DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity

PubMed Central

Anchang, Benedict; Davis, Kara L.; Fienberg, Harris G.; Bendall, Sean C.; Karacosta, Loukia G.; Tibshirani, Robert; Nolan, Garry P.; Plevritis, Sylvia K.

2018-01-01

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple (>40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples. PMID:29654148

Using single cell sequencing data to model the evolutionary history of a tumor.

PubMed

Kim, Kyung In; Simon, Richard

2014-01-24

The introduction of next-generation sequencing (NGS) technology has made it possible to detect genomic alterations within tumor cells on a large scale. However, most applications of NGS show the genetic content of mixtures of cells. Recently developed single cell sequencing technology can identify variation within a single cell. Characterization of multiple samples from a tumor using single cell sequencing can potentially provide information on the evolutionary history of that tumor. This may facilitate understanding how key mutations accumulate and evolve in lineages to form a heterogeneous tumor. We provide a computational method to infer an evolutionary mutation tree based on single cell sequencing data. Our approach differs from traditional phylogenetic tree approaches in that our mutation tree directly describes temporal order relationships among mutation sites. Our method also accommodates sequencing errors. Furthermore, we provide a method for estimating the proportion of time from the earliest mutation event of the sample to the most recent common ancestor of the sample of cells. Finally, we discuss current limitations on modeling with single cell sequencing data and possible improvements under those limitations. Inferring the temporal ordering of mutational sites using current single cell sequencing data is a challenge. Our proposed method may help elucidate relationships among key mutations and their role in tumor progression.

DIMM-SC: a Dirichlet mixture model for clustering droplet-based single cell transcriptomic data.

PubMed

Sun, Zhe; Wang, Ting; Deng, Ke; Wang, Xiao-Feng; Lafyatis, Robert; Ding, Ying; Hu, Ming; Chen, Wei

2018-01-01

Single cell transcriptome sequencing (scRNA-Seq) has become a revolutionary tool to study cellular and molecular processes at single cell resolution. Among existing technologies, the recently developed droplet-based platform enables efficient parallel processing of thousands of single cells with direct counting of transcript copies using Unique Molecular Identifier (UMI). Despite the technology advances, statistical methods and computational tools are still lacking for analyzing droplet-based scRNA-Seq data. Particularly, model-based approaches for clustering large-scale single cell transcriptomic data are still under-explored. We developed DIMM-SC, a Dirichlet Mixture Model for clustering droplet-based Single Cell transcriptomic data. This approach explicitly models UMI count data from scRNA-Seq experiments and characterizes variations across different cell clusters via a Dirichlet mixture prior. We performed comprehensive simulations to evaluate DIMM-SC and compared it with existing clustering methods such as K-means, CellTree and Seurat. In addition, we analyzed public scRNA-Seq datasets with known cluster labels and in-house scRNA-Seq datasets from a study of systemic sclerosis with prior biological knowledge to benchmark and validate DIMM-SC. Both simulation studies and real data applications demonstrated that overall, DIMM-SC achieves substantially improved clustering accuracy and much lower clustering variability compared to other existing clustering methods. More importantly, as a model-based approach, DIMM-SC is able to quantify the clustering uncertainty for each single cell, facilitating rigorous statistical inference and biological interpretations, which are typically unavailable from existing clustering methods. DIMM-SC has been implemented in a user-friendly R package with a detailed tutorial available on www.pitt.edu/∼wec47/singlecell.html. wei.chen@chp.edu or hum@ccf.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Digital Quantification of Proteins and mRNA in Single Mammalian Cells.

PubMed

Albayrak, Cem; Jordi, Christian A; Zechner, Christoph; Lin, Jing; Bichsel, Colette A; Khammash, Mustafa; Tay, Savaş

2016-03-17

Absolute quantification of macromolecules in single cells is critical for understanding and modeling biological systems that feature cellular heterogeneity. Here we show extremely sensitive and absolute quantification of both proteins and mRNA in single mammalian cells by a very practical workflow that combines proximity ligation assay (PLA) and digital PCR. This digital PLA method has femtomolar sensitivity, which enables the quantification of very small protein concentration changes over its entire 3-log dynamic range, a quality necessary for accounting for single-cell heterogeneity. We counted both endogenous (CD147) and exogenously expressed (GFP-p65) proteins from hundreds of single cells and determined the correlation between CD147 mRNA and the protein it encodes. Using our data, a stochastic two-state model of the central dogma was constructed and verified using joint mRNA/protein distributions, allowing us to estimate transcription burst sizes and extrinsic noise strength and calculate the transcription and translation rate constants in single mammalian cells. Copyright © 2016 Elsevier Inc. All rights reserved.

Potentials of single-cell biology in identification and validation of disease biomarkers.

PubMed

Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong

2016-09-01

Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Model-based branching point detection in single-cell data by K-branches clustering

PubMed Central

Chlis, Nikolaos K.; Wolf, F. Alexander; Theis, Fabian J.

2017-01-01

Abstract Motivation The identification of heterogeneities in cell populations by utilizing single-cell technologies such as single-cell RNA-Seq, enables inference of cellular development and lineage trees. Several methods have been proposed for such inference from high-dimensional single-cell data. They typically assign each cell to a branch in a differentiation trajectory. However, they commonly assume specific geometries such as tree-like developmental hierarchies and lack statistically sound methods to decide on the number of branching events. Results We present K-Branches, a solution to the above problem by locally fitting half-lines to single-cell data, introducing a clustering algorithm similar to K-Means. These halflines are proxies for branches in the differentiation trajectory of cells. We propose a modified version of the GAP statistic for model selection, in order to decide on the number of lines that best describe the data locally. In this manner, we identify the location and number of subgroups of cells that are associated with branching events and full differentiation, respectively. We evaluate the performance of our method on single-cell RNA-Seq data describing the differentiation of myeloid progenitors during hematopoiesis, single-cell qPCR data of mouse blastocyst development, single-cell qPCR data of human myeloid monocytic leukemia and artificial data. Availability and implementation An R implementation of K-Branches is freely available at https://github.com/theislab/kbranches. Contact fabian.theis@helmholtz-muenchen.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:28582478

Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data.

PubMed

Chen, Shuonan; Mar, Jessica C

2018-06-19

A fundamental fact in biology states that genes do not operate in isolation, and yet, methods that infer regulatory networks for single cell gene expression data have been slow to emerge. With single cell sequencing methods now becoming accessible, general network inference algorithms that were initially developed for data collected from bulk samples may not be suitable for single cells. Meanwhile, although methods that are specific for single cell data are now emerging, whether they have improved performance over general methods is unknown. In this study, we evaluate the applicability of five general methods and three single cell methods for inferring gene regulatory networks from both experimental single cell gene expression data and in silico simulated data. Standard evaluation metrics using ROC curves and Precision-Recall curves against reference sets sourced from the literature demonstrated that most of the methods performed poorly when they were applied to either experimental single cell data, or simulated single cell data, which demonstrates their lack of performance for this task. Using default settings, network methods were applied to the same datasets. Comparisons of the learned networks highlighted the uniqueness of some predicted edges for each method. The fact that different methods infer networks that vary substantially reflects the underlying mathematical rationale and assumptions that distinguish network methods from each other. This study provides a comprehensive evaluation of network modeling algorithms applied to experimental single cell gene expression data and in silico simulated datasets where the network structure is known. Comparisons demonstrate that most of these assessed network methods are not able to predict network structures from single cell expression data accurately, even if they are specifically developed for single cell methods. Also, single cell methods, which usually depend on more elaborative algorithms, in general have less similarity to each other in the sets of edges detected. The results from this study emphasize the importance for developing more accurate optimized network modeling methods that are compatible for single cell data. Newly-developed single cell methods may uniquely capture particular features of potential gene-gene relationships, and caution should be taken when we interpret these results.

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.

PubMed

Buettner, Florian; Natarajan, Kedar N; Casale, F Paolo; Proserpio, Valentina; Scialdone, Antonio; Theis, Fabian J; Teichmann, Sarah A; Marioni, John C; Stegle, Oliver

2015-02-01

Recent technical developments have enabled the transcriptomes of hundreds of cells to be assayed in an unbiased manner, opening up the possibility that new subpopulations of cells can be found. However, the effects of potential confounding factors, such as the cell cycle, on the heterogeneity of gene expression and therefore on the ability to robustly identify subpopulations remain unclear. We present and validate a computational approach that uses latent variable models to account for such hidden factors. We show that our single-cell latent variable model (scLVM) allows the identification of otherwise undetectable subpopulations of cells that correspond to different stages during the differentiation of naive T cells into T helper 2 cells. Our approach can be used not only to identify cellular subpopulations but also to tease apart different sources of gene expression heterogeneity in single-cell transcriptomes.

Development and characterization of hollow microprobe array as a potential tool for versatile and massively parallel manipulation of single cells.

