only the family of theta-logistics, but also the van Bertalanffy, Gompertz and Potential Growth equations, among other possibilities. It is also shown that, except for two critical points, there is a general size-scaling relation that includes those appearing in the most important allometric theories, including the recently proposed Metabolic Theory of Ecology. With this model, several issues of general interest are discussed such as the growth of animal population, extinctions, cell growth and allometry, and the effect of environment over a population.

The organized melee: Emergence of collective behavior in concentrated suspensions of swimming bacteria and associated phenomena

NASA Astrophysics Data System (ADS)

Cisneros Salerno, Luis

Suspensions of the aerobic bacteria Bacilus subtilis develop patterns and flows from the interplay of motility, chemotaxis and buoyancy. In sessile drops, such bioconvectively driven flows carry plumes down the slanted meniscus and concentrate cells at the drop edge, while in pendant drops such self-concentration occurs at the bottom. These dynamics are explained quantitatively by a mathematical model consisting of oxygen diffusion and consumption, chemotaxis, and viscous fluid dynamics. Concentrated regions in both geometries comprise nearly close-packed populations, forming the collective "Zooming BioNematic" (ZBN) phase. This state exhibits large-scale orientational coherence, analogous to the molecular alignment of nematic liquid crystals, coupled with remarkable spatial and temporal correlations of velocity and vorticity, as measured by both novel and standard applications of particle imaging velocimetry. To probe mechanisms leading to this phase, response of individual cells to steric stress was explored, finding that they can reverse swimming direction at spatial constrictions without turning the cell body. The consequences of this propensity to flip the flagella are quantified, showing that "forwards" and "backwards" motion are dynamically and morphologically indistinguishable. Finally, experiments and mathematical modeling show that complex flows driven by previously unknown bipolar flagellar arrangements are induced when B. subtilis are confined in a thin layer of fluid, between asymmetric boundaries. The resulting driven flow circulates around the cell body ranging over several cell diameters, in contrast to the more localized flows surrounding free swimmers. This discovery extends our knowledge of the dynamic geometry of bacteria and their flagella, and reveals new mechanisms for motility-associated molecular transport and intercellular communication.

Bacterial charity work leads to population-wide resistance.

PubMed

Lee, Henry H; Molla, Michael N; Cantor, Charles R; Collins, James J

2010-09-02

Bacteria show remarkable adaptability in the face of antibiotic therapeutics. Resistance alleles in drug target-specific sites and general stress responses have been identified in individual end-point isolates. Less is known, however, about the population dynamics during the development of antibiotic-resistant strains. Here we follow a continuous culture of Escherichia coli facing increasing levels of antibiotic and show that the vast majority of isolates are less resistant than the population as a whole. We find that the few highly resistant mutants improve the survival of the population's less resistant constituents, in part by producing indole, a signalling molecule generated by actively growing, unstressed cells. We show, through transcriptional profiling, that indole serves to turn on drug efflux pumps and oxidative-stress protective mechanisms. The indole production comes at a fitness cost to the highly resistant isolates, and whole-genome sequencing reveals that this bacterial altruism is made possible by drug-resistance mutations unrelated to indole production. This work establishes a population-based resistance mechanism constituting a form of kin selection whereby a small number of resistant mutants can, at some cost to themselves, provide protection to other, more vulnerable, cells, enhancing the survival capacity of the overall population in stressful environments.

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

B-cell development and pneumococcal immunity in vertically acquired HIV infection.

PubMed

Eisen, Sarah; Hayden, Clare; Young, Carmel J; Gilson, Richard; Jungmann, Eva; Jacobsen, Marianne C; Poulsom, Hannah; Goldblatt, David; Klein, Nigel J; Baxendale, Helen E