PubMed

Nagai, Moeto; Oohara, Kiyotaka; Kato, Keita; Kawashima, Takahiro; Shibata, Takayuki

2015-04-01

Parallel manipulation of single cells is important for reconstructing in vivo cellular microenvironments and studying cell functions. To manipulate single cells and reconstruct their environments, development of a versatile manipulation tool is necessary. In this study, we developed an array of hollow probes using microelectromechanical systems fabrication technology and demonstrated the manipulation of single cells. We conducted a cell aspiration experiment with a glass pipette and modeled a cell using a standard linear solid model, which provided information for designing hollow stepped probes for minimally invasive single-cell manipulation. We etched a silicon wafer on both sides and formed through holes with stepped structures. The inner diameters of the holes were reduced by SiO2 deposition of plasma-enhanced chemical vapor deposition to trap cells on the tips. This fabrication process makes it possible to control the wall thickness, inner diameter, and outer diameter of the probes. With the fabricated probes, single cells were manipulated and placed in microwells at a single-cell level in a parallel manner. We studied the capture, release, and survival rates of cells at different suction and release pressures and found that the cell trapping rate was directly proportional to the suction pressure, whereas the release rate and viability decreased with increasing the suction pressure. The proposed manipulation system makes it possible to place cells in a well array and observe the adherence, spreading, culture, and death of the cells. This system has potential as a tool for massively parallel manipulation and for three-dimensional hetero cellular assays.

Interactions between airway epithelial cells and dendritic cells during viral infections using an in vitro co-culture model

EPA Science Inventory

Rationale: Historically, single cell culture models have been limited in pathological and physiological relevance. A co-culture model of dendritic cells (DCs) and differentiated human airway epithelial cells was developed to examine potential interactions between these two cell t...

A biochemically semi-detailed model of auxin-mediated vein formation in plant leaves.

PubMed

Roussel, Marc R; Slingerland, Martin J

2012-09-01

We present here a model intended to capture the biochemistry of vein formation in plant leaves. The model consists of three modules. Two of these modules, those describing auxin signaling and transport in plant cells, are biochemically detailed. We couple these modules to a simple model for PIN (auxin efflux carrier) protein localization based on an extracellular auxin sensor. We study the single-cell responses of this combined model in order to verify proper functioning of the modeled biochemical network. We then assemble a multicellular model from the single-cell building blocks. We find that the model can, under some conditions, generate files of polarized cells, but not true veins. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

In vivo imaging of T cell lymphoma infiltration process at the colon.

PubMed

Ueda, Yoshibumi; Ishiwata, Toshiyuki; Shinji, Seiichi; Arai, Tomio; Matsuda, Yoko; Aida, Junko; Sugimoto, Naotoshi; Okazaki, Toshiro; Kikuta, Junichi; Ishii, Masaru; Sato, Moritoshi

2018-03-05

The infiltration and proliferation of cancer cells in the secondary organs are of great interest, since they contribute to cancer metastasis. However, cancer cell dynamics in the secondary organs have not been elucidated at single-cell resolution. In the present study, we established an in vivo model using two-photon microscopy to observe how infiltrating cancer cells form assemblages from single T-cell lymphomas, EL4 cells, in the secondary organs. Using this model, after inoculation of EL4 cells in mice, we discovered that single EL4 cells infiltrated into the colon. In the early stage, sporadic elongated EL4 cells became lodged in small blood vessels. Real-time imaging revealed that, whereas more than 70% of EL4 cells did not move during a 1-hour observation, other EL4 cells irregularly moved even in small vessels and dynamically changed shape upon interacting with other cells. In the late stages, EL4 cells formed small nodules composed of several EL4 cells in blood vessels as well as crypts, suggesting the existence of diverse mechanisms of nodule formation. The present in vivo imaging system is instrumental to dissect cancer cell dynamics during metastasis in other organs at the single-cell level.

Statistical Modeling of Single Target Cell Encapsulation

PubMed Central

Moon, SangJun; Ceyhan, Elvan; Gurkan, Umut Atakan; Demirci, Utkan

2011-01-01

High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems. PMID:21814548

Correlated receptor transport processes buffer single-cell heterogeneity

PubMed Central

Kallenberger, Stefan M.; Unger, Anne L.; Legewie, Stefan; Lymperopoulos, Konstantinos; Eils, Roland

2017-01-01

Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system. PMID:28945754

Modeling of single event transients with dual double-exponential current sources: Implications for logic cell characterization

DOE PAGES

Black, Dolores Archuleta; Robinson, William H.; Wilcox, Ian Zachary; ...

2015-08-07

Single event effects (SEE) are a reliability concern for modern microelectronics. Bit corruptions can be caused by single event upsets (SEUs) in the storage cells or by sampling single event transients (SETs) from a logic path. Likewise, an accurate prediction of soft error susceptibility from SETs requires good models to convert collected charge into compact descriptions of the current injection process. This paper describes a simple, yet effective, method to model the current waveform resulting from a charge collection event for SET circuit simulations. The model uses two double-exponential current sources in parallel, and the results illustrate why a conventionalmore » model based on one double-exponential source can be incomplete. Furthermore, a small set of logic cells with varying input conditions, drive strength, and output loading are simulated to extract the parameters for the dual double-exponential current sources. As a result, the parameters are based upon both the node capacitance and the restoring current (i.e., drive strength) of the logic cell.« less

Single molecule microscopy in 3D cell cultures and tissues.

PubMed

Lauer, Florian M; Kaemmerer, Elke; Meckel, Tobias

2014-12-15

From the onset of the first microscopic visualization of single fluorescent molecules in living cells at the beginning of this century, to the present, almost routine application of single molecule microscopy, the method has well-proven its ability to contribute unmatched detailed insight into the heterogeneous and dynamic molecular world life is composed of. Except for investigations on bacteria and yeast, almost the entire story of success is based on studies on adherent mammalian 2D cell cultures. However, despite this continuous progress, the technique was not able to keep pace with the move of the cell biology community to adapt 3D cell culture models for basic research, regenerative medicine, or drug development and screening. In this review, we will summarize the progress, which only recently allowed for the application of single molecule microscopy to 3D cell systems and give an overview of the technical advances that led to it. While initially posing a challenge, we finally conclude that relevant 3D cell models will become an integral part of the on-going success of single molecule microscopy. Copyright © 2014 Elsevier B.V. All rights reserved.

Principles of a multistack electrochemical wastewater treatment design

NASA Astrophysics Data System (ADS)

Elsahwi, Essam S.; Dawson, Francis P.; Ruda, Harry E.

2018-02-01

Electrolyzer stacks in a bipolar architecture (cells connected in series) are desirable since power provided to a stack can be transferred at high voltages and low currents and thus the losses in the power bus can be reduced. The anode electrodes (active electrodes) considered as part of this study are single sided but there are manufacturing cost advantages to implementing double side anodes in the future. One of the main concerns with a bipolar stack implementation is the existence of leakage currents (bypass currents). The leakage current is associated with current paths that are not between adjacent anode and cathode pairs. This leads to non uniform current density distributions which compromise the electrochemical conversion efficiency of the stack and can also lead to unwanted side reactions. The objective of this paper is to develop modelling tools for a bipolar architecture consisting of two single sided cells that use single sided anodes. It is assumed that chemical reactions are single electron transfer rate limited and that diffusion and convection effects can be ignored. The design process consists of the flowing two steps: development of a large signal model for the stack, and then the extraction of a small signal model from the large signal model. The small signal model facilitates the design of a controller that satisfies current or voltage regulation requirements. A model has been developed for a single cell and two cells in series but can be generalized to more than two cells in series and to incorporate double sided anode configurations in the future. The developed model is able to determine the leakage current and thus provide a quantitative assessment on the performance of the cell.

Development of a facile droplet-based single-cell isolation platform for cultivation and genomic analysis in microorganisms.

PubMed

Zhang, Qiang; Wang, Tingting; Zhou, Qian; Zhang, Peng; Gong, Yanhai; Gou, Honglei; Xu, Jian; Ma, Bo

2017-01-23

Wider application of single-cell analysis has been limited by the lack of an easy-to-use and low-cost strategy for single-cell isolation that can be directly coupled to single-cell sequencing and single-cell cultivation, especially for small-size microbes. Herein, a facile droplet microfluidic platform was developed to dispense individual microbial cells into conventional standard containers for downstream analysis. Functional parts for cell encapsulation, droplet inspection and sorting, as well as a chip-to-tube capillary interface were integrated on one single chip with simple architecture, and control of the droplet sorting was achieved by a low-cost solenoid microvalve. Using microalgal and yeast cells as models, single-cell isolation success rate of over 90% and single-cell cultivation success rate of 80% were demonstrated. We further showed that the individual cells isolated can be used in high-quality DNA and RNA analyses at both gene-specific and whole-genome levels (i.e. real-time quantitative PCR and genome sequencing). The simplicity and reliability of the method should improve accessibility of single-cell analysis and facilitate its wider application in microbiology researches.

Development of a facile droplet-based single-cell isolation platform for cultivation and genomic analysis in microorganisms

PubMed Central

Zhang, Qiang; Wang, Tingting; Zhou, Qian; Zhang, Peng; Gong, Yanhai; Gou, Honglei; Xu, Jian; Ma, Bo

2017-01-01

Wider application of single-cell analysis has been limited by the lack of an easy-to-use and low-cost strategy for single-cell isolation that can be directly coupled to single-cell sequencing and single-cell cultivation, especially for small-size microbes. Herein, a facile droplet microfluidic platform was developed to dispense individual microbial cells into conventional standard containers for downstream analysis. Functional parts for cell encapsulation, droplet inspection and sorting, as well as a chip-to-tube capillary interface were integrated on one single chip with simple architecture, and control of the droplet sorting was achieved by a low-cost solenoid microvalve. Using microalgal and yeast cells as models, single-cell isolation success rate of over 90% and single-cell cultivation success rate of 80% were demonstrated. We further showed that the individual cells isolated can be used in high-quality DNA and RNA analyses at both gene-specific and whole-genome levels (i.e. real-time quantitative PCR and genome sequencing). The simplicity and reliability of the method should improve accessibility of single-cell analysis and facilitate its wider application in microbiology researches. PMID:28112223

Modeling intrinsic electrophysiology of AII amacrine cells: preliminary results.

PubMed

Apollo, Nick; Grayden, David B; Burkitt, Anthony N; Meffin, Hamish; Kameneva, Tatiana

2013-01-01

In patients who have lost their photoreceptors due to retinal degenerative diseases, it is possible to restore rudimentary vision by electrically stimulating surviving neurons. AII amacrine cells, which reside in the inner plexiform layer, split the signal from rod bipolar cells into ON and OFF cone pathways. As a result, it is of interest to develop a computational model to aid in the understanding of how these cells respond to the electrical stimulation delivered by a prosthetic implant. The aim of this work is to develop and constrain parameters in a single-compartment model of an AII amacrine cell using data from whole-cell patch clamp recordings. This model will be used to explore responses of AII amacrine cells to electrical stimulation. Single-compartment Hodgkin-Huxley-type neural models are simulated in the NEURON environment. Simulations showed successful reproduction of the potassium currentvoltage relationship and some of the spiking properties observed in vitro.

An non-uniformity voltage model for proton exchange membrane fuel cell

NASA Astrophysics Data System (ADS)

Li, Kelei; Li, Yankun; Liu, Jiawei; Guo, Ai

2017-01-01

The fuel cell used in transportation has environmental protection, high efficiency and no line traction power system which can greatly reduce line construction investment. That makes it a huge potential. The voltage uniformity is one of the most important factors affecting the operation life of proton exchange membrane fuel cell (PEMFC). On the basis of principle and classical model of the PEMFC, single cell voltage is calculated and the location coefficients are introduced so as to establish a non-uniformity voltage model. These coefficients are estimated with the experimental datum at stack current 50 A. The model is validated respectively with datum at 60 A and 100 A. The results show that the model reflects the basic characteristics of voltage non-uniformity and provides the beneficial reference for fuel cell control and single cell voltage detection.

The interplay between genetic and bioelectrical signaling permits a spatial regionalisation of membrane potentials in model multicellular ensembles

PubMed Central

Cervera, Javier; Meseguer, Salvador; Mafe, Salvador

2016-01-01

The single cell-centred approach emphasises ion channels as specific proteins that determine individual properties, disregarding their contribution to multicellular outcomes. We simulate the interplay between genetic and bioelectrical signals in non-excitable cells from the local single-cell level to the long range multicellular ensemble. The single-cell genetic regulation is based on mean-field kinetic equations involving the mRNA and protein concentrations. The transcription rate factor is assumed to depend on the absolute value of the cell potential, which is dictated by the voltage-gated cell ion channels and the intercellular gap junctions. The interplay between genetic and electrical signals may allow translating single-cell states into multicellular states which provide spatio-temporal information. The model results have clear implications for biological processes: (i) bioelectric signals can override slightly different genetic pre-patterns; (ii) ensembles of cells initially at the same potential can undergo an electrical regionalisation because of persistent genetic differences between adjacent spatial regions; and (iii) shifts in the normal cell electrical balance could trigger significant changes in the genetic regulation. PMID:27731412

The interplay between genetic and bioelectrical signaling permits a spatial regionalisation of membrane potentials in model multicellular ensembles.

PubMed

Cervera, Javier; Meseguer, Salvador; Mafe, Salvador

2016-10-12

The single cell-centred approach emphasises ion channels as specific proteins that determine individual properties, disregarding their contribution to multicellular outcomes. We simulate the interplay between genetic and bioelectrical signals in non-excitable cells from the local single-cell level to the long range multicellular ensemble. The single-cell genetic regulation is based on mean-field kinetic equations involving the mRNA and protein concentrations. The transcription rate factor is assumed to depend on the absolute value of the cell potential, which is dictated by the voltage-gated cell ion channels and the intercellular gap junctions. The interplay between genetic and electrical signals may allow translating single-cell states into multicellular states which provide spatio-temporal information. The model results have clear implications for biological processes: (i) bioelectric signals can override slightly different genetic pre-patterns; (ii) ensembles of cells initially at the same potential can undergo an electrical regionalisation because of persistent genetic differences between adjacent spatial regions; and (iii) shifts in the normal cell electrical balance could trigger significant changes in the genetic regulation.

Limiting Energy Dissipation Induces Glassy Kinetics in Single-Cell High-Precision Responses

PubMed Central

Das, Jayajit

2016-01-01

Single cells often generate precise responses by involving dissipative out-of-thermodynamic-equilibrium processes in signaling networks. The available free energy to fuel these processes could become limited depending on the metabolic state of an individual cell. How does limiting dissipation affect the kinetics of high-precision responses in single cells? I address this question in the context of a kinetic proofreading scheme used in a simple model of early-time T cell signaling. Using exact analytical calculations and numerical simulations, I show that limiting dissipation qualitatively changes the kinetics in single cells marked by emergence of slow kinetics, large cell-to-cell variations of copy numbers, temporally correlated stochastic events (dynamic facilitation), and ergodicity breaking. Thus, constraints in energy dissipation, in addition to negatively affecting ligand discrimination in T cells, can create a fundamental difficulty in determining single-cell kinetics from cell-population results. PMID:26958894

A single-cell spiking model for the origin of grid-cell patterns

PubMed Central

Kempter, Richard

2017-01-01

Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity. PMID:28968386

Preface of the "Symposium on Mathematical Models and Methods to investigate Heterogeneity in Cell and Cell Population Biology"

NASA Astrophysics Data System (ADS)

Clairambault, Jean

2016-06-01

This session investigates hot topics related to mathematical representations of cell and cell population dynamics in biology and medicine, in particular, but not only, with applications to cancer. Methods in mathematical modelling and analysis, and in statistical inference using single-cell and cell population data, should contribute to focus this session on heterogeneity in cell populations. Among other methods are proposed: a) Intracellular protein dynamics and gene regulatory networks using ordinary/partial/delay differential equations (ODEs, PDEs, DDEs); b) Representation of cell population dynamics using agent-based models (ABMs) and/or PDEs; c) Hybrid models and multiscale models to integrate single-cell dynamics into cell population behaviour; d) Structured cell population dynamics and asymptotic evolution w.r.t. relevant traits; e) Heterogeneity in cancer cell populations: origin, evolution, phylogeny and methods of reconstruction; f) Drug resistance as an evolutionary phenotype: predicting and overcoming it in therapeutics; g) Theoretical therapeutic optimisation of combined drug treatments in cancer cell populations and in populations of other organisms, such as bacteria.

Copy number variants calling for single cell sequencing data by multi-constrained optimization.

PubMed

Xu, Bo; Cai, Hongmin; Zhang, Changsheng; Yang, Xi; Han, Guoqiang

2016-08-01

Variations in DNA copy number carry important information on genome evolution and regulation of DNA replication in cancer cells. The rapid development of single-cell sequencing technology allows one to explore gene expression heterogeneity among single-cells, thus providing important cancer cell evolution information. Single-cell DNA/RNA sequencing data usually have low genome coverage, which requires an extra step of amplification to accumulate enough samples. However, such amplification will introduce large bias and makes bioinformatics analysis challenging. Accurately modeling the distribution of sequencing data and effectively suppressing the bias influence is the key to success variations analysis. Recent advances demonstrate the technical noises by amplification are more likely to follow negative binomial distribution, a special case of Poisson distribution. Thus, we tackle the problem CNV detection by formulating it into a quadratic optimization problem involving two constraints, in which the underling signals are corrupted by Poisson distributed noises. By imposing the constraints of sparsity and smoothness, the reconstructed read depth signals from single-cell sequencing data are anticipated to fit the CNVs patterns more accurately. An efficient numerical solution based on the classical alternating direction minimization method (ADMM) is tailored to solve the proposed model. We demonstrate the advantages of the proposed method using both synthetic and empirical single-cell sequencing data. Our experimental results demonstrate that the proposed method achieves excellent performance and high promise of success with single-cell sequencing data. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Reconstructing blood stem cell regulatory network models from single-cell molecular profiles

PubMed Central

Hamey, Fiona K.; Nestorowa, Sonia; Kinston, Sarah J.; Kent, David G.; Wilson, Nicola K.

2017-01-01

Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte–erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (Nfe2) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (Cbfa2t3h) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships. PMID:28584094

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.

Dynamics of Cell Ensembles on Adhesive Micropatterns: Bridging the Gap between Single Cell Spreading and Collective Cell Migration

PubMed Central

Albert, Philipp J.; Schwarz, Ulrich S.