2016-07-31

Many children with HIV infection now survive into adulthood. This study explored the impact of vertically acquired HIV in the era of antiretroviral therapy on the development of humoral immunity. Natural and vaccine-related immunity to pneumococcus and B-cell phenotype was characterized and compared in three groups of young adults: those with vertically-acquired infection, those with horizontally acquired infection and healthy controls. Serotype-specific pneumococcal (Pnc) immunoglobulin M and G concentrations before and up to 1 year post-Pnc polysaccharide (Pneumovax) immunization were determined, and opsonophagocytic activity was analysed. B-cell subpopulations and dynamic markers of B-cell signalling, turnover and susceptibility to apoptosis were evaluated by flow cytometry. HIV-infected patients showed impaired natural Pnc immunity and reduced humoral responses to immunization with Pneumovax; this was greatest in those viraemic at time of the study. Early-life viral control before the age of 10 years diminished these changes. Expanded populations of abnormally activated and immature B-cells were seen in both HIV-infected cohorts. Vertically infected patients were particularly vulnerable to reductions in marginal zone and switched memory populations. These aberrations were reduced in patients with early-life viral control. In children with HIV, damage to B-cell memory populations and impaired natural and vaccine immunity to pneumococcus is evident in early adult life. Sustained viral control from early childhood may help to limit this effect and optimize humoral immunity in adult life.

Population dynamics and in vitro antibody pressure of porcine parvovirus indicate a decrease in variability.

PubMed

Streck, André Felipe; Homeier, Timo; Foerster, Tessa; Truyen, Uwe

2013-09-01

To estimate the impact of porcine parvovirus (PPV) vaccines on the emergence of new phenotypes, the population dynamic history of the virus was calculated using the Bayesian Markov chain Monte Carlo method with a Bayesian skyline coalescent model. Additionally, an in vitro model was performed with consecutive passages of the 'Challenge' strain (a virulent field strain) and NADL2 strain (a vaccine strain) in a PK-15 cell line supplemented with polyclonal antibodies raised against the vaccine strain. A decrease in genetic diversity was observed in the presence of antibodies in vitro or after vaccination (as estimated by the in silico model). We hypothesized that the antibodies induced a selective pressure that may reduce the incidence of neutral selection, which should play a major role in the emergence of new mutations. In this scenario, vaccine failures and non-vaccinated populations (e.g. wild boars) may have an important impact in the emergence of new phenotypes.

A Multi-Paradigm Modeling Framework to Simulate Dynamic Reciprocity in a Bioreactor

PubMed Central

Kaul, Himanshu; Cui, Zhanfeng; Ventikos, Yiannis

2013-01-01

Despite numerous technology advances, bioreactors are still mostly utilized as functional black-boxes where trial and error eventually leads to the desirable cellular outcome. Investigators have applied various computational approaches to understand the impact the internal dynamics of such devices has on overall cell growth, but such models cannot provide a comprehensive perspective regarding the system dynamics, due to limitations inherent to the underlying approaches. In this study, a novel multi-paradigm modeling platform capable of simulating the dynamic bidirectional relationship between cells and their microenvironment is presented. Designing the modeling platform entailed combining and coupling fully an agent-based modeling platform with a transport phenomena computational modeling framework. To demonstrate capability, the platform was used to study the impact of bioreactor parameters on the overall cell population behavior and vice versa. In order to achieve this, virtual bioreactors were constructed and seeded. The virtual cells, guided by a set of rules involving the simulated mass transport inside the bioreactor, as well as cell-related probabilistic parameters, were capable of displaying an array of behaviors such as proliferation, migration, chemotaxis and apoptosis. In this way the platform was shown to capture not only the impact of bioreactor transport processes on cellular behavior but also the influence that cellular activity wields on that very same local mass transport, thereby influencing overall cell growth. The platform was validated by simulating cellular chemotaxis in a virtual direct visualization chamber and comparing the simulation with its experimental analogue. The results presented in this paper are in agreement with published models of similar flavor. The modeling platform can be used as a concept selection tool to optimize bioreactor design specifications. PMID:23555740

The cell-stretcher: A novel device for the mechanical stimulation of cell populations

NASA Astrophysics Data System (ADS)

Seriani, S.; Del Favero, G.; Mahaffey, J.; Marko, D.; Gallina, P.; Long, C. S.; Mestroni, L.; Sbaizero, O.