2016-01-01

The collective dynamics of multicellular systems arise from the interplay of a few fundamental elements: growth, division and apoptosis of single cells; their mechanical and adhesive interactions with neighboring cells and the extracellular matrix; and the tendency of polarized cells to move. Micropatterned substrates are increasingly used to dissect the relative roles of these fundamental processes and to control the resulting dynamics. Here we show that a unifying computational framework based on the cellular Potts model can describe the experimentally observed cell dynamics over all relevant length scales. For single cells, the model correctly predicts the statistical distribution of the orientation of the cell division axis as well as the final organisation of the two daughters on a large range of micropatterns, including those situations in which a stable configuration is not achieved and rotation ensues. Large ensembles migrating in heterogeneous environments form non-adhesive regions of inward-curved arcs like in epithelial bridge formation. Collective migration leads to swirl formation with variations in cell area as observed experimentally. In each case, we also use our model to predict cell dynamics on patterns that have not been studied before. PMID:27054883

Homogenized modeling methodology for 18650 lithium-ion battery module under large deformation

PubMed Central

Tang, Liang; Cheng, Pengle

2017-01-01

Effective lithium-ion battery module modeling has become a bottleneck for full-size electric vehicle crash safety numerical simulation. Modeling every single cell in detail would be costly. However, computational accuracy could be lost if the module is modeled by using a simple bulk material or rigid body. To solve this critical engineering problem, a general method to establish a computational homogenized model for the cylindrical battery module is proposed. A single battery cell model is developed and validated through radial compression and bending experiments. To analyze the homogenized mechanical properties of the module, a representative unit cell (RUC) is extracted with the periodic boundary condition applied on it. An elastic–plastic constitutive model is established to describe the computational homogenized model for the module. Two typical packing modes, i.e., cubic dense packing and hexagonal packing for the homogenized equivalent battery module (EBM) model, are targeted for validation compression tests, as well as the models with detailed single cell description. Further, the homogenized EBM model is confirmed to agree reasonably well with the detailed battery module (DBM) model for different packing modes with a length scale of up to 15 × 15 cells and 12% deformation where the short circuit takes place. The suggested homogenized model for battery module makes way for battery module and pack safety evaluation for full-size electric vehicle crashworthiness analysis. PMID:28746390

Homogenized modeling methodology for 18650 lithium-ion battery module under large deformation.

PubMed

Tang, Liang; Zhang, Jinjie; Cheng, Pengle

2017-01-01

Effective lithium-ion battery module modeling has become a bottleneck for full-size electric vehicle crash safety numerical simulation. Modeling every single cell in detail would be costly. However, computational accuracy could be lost if the module is modeled by using a simple bulk material or rigid body. To solve this critical engineering problem, a general method to establish a computational homogenized model for the cylindrical battery module is proposed. A single battery cell model is developed and validated through radial compression and bending experiments. To analyze the homogenized mechanical properties of the module, a representative unit cell (RUC) is extracted with the periodic boundary condition applied on it. An elastic-plastic constitutive model is established to describe the computational homogenized model for the module. Two typical packing modes, i.e., cubic dense packing and hexagonal packing for the homogenized equivalent battery module (EBM) model, are targeted for validation compression tests, as well as the models with detailed single cell description. Further, the homogenized EBM model is confirmed to agree reasonably well with the detailed battery module (DBM) model for different packing modes with a length scale of up to 15 × 15 cells and 12% deformation where the short circuit takes place. The suggested homogenized model for battery module makes way for battery module and pack safety evaluation for full-size electric vehicle crashworthiness analysis.

Computational Modeling | Photovoltaic Research | NREL

Science.gov Websites

performance of single- and multijunction cells and modules. We anticipate the upcoming completion of our next software package for a simplified electronic design of single- and multicrystalline silicon solar cells

Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours

PubMed Central

Molnar, Csaba; Jermyn, Ian H.; Kato, Zoltan; Rahkama, Vesa; Östling, Päivi; Mikkonen, Piia; Pietiäinen, Vilja; Horvath, Peter

2016-01-01

The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phenotypic variation. However, the cells used in experiments can lose their contact inhibition, and can therefore pile up on top of each other, making the detection of single cells extremely challenging using current segmentation methods. The model we present here can detect cell nuclei and their morphology even in high-confluency cell cultures with many overlapping cell nuclei. We combine the “gas of near circles” active contour model, which favors circular shapes but allows slight variations around them, with a new data model. This captures a common property of many microscopic imaging techniques: the intensities from superposed nuclei are additive, so that two overlapping nuclei, for example, have a total intensity that is approximately double the intensity of a single nucleus. We demonstrate the power of our method on microscopic images of cells, comparing the results with those obtained from a widely used approach, and with manual image segmentations by experts. PMID:27561654

Decipher the Molecular Response of Plant Single Cell Types to Environmental Stresses

DOE PAGES

Nourbakhsh-Rey, Mehrnoush; Libault, Marc

2016-01-01

The analysis of the molecular response of entire plants or organs to environmental stresses suffers from the cellular complexity of the samples used. Specifically, this cellular complexity masks cell-specific responses to environmental stresses and logically leads to the dilution of the molecular changes occurring in each cell type composing the tissue/organ/plant in response to the stress. Therefore, to generate a more accurate picture of these responses, scientists are focusing on plant single cell type approaches. Several cell types are now considered as models such as the pollen, the trichomes, the cotton fiber, various root cell types including the root hairmore » cell, and the guard cell of stomata. Among them, several have been used to characterize plant response to abiotic and biotic stresses. Lastly, in this review, we are describing the various -omic studies performed on these different plant single cell type models to better understand plant cell response to biotic and abiotic stresses.« less

Decipher the Molecular Response of Plant Single Cell Types to Environmental Stresses

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

Nourbakhsh-Rey, Mehrnoush; Libault, Marc

The analysis of the molecular response of entire plants or organs to environmental stresses suffers from the cellular complexity of the samples used. Specifically, this cellular complexity masks cell-specific responses to environmental stresses and logically leads to the dilution of the molecular changes occurring in each cell type composing the tissue/organ/plant in response to the stress. Therefore, to generate a more accurate picture of these responses, scientists are focusing on plant single cell type approaches. Several cell types are now considered as models such as the pollen, the trichomes, the cotton fiber, various root cell types including the root hairmore » cell, and the guard cell of stomata. Among them, several have been used to characterize plant response to abiotic and biotic stresses. Lastly, in this review, we are describing the various -omic studies performed on these different plant single cell type models to better understand plant cell response to biotic and abiotic stresses.« less

A Facile Droplet-Chip-Time-Resolved Inductively Coupled Plasma Mass Spectrometry Online System for Determination of Zinc in Single Cell.

PubMed

Wang, Han; Chen, Beibei; He, Man; Hu, Bin

2017-05-02

Single cell analysis is a significant research field in recent years reflecting the heterogeneity of cells in a biological system. In this work, a facile droplet chip was fabricated and online combined with time-resolved inductively coupled plasma mass spectrometry (ICPMS) via a microflow nebulizer for the determination of zinc in single HepG2 cells. On the focusing geometric designed PDMS microfluidic chip, the aqueous cell suspension was ejected and divided by hexanol to generate droplets. The droplets encapsulated single cells remain intact during the transportation into ICP for subsequent detection. Under the optimized conditions, the frequency of droplet generation is 3-6 × 10 6 min -1 , and the injected cell number is 2500 min -1 , which can ensure the single cell encapsulation. ZnO nanoparticles (NPs) were used for the quantification of zinc in single cells, and the accuracy was validated by conventional acid digestion-ICPMS method. The ZnO NPs incubated HepG2 cells were analyzed as model samples, and the results exhibit the heterogeneity of HepG2 cells in the uptake/adsorption of ZnO NPs. The developed online droplet-chip-ICPMS analysis system achieves stable single cell encapsulation and has high throughput for single cell analysis. It has the potential in monitoring the content as well as distribution of trace elements/NPs at the single cell level.

Droplet microfluidics for amplification-free genetic detection of single cells.

PubMed

Rane, Tushar D; Zec, Helena C; Puleo, Chris; Lee, Abraham P; Wang, Tza-Huei

2012-09-21

In this article we present a novel droplet microfluidic chip enabling amplification-free detection of single pathogenic cells. The device streamlines multiple functionalities to carry out sample digitization, cell lysis, probe-target hybridization for subsequent fluorescent detection. A peptide nucleic acid fluorescence resonance energy transfer probe (PNA beacon) is used to detect 16S rRNA present in pathogenic cells. Initially the sensitivity and quantification abilities of the platform are tested using a synthetic target mimicking the actual expression level of 16S rRNA in single cells. The capability of the device to perform "sample-to-answer" pathogen detection of single cells is demonstrated using E. coli as a model pathogen.

Single-Cell Genomics: Approaches and Utility in Immunology.

PubMed

Neu, Karlynn E; Tang, Qingming; Wilson, Patrick C; Khan, Aly A

2017-02-01

Single-cell genomics offers powerful tools for studying immune cells, which make it possible to observe rare and intermediate cell states that cannot be resolved at the population level. Advances in computer science and single-cell sequencing technology have created a data-driven revolution in immunology. The challenge for immunologists is to harness computing and turn an avalanche of quantitative data into meaningful discovery of immunological principles, predictive models, and strategies for therapeutics. Here, we review the current literature on computational analysis of single-cell RNA-sequencing data and discuss underlying assumptions, methods, and applications in immunology, and highlight important directions for future research. Copyright © 2016 Elsevier Ltd. All rights reserved.

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

Single Cell Genomics: Approaches and Utility in Immunology

PubMed Central

Neu, Karlynn E; Tang, Qingming; Wilson, Patrick C; Khan, Aly A

2017-01-01

Single cell genomics offers powerful tools for studying lymphocytes, which make it possible to observe rare and intermediate cell states that cannot be resolved at the population-level. Advances in computer science and single cell sequencing technology have created a data-driven revolution in immunology. The challenge for immunologists is to harness computing and turn an avalanche of quantitative data into meaningful discovery of immunological principles, predictive models, and strategies for therapeutics. Here, we review the current literature on computational analysis of single cell RNA-seq data and discuss underlying assumptions, methods, and applications in immunology, and highlight important directions for future research. PMID:28094102

Calibrating genomic and allelic coverage bias in single-cell sequencing.

PubMed

Zhang, Cheng-Zhong; Adalsteinsson, Viktor A; Francis, Joshua; Cornils, Hauke; Jung, Joonil; Maire, Cecile; Ligon, Keith L; Meyerson, Matthew; Love, J Christopher

2015-04-16

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1-10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (∼0.1 × ) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples.

Calibrating genomic and allelic coverage bias in single-cell sequencing

PubMed Central

Francis, Joshua; Cornils, Hauke; Jung, Joonil; Maire, Cecile; Ligon, Keith L.; Meyerson, Matthew; Love, J. Christopher

2016-01-01

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1–10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (~0.1 ×) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples. PMID:25879913

Multi-Scale Modeling to Improve Single-Molecule, Single-Cell Experiments

NASA Astrophysics Data System (ADS)

Munsky, Brian; Shepherd, Douglas

2014-03-01

Single-cell, single-molecule experiments are producing an unprecedented amount of data to capture the dynamics of biological systems. When integrated with computational models, observations of spatial, temporal and stochastic fluctuations can yield powerful quantitative insight. We concentrate on experiments that localize and count individual molecules of mRNA. These high precision experiments have large imaging and computational processing costs, and we explore how improved computational analyses can dramatically reduce overall data requirements. In particular, we show how analyses of spatial, temporal and stochastic fluctuations can significantly enhance parameter estimation results for small, noisy data sets. We also show how full probability distribution analyses can constrain parameters with far less data than bulk analyses or statistical moment closures. Finally, we discuss how a systematic modeling progression from simple to more complex analyses can reduce total computational costs by orders of magnitude. We illustrate our approach using single-molecule, spatial mRNA measurements of Interleukin 1-alpha mRNA induction in human THP1 cells following stimulation. Our approach could improve the effectiveness of single-molecule gene regulation analyses for many other process.

Jamming and liquidity in 3D cancer cell aggregates

NASA Astrophysics Data System (ADS)

Oswald, Linda; Grosser, Steffen; Lippoldt, Jürgen; Pawlizak, Steve; Fritsch, Anatol; KäS, Josef A.

Traditionally, tissues are treated as simple liquids, which holds for example for embryonic tissue. However, recent experiments have shown that this picture is insufficient for other tissue types, suggesting possible transitions to solid-like behavior induced by cellular jamming. The coarse-grained self-propelled Voronoi (SPV) model predicts such a transition depending on cell shape which is thought to arise from an interplay of cell-cell adhesion and cortical tension. We observe non-liquid behavior in 3D breast cancer spheroids of varying metastatic potential and correlate single cell shapes, single cell dynamics and collective dynamic behavior of fusion and segregation experiments via the SPV model.

A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development.

PubMed

Yao, Zizhen; Mich, John K; Ku, Sherman; Menon, Vilas; Krostag, Anne-Rachel; Martinez, Refugio A; Furchtgott, Leon; Mulholland, Heather; Bort, Susan; Fuqua, Margaret A; Gregor, Ben W; Hodge, Rebecca D; Jayabalu, Anu; May, Ryan C; Melton, Samuel; Nelson, Angelique M; Ngo, N Kiet; Shapovalova, Nadiya V; Shehata, Soraya I; Smith, Michael W; Tait, Leah J; Thompson, Carol L; Thomsen, Elliot R; Ye, Chaoyang; Glass, Ian A; Kaykas, Ajamete; Yao, Shuyuan; Phillips, John W; Grimley, Joshua S; Levi, Boaz P; Wang, Yanling; Ramanathan, Sharad

2017-01-05

During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/β-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states

PubMed Central

Jang, Sumin; Choubey, Sandeep; Furchtgott, Leon; Zou, Ling-Nan; Doyle, Adele; Menon, Vilas; Loew, Ethan B; Krostag, Anne-Rachel; Martinez, Refugio A; Madisen, Linda; Levi, Boaz P; Ramanathan, Sharad

2017-01-01

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development. DOI: http://dx.doi.org/10.7554/eLife.20487.001 PMID:28296635

Self-organized, near-critical behavior during aggregation in Dictyostelium discoideum

NASA Astrophysics Data System (ADS)

de Palo, Giovanna; Yi, Darvin; Gregor, Thomas; Endres, Robert

During starvation, the social amoeba Dictyostelium discoideum aggregates artfully via pattern formation into a multicellular slug and finally spores. The aggregation process is mediated by the secretion and sensing of cyclic adenosine monophosphate, leading to the synchronized movement of cells. The whole process is a remarkable example of collective behavior, spontaneously emerging from single-cell chemotaxis. Despite this phenomenon being broadly studied, a precise characterization of the transition from single cells to multicellularity has been elusive. Here, using fluorescence imaging data of thousands of cells, we investigate the role of cell shape in aggregation, demonstrating remarkable transitions in cell behavior. To better understand their functional role, we analyze cell-cell correlations and provide evidence for self-organization at the onset of aggregation (as opposed to leader cells), with features of criticality in this finite system. To capture the mechanism of self-organization, we extend a detailed single-cell model of D.discoideum chemotaxis by adding cell-cell communication. We then use these results to extract a minimal set of rules leading to aggregation in the population model. If universal, similar rules may explain other types of collective cell behavior.

Cell differentiation modeled via a coupled two-switch regulatory network

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Limiting Energy Dissipation Induces Glassy Kinetics in Single-Cell High-Precision Responses.

PubMed

Das, Jayajit

2016-03-08

Single cells often generate precise responses by involving dissipative out-of-thermodynamic-equilibrium processes in signaling networks. The available free energy to fuel these processes could become limited depending on the metabolic state of an individual cell. How does limiting dissipation affect the kinetics of high-precision responses in single cells? I address this question in the context of a kinetic proofreading scheme used in a simple model of early-time T cell signaling. Using exact analytical calculations and numerical simulations, I show that limiting dissipation qualitatively changes the kinetics in single cells marked by emergence of slow kinetics, large cell-to-cell variations of copy numbers, temporally correlated stochastic events (dynamic facilitation), and ergodicity breaking. Thus, constraints in energy dissipation, in addition to negatively affecting ligand discrimination in T cells, can create a fundamental difficulty in determining single-cell kinetics from cell-population results. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A Finite Element Study of Micropipette Aspiration of Single Cells: Effect of Compressibility

PubMed Central

Jafari Bidhendi, Amirhossein; Korhonen, Rami K.

2012-01-01

Micropipette aspiration (MA) technique has been widely used to measure the viscoelastic properties of different cell types. Cells experience nonlinear large deformations during the aspiration procedure. Neo-Hookean viscohyperelastic (NHVH) incompressible and compressible models were used to simulate the creep behavior of cells in MA, particularly accounting for the effect of compressibility, bulk relaxation, and hardening phenomena under large strain. In order to find optimal material parameters, the models were fitted to the experimental data available for mesenchymal stem cells. Finally, through Neo-Hookean porohyperelastic (NHPH) material model for the cell, the influence of fluid flow on the aspiration length of the cell was studied. Based on the results, we suggest that the compressibility and bulk relaxation/fluid flow play a significant role in the deformation behavior of single cells and should be taken into account in the analysis of the mechanics of cells. PMID:22400045

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

NASA Astrophysics Data System (ADS)

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-09-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics.

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

PubMed Central

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-01-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics. PMID:27671239

Theory and simulation of backbombardment in single-cell thermionic-cathode electron guns

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

Edelen, J.  P.; Biedron, S.  G.; Harris, J.  R.

This paper presents a comparison between simulation results and a first principles analytical model of electron back-bombardment developed at Colorado State University for single-cell, thermionic-cathode rf guns. While most previous work on back-bombardment has been specific to particular accelerator systems, this work is generalized to a wide variety of guns within the applicable parameter space. The merits and limits of the analytic model will be discussed. This paper identifies the three fundamental parameters that drive the back-bombardment process, and demonstrates relative accuracy in calculating the predicted back-bombardment power of a single-cell thermionic gun.

Theory and simulation of backbombardment in single-cell thermionic-cathode electron guns

DOE PAGES

Edelen, J.  P.; Biedron, S.  G.; Harris, J.  R.; ...

2015-04-01

This paper presents a comparison between simulation results and a first principles analytical model of electron back-bombardment developed at Colorado State University for single-cell, thermionic-cathode rf guns. While most previous work on back-bombardment has been specific to particular accelerator systems, this work is generalized to a wide variety of guns within the applicable parameter space. The merits and limits of the analytic model will be discussed. This paper identifies the three fundamental parameters that drive the back-bombardment process, and demonstrates relative accuracy in calculating the predicted back-bombardment power of a single-cell thermionic gun.