2016-08-01

Mechanical stimulation appears to be a critical modulator for many aspects of biology, both of living tissue and cells. The cell-stretcher, a novel device for the mechanical uniaxial stimulation of populations of cells, is described. The system is based on a variable stroke cam-lever-tappet mechanism which allows the delivery of cyclic stimuli with frequencies of up to 10 Hz and deformation between 1% and 20%. The kinematics is presented and a simulation of the dynamics of the system is shown, in order to compute the contact forces in the mechanism. The cells, following cultivation and preparation, are plated on an ad hoc polydimethylsiloxane membrane which is then loaded on the clamps of the cell-stretcher via force-adjustable magnetic couplings. In order to show the viability of the experimentation and biocompatibility of the cell-stretcher, a set of two in vitro tests were performed. Human epithelial carcinoma cell line A431 and Adult Mouse Ventricular Fibroblasts (AMVFs) from a dual reporter mouse were subject to 0.5 Hz, 24 h cyclic stretching at 15% strain, and to 48 h stimulation at 0.5 Hz and 15% strain, respectively. Visual analysis was performed on A431, showing definite morphological changes in the form of cellular extroflections in the direction of stimulation compared to an unstimulated control. A cytometric analysis was performed on the AMVF population. Results show a post-stimulation live-dead ratio deviance of less than 6% compared to control, which proves that the environment created by the cell-stretcher is suitable for in vitro experimentation.

CD147 (Basigin/Emmprin) identifies FoxP3+CD45RO+CTLA4+-activated human regulatory T cells.

PubMed

Solstad, Therese; Bains, Simer Jit; Landskron, Johannes; Aandahl, Einar Martin; Thiede, Bernd; Taskén, Kjetil; Torgersen, Knut Martin

2011-11-10

Human CD4(+)FoxP3(+) T cells are functionally and phenotypically heterogeneous providing plasticity to immune activation and regulation. To better understand the functional dynamics within this subset, we first used a combined strategy of subcellular fractionation and proteomics to describe differences at the protein level between highly purified human CD4(+)CD25(+) and CD4(+)CD25(-) T-cell populations. This identified a set of membrane proteins highly expressed on the cell surface of human regulatory T cells (Tregs), including CD71, CD95, CD147, and CD148. CD147 (Basigin or Emmprin) divided CD4(+)CD25(+) cells into distinct subsets. Furthermore, CD147, CD25, FoxP3, and in particular CTLA-4 expression correlated. Phenotypical and functional analyses suggested that CD147 marks the switch between resting (CD45RA(+)) and activated (CD45RO(+)) subsets within the FoxP3(+) T-cell population. Sorting of regulatory T cells into CD147(-) and CD147(+) populations demonstrated that CD147 identifies an activated and highly suppressive CD45RO(+) Treg subset. When analyzing CD4(+) T cells for their cytokine producing potential, CD147 levels grouped the FoxP3(+) subset into 3 categories with different ability to produce IL-2, TNF-α, IFN-γ, and IL-17. Together, this suggests that CD147 is a direct marker for activated Tregs within the CD4(+)FoxP3(+) subset and may provide means to manipulate cells important for immune homeostasis.

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis

PubMed Central

Ji, Zhicheng; Ji, Hongkai

2016-01-01

When analyzing single-cell RNA-seq data, constructing a pseudo-temporal path to order cells based on the gradual transition of their transcriptomes is a useful way to study gene expression dynamics in a heterogeneous cell population. Currently, a limited number of computational tools are available for this task, and quantitative methods for comparing different tools are lacking. Tools for Single Cell Analysis (TSCAN) is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis. TSCAN uses a cluster-based minimum spanning tree (MST) approach to order cells. Cells are first grouped into clusters and an MST is then constructed to connect cluster centers. Pseudo-time is obtained by projecting each cell onto the tree, and the ordered sequence of cells can be used to study dynamic changes of gene expression along the pseudo-time. Clustering cells before MST construction reduces the complexity of the tree space. This often leads to improved cell ordering. It also allows users to conveniently adjust the ordering based on prior knowledge. TSCAN has a graphical user interface (GUI) to support data visualization and user interaction. Furthermore, quantitative measures are developed to objectively evaluate and compare different pseudo-time reconstruction methods. TSCAN is available at https://github.com/zji90/TSCAN and as a Bioconductor package. PMID:27179027

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis.