A Mouse Model for Conditional Secretion of Specific Single-Chain Antibodies Provides Genetic Evidence for Regulation of Cortical Plasticity by a Non-cell Autonomous Homeoprotein Transcription Factor.

PubMed

Bernard, Clémence; Vincent, Clémentine; Testa, Damien; Bertini, Eva; Ribot, Jérôme; Di Nardo, Ariel A; Volovitch, Michel; Prochiantz, Alain

2016-05-01

During postnatal life the cerebral cortex passes through critical periods of plasticity allowing its physiological adaptation to the environment. In the visual cortex, critical period onset and closure are influenced by the non-cell autonomous activity of the Otx2 homeoprotein transcription factor, which regulates the maturation of parvalbumin-expressing inhibitory interneurons (PV cells). In adult mice, the maintenance of a non-plastic adult state requires continuous Otx2 import by PV cells. An important source of extra-cortical Otx2 is the choroid plexus, which secretes Otx2 into the cerebrospinal fluid. Otx2 secretion and internalization requires two small peptidic domains that are part of the DNA-binding domain. Thus, mutating these "transfer" sequences also modifies cell autonomous transcription, precluding this approach to obtain a cell autonomous-only mouse. Here, we develop a mouse model with inducible secretion of an anti-Otx2 single-chain antibody to trap Otx2 in the extracellular milieu. Postnatal secretion of this single-chain antibody by PV cells delays PV maturation and reduces plasticity gene expression. Induced adult expression of this single-chain antibody in cerebrospinal fluid decreases Otx2 internalization by PV cells, strongly induces plasticity gene expression and reopens physiological plasticity. We provide the first mammalian genetic evidence for a signaling mechanism involving intercellular transfer of a homeoprotein transcription factor. Our single-chain antibody mouse model is a valid strategy for extracellular neutralization that could be applied to other homeoproteins and signaling molecules within and beyond the nervous system.

TRACING CO-REGULATORY NETWORK DYNAMICS IN NOISY, SINGLE-CELL TRANSCRIPTOME TRAJECTORIES.

PubMed

Cordero, Pablo; Stuart, Joshua M

2017-01-01

The availability of gene expression data at the single cell level makes it possible to probe the molecular underpinnings of complex biological processes such as differentiation and oncogenesis. Promising new methods have emerged for reconstructing a progression 'trajectory' from static single-cell transcriptome measurements. However, it remains unclear how to adequately model the appreciable level of noise in these data to elucidate gene regulatory network rewiring. Here, we present a framework called Single Cell Inference of MorphIng Trajectories and their Associated Regulation (SCIMITAR) that infers progressions from static single-cell transcriptomes by employing a continuous parametrization of Gaussian mixtures in high-dimensional curves. SCIMITAR yields rich models from the data that highlight genes with expression and co-expression patterns that are associated with the inferred progression. Further, SCIMITAR extracts regulatory states from the implicated trajectory-evolvingco-expression networks. We benchmark the method on simulated data to show that it yields accurate cell ordering and gene network inferences. Applied to the interpretation of a single-cell human fetal neuron dataset, SCIMITAR finds progression-associated genes in cornerstone neural differentiation pathways missed by standard differential expression tests. Finally, by leveraging the rewiring of gene-gene co-expression relations across the progression, the method reveals the rise and fall of co-regulatory states and trajectory-dependent gene modules. These analyses implicate new transcription factors in neural differentiation including putative co-factors for the multi-functional NFAT pathway.

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

Brechenmacher, Laurent; Nguyen, Tran H.; Hixson, Kim K.

Root hairs are a terminally differentiated single cell type, mainly involved in water and nutrient uptake from the soil. The soybean root hair cell represents an excellent model for the study of single cell systems biology. In this study, we identified 5702 proteins, with at least two peptides, from soybean root hairs using an accurate mass and time tag approach, establishing the most comprehensive proteome reference map of this single cell type. We also showed that trypsin is the most appropriate enzyme for soybean proteomic studies by performing an in silico digestion of the soybean proteome database using different proteases.more » Although the majority of proteins identified in this study are involved in basal metabolism, the function of others are more related to root hair formation/function and include proteins involved in nutrient uptake (transporters) or vesicular trafficking (cytoskeleton and RAB proteins). Interestingly, some of these proteins appear to be specifically expressed in root hairs and constitute very good candidates for further studies to elucidate unique features of this single cell model.« less

Single Cell Oncogenesis

NASA Astrophysics Data System (ADS)

Lu, Xin

It is believed that cancer originates from a single cell that has gone through generations of evolution of genetic and epigenetic changes that associate with the hallmarks of cancer. In some cancers such as various types of leukemia, cancer is clonal. Yet in other cancers like glioblastoma (GBM), there is tremendous tumor heterogeneity that is likely to be caused by simultaneous evolution of multiple subclones within the same tissue. It is obvious that understanding how a single cell develops into a clonal tumor upon genetic alterations, at molecular and cellular levels, holds the key to the real appreciation of tumor etiology and ultimate solution for therapeutics. Surprisingly very little is known about the process of spontaneous tumorigenesis from single cells in human or vertebrate animal models. The main reason is the lack of technology to track the natural process of single cell changes from a homeostatic state to a progressively cancerous state. Recently, we developed a patented compound, photoactivatable (''caged'') tamoxifen analogue 4-OHC and associated technique called optochemogenetic switch (OCG switch), which we believe opens the opportunity to address this urgent biological as well as clinical question about cancer. We propose to combine OCG switch with genetically engineered mouse models of head and neck squamous cell carcinoma and high grade astrocytoma (including GBM) to study how single cells, when transformed through acute loss of tumor suppressor genes PTEN and TP53 and gain of oncogenic KRAS, can develop into tumor colonies with cellular and molecular heterogeneity in these tissues. The abstract is for my invited talk in session ``Beyond Darwin: Evolution in Single Cells'' 3/18/2016 11:15 AM.

Ensemble methods for stochastic networks with special reference to the biological clock of Neurospora crassa.

PubMed

Caranica, C; Al-Omari, A; Deng, Z; Griffith, J; Nilsen, R; Mao, L; Arnold, J; Schüttler, H-B

2018-01-01

A major challenge in systems biology is to infer the parameters of regulatory networks that operate in a noisy environment, such as in a single cell. In a stochastic regime it is hard to distinguish noise from the real signal and to infer the noise contribution to the dynamical behavior. When the genetic network displays oscillatory dynamics, it is even harder to infer the parameters that produce the oscillations. To address this issue we introduce a new estimation method built on a combination of stochastic simulations, mass action kinetics and ensemble network simulations in which we match the average periodogram and phase of the model to that of the data. The method is relatively fast (compared to Metropolis-Hastings Monte Carlo Methods), easy to parallelize, applicable to large oscillatory networks and large (~2000 cells) single cell expression data sets, and it quantifies the noise impact on the observed dynamics. Standard errors of estimated rate coefficients are typically two orders of magnitude smaller than the mean from single cell experiments with on the order of ~1000 cells. We also provide a method to assess the goodness of fit of the stochastic network using the Hilbert phase of single cells. An analysis of phase departures from the null model with no communication between cells is consistent with a hypothesis of Stochastic Resonance describing single cell oscillators. Stochastic Resonance provides a physical mechanism whereby intracellular noise plays a positive role in establishing oscillatory behavior, but may require model parameters, such as rate coefficients, that differ substantially from those extracted at the macroscopic level from measurements on populations of millions of communicating, synchronized cells.

Single Vector Calibration System for Multi-Axis Load Cells and Method for Calibrating a Multi-Axis Load Cell

NASA Technical Reports Server (NTRS)

Parker, Peter A. (Inventor)

2003-01-01

A single vector calibration system is provided which facilitates the calibration of multi-axis load cells, including wind tunnel force balances. The single vector system provides the capability to calibrate a multi-axis load cell using a single directional load, for example loading solely in the gravitational direction. The system manipulates the load cell in three-dimensional space, while keeping the uni-directional calibration load aligned. The use of a single vector calibration load reduces the set-up time for the multi-axis load combinations needed to generate a complete calibration mathematical model. The system also reduces load application inaccuracies caused by the conventional requirement to generate multiple force vectors. The simplicity of the system reduces calibration time and cost, while simultaneously increasing calibration accuracy.

Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data.

PubMed

Jia, Cheng; Hu, Yu; Kelly, Derek; Kim, Junhyong; Li, Mingyao; Zhang, Nancy R

2017-11-02

Recent technological breakthroughs have made it possible to measure RNA expression at the single-cell level, thus paving the way for exploring expression heterogeneity among individual cells. Current single-cell RNA sequencing (scRNA-seq) protocols are complex and introduce technical biases that vary across cells, which can bias downstream analysis without proper adjustment. To account for cell-to-cell technical differences, we propose a statistical framework, TASC (Toolkit for Analysis of Single Cell RNA-seq), an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins. TASC incorporates the technical parameters, which reflect cell-to-cell batch effects, into a hierarchical mixture model to estimate the biological variance of a gene and detect differentially expressed genes. More importantly, TASC is able to adjust for covariates to further eliminate confounding that may originate from cell size and cell cycle differences. In simulation and real scRNA-seq data, TASC achieves accurate Type I error control and displays competitive sensitivity and improved robustness to batch effects in differential expression analysis, compared to existing methods. TASC is programmed to be computationally efficient, taking advantage of multi-threaded parallelization. We believe that TASC will provide a robust platform for researchers to leverage the power of scRNA-seq. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data

PubMed Central

Jia, Cheng; Hu, Yu; Kelly, Derek; Kim, Junhyong

2017-01-01

Abstract Recent technological breakthroughs have made it possible to measure RNA expression at the single-cell level, thus paving the way for exploring expression heterogeneity among individual cells. Current single-cell RNA sequencing (scRNA-seq) protocols are complex and introduce technical biases that vary across cells, which can bias downstream analysis without proper adjustment. To account for cell-to-cell technical differences, we propose a statistical framework, TASC (Toolkit for Analysis of Single Cell RNA-seq), an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins. TASC incorporates the technical parameters, which reflect cell-to-cell batch effects, into a hierarchical mixture model to estimate the biological variance of a gene and detect differentially expressed genes. More importantly, TASC is able to adjust for covariates to further eliminate confounding that may originate from cell size and cell cycle differences. In simulation and real scRNA-seq data, TASC achieves accurate Type I error control and displays competitive sensitivity and improved robustness to batch effects in differential expression analysis, compared to existing methods. TASC is programmed to be computationally efficient, taking advantage of multi-threaded parallelization. We believe that TASC will provide a robust platform for researchers to leverage the power of scRNA-seq. PMID:29036714

Analysis of mitosis and antimitotic drug responses in tumors by in vivo microscopy and single-cell pharmacodynamics.

PubMed

Orth, James D; Kohler, Rainer H; Foijer, Floris; Sorger, Peter K; Weissleder, Ralph; Mitchison, Timothy J

2011-07-01

Cancer relies upon frequent or abnormal cell division, but how the tumor microenvironment affects mitotic processes in vivo remains unclear, largely due to the technical challenges of optical access, spatial resolution, and motion. We developed high-resolution in vivo microscopy methods to visualize mitosis in a murine xenograft model of human cancer. Using these methods, we determined whether the single-cell response to the antimitotic drug paclitaxel (Ptx) was the same in tumors as in cell culture, observed the impact of Ptx on the tumor response as a whole, and evaluated the single-cell pharmacodynamics (PD) of Ptx (by in vivo PD microscopy). Mitotic initiation was generally less frequent in tumors than in cell culture, but subsequently it proceeded normally. Ptx treatment caused spindle assembly defects and mitotic arrest, followed by slippage from mitotic arrest, multinucleation, and apoptosis. Compared with cell culture, the peak mitotic index in tumors exposed to Ptx was lower and the tumor cells survived longer after mitotic arrest, becoming multinucleated rather than dying directly from mitotic arrest. Thus, the tumor microenvironment was much less proapoptotic than cell culture. The morphologies associated with mitotic arrest were dose and time dependent, thereby providing a semiquantitative, single-cell measure of PD. Although many tumor cells did not progress through Ptx-induced mitotic arrest, tumor significantly regressed in the model. Our findings show that in vivo microscopy offers a useful tool to visualize mitosis during tumor progression, drug responses, and cell fate at the single-cell level. ©2011 AACR.

Imaging mRNA In Vivo, from Birth to Death.

PubMed

Tutucci, Evelina; Livingston, Nathan M; Singer, Robert H; Wu, Bin

2018-05-20

RNA is the fundamental information transfer system in the cell. The ability to follow single messenger RNAs (mRNAs) from transcription to degradation with fluorescent probes gives quantitative information about how the information is transferred from DNA to proteins. This review focuses on the latest technological developments in the field of single-mRNA detection and their usage to study gene expression in both fixed and live cells. By describing the application of these imaging tools, we follow the journey of mRNA from transcription to decay in single cells, with single-molecule resolution. We review current theoretical models for describing transcription and translation that were generated by single-molecule and single-cell studies. These methods provide a basis to study how single-molecule interactions generate phenotypes, fundamentally changing our understating of gene expression regulation.

Diagnosis of colorectal cancer using Raman spectroscopy of laser-trapped single living epithelial cells

NASA Astrophysics Data System (ADS)

Chen, Kun; Qin, Yejun; Zheng, Feng; Sun, Menghong; Shi, Daren

2006-07-01

A single-cell diagnostic technique for epithelial cancers is developed by utilizing laser trapping and Raman spectroscopy to differentiate cancerous and normal epithelial cells. Single-cell suspensions were prepared from surgically removed human colorectal tissues following standard primary culture protocols and examined in a near-infrared laser-trapping Raman spectroscopy system, where living epithelial cells were investigated one by one. A diagnostic model was built on the spectral data obtained from 8 patients and validated by the data from 2 new patients. Our technique has potential applications from epithelial cancer diagnosis to the study of cell dynamics of carcinogenesis.

A single-molecule view of gene regulation in cancer

NASA Astrophysics Data System (ADS)

Larson, Daniel

2013-03-01

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. Steroid receptors coordinate a diverse range of responses in higher eukaryotes and are involved in a wide range of human diseases, including cancer. Steroid receptor response elements are present throughout the human genome and modulate chromatin remodeling and transcription in both a local and long-range fashion. As such, steroid receptor-mediated transcription is a paradigm of genetic control in the metazoan nucleus. Moreover, the ligand-dependent nature of these transcription factors makes them appealing targets for therapeutic intervention, necessitating a quantitative understanding of how receptors control output from target genes. 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 gene and follow dynamic synthesis of RNA from the activated locus. The response delay is a measure of time required for chromatin remodeling at a single gene.

Protein gradients in single cells induced by their coupling to "morphogen"-like diffusion

NASA Astrophysics Data System (ADS)

Nandi, Saroj Kumar; Safran, Sam A.

2018-05-01

One of the many ways cells transmit information within their volume is through steady spatial gradients of different proteins. However, the mechanism through which proteins without any sources or sinks form such single-cell gradients is not yet fully understood. One of the models for such gradient formation, based on differential diffusion, is limited to proteins with large ratios of their diffusion constants or to specific protein-large molecule interactions. We introduce a novel mechanism for gradient formation via the coupling of the proteins within a single cell with a molecule, that we call a "pronogen," whose action is similar to that of morphogens in multi-cell assemblies; the pronogen is produced with a fixed flux at one side of the cell. This coupling results in an effectively non-linear diffusion degradation model for the pronogen dynamics within the cell, which leads to a steady-state gradient of the protein concentration. We use stability analysis to show that these gradients are linearly stable with respect to perturbations.

Protein degradation rate is the dominant mechanism accounting for the differences in protein abundance of basal p53 in a human breast and colorectal cancer cell line.

PubMed

Lakatos, Eszter; Salehi-Reyhani, Ali; Barclay, Michael; Stumpf, Michael P H; Klug, David R

2017-01-01

We determine p53 protein abundances and cell to cell variation in two human cancer cell lines with single cell resolution, and show that the fractional width of the distributions is the same in both cases despite a large difference in average protein copy number. We developed a computational framework to identify dominant mechanisms controlling the variation of protein abundance in a simple model of gene expression from the summary statistics of single cell steady state protein expression distributions. Our results, based on single cell data analysed in a Bayesian framework, lends strong support to a model in which variation in the basal p53 protein abundance may be best explained by variations in the rate of p53 protein degradation. This is supported by measurements of the relative average levels of mRNA which are very similar despite large variation in the level of protein.

Cellular dosimetry of (111)In using monte carlo N-particle computer code: comparison with analytic methods and correlation with in vitro cytotoxicity.

PubMed

Cai, Zhongli; Pignol, Jean-Philippe; Chan, Conrad; Reilly, Raymond M

2010-03-01

Our objective was to compare Monte Carlo N-particle (MCNP) self- and cross-doses from (111)In to the nucleus of breast cancer cells with doses calculated by reported analytic methods (Goddu et al. and Farragi et al.). A further objective was to determine whether the MCNP-predicted surviving fraction (SF) of breast cancer cells exposed in vitro to (111)In-labeled diethylenetriaminepentaacetic acid human epidermal growth factor ((111)In-DTPA-hEGF) could accurately predict the experimentally determined values. MCNP was used to simulate the transport of electrons emitted by (111)In from the cell surface, cytoplasm, or nucleus. The doses to the nucleus per decay (S values) were calculated for single cells, closely packed monolayer cells, or cell clusters. The cell and nucleus dimensions of 6 breast cancer cell lines were measured, and cell line-specific S values were calculated. For self-doses, MCNP S values of nucleus to nucleus agreed very well with those of Goddu et al. (ratio of S values using analytic methods vs. MCNP = 0.962-0.995) and Faraggi et al. (ratio = 1.011-1.024). MCNP S values of cytoplasm and cell surface to nucleus compared fairly well with the reported values (ratio = 0.662-1.534 for Goddu et al.; 0.944-1.129 for Faraggi et al.). For cross doses, the S values to the nucleus were independent of (111)In subcellular distribution but increased with cluster size. S values for monolayer cells were significantly different from those of single cells and cell clusters. The MCNP-predicted SF for monolayer MDA-MB-468, MDA-MB-231, and MCF-7 cells agreed with the experimental data (relative error of 3.1%, -1.0%, and 1.7%). The single-cell and cell cluster models were less accurate in predicting the SF. For MDA-MB-468 cells, relative error was 8.1% using the single-cell model and -54% to -67% using the cell cluster model. Individual cell-line dimensions had large effects on S values and were needed to estimate doses and SF accurately. MCNP simulation compared well with the reported analytic methods in the calculation of subcellular S values for single cells and cell clusters. Application of a monolayer model was most accurate in predicting the SF of breast cancer cells exposed in vitro to (111)In-DTPA-hEGF.