PubMed

Ji, Zhicheng; Ji, Hongkai

2016-07-27

When analyzing single-cell RNA-seq data, constructing a pseudo-temporal path to order cells based on the gradual transition of their transcriptomes is a useful way to study gene expression dynamics in a heterogeneous cell population. Currently, a limited number of computational tools are available for this task, and quantitative methods for comparing different tools are lacking. Tools for Single Cell Analysis (TSCAN) is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis. TSCAN uses a cluster-based minimum spanning tree (MST) approach to order cells. Cells are first grouped into clusters and an MST is then constructed to connect cluster centers. Pseudo-time is obtained by projecting each cell onto the tree, and the ordered sequence of cells can be used to study dynamic changes of gene expression along the pseudo-time. Clustering cells before MST construction reduces the complexity of the tree space. This often leads to improved cell ordering. It also allows users to conveniently adjust the ordering based on prior knowledge. TSCAN has a graphical user interface (GUI) to support data visualization and user interaction. Furthermore, quantitative measures are developed to objectively evaluate and compare different pseudo-time reconstruction methods. TSCAN is available at https://github.com/zji90/TSCAN and as a Bioconductor package. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Dynamic Bioreactor Culture of High Volume Engineered Bone Tissue

PubMed Central

Nguyen, Bao-Ngoc B.; Ko, Henry; Moriarty, Rebecca A.; Etheridge, Julie M.

2016-01-01

Within the field of tissue engineering and regenerative medicine, the fabrication of tissue grafts of any significant size—much less a whole organ or tissue—remains a major challenge. Currently, tissue-engineered constructs cultured in vitro have been restrained in size primarily due to the diffusion limit of oxygen and nutrients to the center of these grafts. Previously, we developed a novel tubular perfusion system (TPS) bioreactor, which allows the dynamic culture of bead-encapsulated cells and increases the supply of nutrients to the entire cell population. More interestingly, the versatility of TPS bioreactor allows a large range of engineered tissue volumes to be cultured, including large bone grafts. In this study, we utilized alginate-encapsulated human mesenchymal stem cells for the culture of a tissue-engineered bone construct in the size and shape of the superior half of an adult human femur (∼200 cm3), a 20-fold increase over previously reported volumes of in vitro engineered bone grafts. Dynamic culture in TPS bioreactor not only resulted in high cell viability throughout the femur graft, but also showed early signs of stem cell differentiation through increased expression of osteogenic genes and proteins, consistent with our previous models of smaller bone constructs. This first foray into full-scale bone engineering provides the foundation for future clinical applications of bioengineered bone grafts. PMID:26653703

Myosin-II sets the optimal response time scale of chemotactic amoeba

NASA Astrophysics Data System (ADS)

Hsu, Hsin-Fang; Westendorf, Christian; Tarantola, Marco; Bodenschatz, Eberhard; Beta, Carsten

2014-03-01

The response dynamics of the actin cytoskeleton to external chemical stimuli plays a fundamental role in numerous cellular functions. One of the key players that governs the dynamics of the actin network is the motor protein myosin-II. Here we investigate the role of myosin-II in the response of the actin system to external stimuli. We used a microfluidic device in combination with a photoactivatable chemoattractant to apply stimuli to individual cells with high temporal resolution. We directly compare the actin dynamics in Dictyostelium discodelium wild type (WT) cells to a knockout mutant that is deficient in myosin-II (MNL). Similar to the WT a small population of MNL cells showed self-sustained oscillations even in absence of external stimuli. The actin response of MNL cells to a short pulse of chemoattractant resembles WT during the first 15 sec but is significantly delayed afterward. The amplitude of the dominant peak in the power spectrum from the response time series of MNL cells to periodic stimuli with varying period showed a clear resonance peak at a forcing period of 36 sec, which is significantly delayed as compared to the resonance at 20 sec found for the WT. This shift indicates an important role of myosin-II in setting the response time scale of motile amoeba. Institute of Physics und Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, 14476 Potsdam, Germany.

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.