CellStress - open source image analysis program for single-cell analysis

NASA Astrophysics Data System (ADS)

Smedh, Maria; Beck, Caroline; Sott, Kristin; Goksör, Mattias

2010-08-01

This work describes our image-analysis software, CellStress, which has been developed in Matlab and is issued under a GPL license. CellStress was developed in order to analyze migration of fluorescent proteins inside single cells during changing environmental conditions. CellStress can also be used to score information regarding protein aggregation in single cells over time, which is especially useful when monitoring cell signaling pathways involved in e.g. Alzheimer's or Huntington's disease. Parallel single-cell analysis of large numbers of cells is an important part of the research conducted in systems biology and quantitative biology in order to mathematically describe cellular processes. To quantify properties for single cells, large amounts of data acquired during extended time periods are needed. Manual analyses of such data involve huge efforts and could also include a bias, which complicates the use and comparison of data for further simulations or modeling. Therefore, it is necessary to have an automated and unbiased image analysis procedure, which is the aim of CellStress. CellStress utilizes cell contours detected by CellStat (developed at Fraunhofer-Chalmers Centre), which identifies cell boundaries using bright field images, and thus reduces the fluorescent labeling needed.

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data.

PubMed

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

2015-06-01

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

Single-cell-based computer simulation of the oxygen-dependent tumour response to irradiation

NASA Astrophysics Data System (ADS)

Harting, Christine; Peschke, Peter; Borkenstein, Klaus; Karger, Christian P.

2007-08-01

Optimization of treatment plans in radiotherapy requires the knowledge of tumour control probability (TCP) and normal tissue complication probability (NTCP). Mathematical models may help to obtain quantitative estimates of TCP and NTCP. A single-cell-based computer simulation model is presented, which simulates tumour growth and radiation response on the basis of the response of the constituting cells. The model contains oxic, hypoxic and necrotic tumour cells as well as capillary cells which are considered as sources of a radial oxygen profile. Survival of tumour cells is calculated by the linear quadratic model including the modified response due to the local oxygen concentration. The model additionally includes cell proliferation, hypoxia-induced angiogenesis, apoptosis and resorption of inactivated tumour cells. By selecting different degrees of angiogenesis, the model allows the simulation of oxic as well as hypoxic tumours having distinctly different oxygen distributions. The simulation model showed that poorly oxygenated tumours exhibit an increased radiation tolerance. Inter-tumoural variation of radiosensitivity flattens the dose response curve. This effect is enhanced by proliferation between fractions. Intra-tumoural radiosensitivity variation does not play a significant role. The model may contribute to the mechanistic understanding of the influence of biological tumour parameters on TCP. It can in principle be validated in radiation experiments with experimental tumours.

A single cyclin–CDK complex is sufficient for both mitotic and meiotic progression in fission yeast

PubMed Central

Gutiérrez-Escribano, Pilar; Nurse, Paul

2015-01-01

The dominant model for eukaryotic cell cycle control proposes that cell cycle progression is driven by a succession of CDK complexes with different substrate specificities. However, in fission yeast it has been shown that a single CDK complex generated by the fusion of the Cdc13 cyclin with the CDK protein Cdc2 can drive the mitotic cell cycle. Meiosis is a modified cell cycle programme in which a single S-phase is followed by two consecutive rounds of chromosome segregation. Here we systematically analyse the requirements of the different fission yeast cyclins for meiotic cell cycle progression. We also show that a single Cdc13–Cdc2 complex, in the absence of the other cyclins, can drive the meiotic cell cycle. We propose that qualitatively different CDK complexes are not absolutely required for cell cycle progression either during mitosis or meiosis, and that a single CDK complex can drive both cell cycle programmes. PMID:25891897

Modeling of cytometry data in logarithmic space: When is a bimodal distribution not bimodal?

PubMed

Erez, Amir; Vogel, Robert; Mugler, Andrew; Belmonte, Andrew; Altan-Bonnet, Grégoire

2018-02-16

Recent efforts in systems immunology lead researchers to build quantitative models of cell activation and differentiation. One goal is to account for the distributions of proteins from single-cell measurements by flow cytometry or mass cytometry as readout of biological regulation. In that context, large cell-to-cell variability is often observed in biological quantities. We show here that these readouts, viewed in logarithmic scale may result in two easily-distinguishable modes, while the underlying distribution (in linear scale) is unimodal. We introduce a simple mathematical test to highlight this mismatch. We then dissect the flow of influence of cell-to-cell variability proposing a graphical model which motivates higher-dimensional analysis of the data. Finally we show how acquiring additional biological information can be used to reduce uncertainty introduced by cell-to-cell variability, helping to clarify whether the data is uni- or bimodal. This communication has cautionary implications for manual and automatic gating strategies, as well as clustering and modeling of single-cell measurements. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

Single Neurons in M1 and Premotor Cortex Directly Reflect Behavioral Interference

PubMed Central

Zach, Neta; Inbar, Dorrit; Grinvald, Yael; Vaadia, Eilon

2012-01-01

Some motor tasks, if learned together, interfere with each other's consolidation and subsequent retention, whereas other tasks do not. Interfering tasks are said to employ the same internal model whereas noninterfering tasks use different models. The division of function among internal models, as well as their possible neural substrates, are not well understood. To investigate these questions, we compared responses of single cells in the primary motor cortex and premotor cortex of primates to interfering and noninterfering tasks. The interfering tasks were visuomotor rotation followed by opposing visuomotor rotation. The noninterfering tasks were visuomotor rotation followed by an arbitrary association task. Learning two noninterfering tasks led to the simultaneous formation of neural activity typical of both tasks, at the level of single neurons. In contrast, and in accordance with behavioral results, after learning two interfering tasks, only the second task was successfully reflected in motor cortical single cell activity. These results support the hypothesis that the representational capacity of motor cortical cells is the basis of behavioral interference and division between internal models. PMID:22427923

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

PubMed

Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng

2018-01-01

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

Modeling genome coverage in single-cell sequencing

PubMed Central

Daley, Timothy; Smith, Andrew D.

2014-01-01

Motivation: Single-cell DNA sequencing is necessary for examining genetic variation at the cellular level, which remains hidden in bulk sequencing experiments. But because they begin with such small amounts of starting material, the amount of information that is obtained from single-cell sequencing experiment is highly sensitive to the choice of protocol employed and variability in library preparation. In particular, the fraction of the genome represented in single-cell sequencing libraries exhibits extreme variability due to quantitative biases in amplification and loss of genetic material. Results: We propose a method to predict the genome coverage of a deep sequencing experiment using information from an initial shallow sequencing experiment mapped to a reference genome. The observed coverage statistics are used in a non-parametric empirical Bayes Poisson model to estimate the gain in coverage from deeper sequencing. This approach allows researchers to know statistical features of deep sequencing experiments without actually sequencing deeply, providing a basis for optimizing and comparing single-cell sequencing protocols or screening libraries. Availability and implementation: The method is available as part of the preseq software package. Source code is available at http://smithlabresearch.org/preseq. Contact: andrewds@usc.edu Supplementary information: Supplementary material is available at Bioinformatics online. PMID:25107873

Voronoi Cell Patterns: theoretical model and application to submonolayer growth

NASA Astrophysics Data System (ADS)

González, Diego Luis; Einstein, T. L.

2012-02-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We apply our model to describe the Voronoi cell patterns of island nucleation for critical island sizes i=0,1,2,3. Experimental results for the Voronoi cells of InAs/GaAs quantum dots are also described by our model.

Clustering Single-Cell Expression Data Using Random Forest Graphs.

PubMed

Pouyan, Maziyar Baran; Nourani, Mehrdad

2017-07-01

Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

PubMed Central

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

2015-01-01

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

Cell-cell bioelectrical interactions and local heterogeneities in genetic networks: a model for the stabilization of single-cell states and multicellular oscillations.

PubMed

Cervera, Javier; Manzanares, José A; Mafe, Salvador

2018-04-04

Genetic networks operate in the presence of local heterogeneities in single-cell transcription and translation rates. Bioelectrical networks and spatio-temporal maps of cell electric potentials can influence multicellular ensembles. Could cell-cell bioelectrical interactions mediated by intercellular gap junctions contribute to the stabilization of multicellular states against local genetic heterogeneities? We theoretically analyze this question on the basis of two well-established experimental facts: (i) the membrane potential is a reliable read-out of the single-cell electrical state and (ii) when the cells are coupled together, their individual cell potentials can be influenced by ensemble-averaged electrical potentials. We propose a minimal biophysical model for the coupling between genetic and bioelectrical networks that associates the local changes occurring in the transcription and translation rates of an ion channel protein with abnormally low (depolarized) cell potentials. We then analyze the conditions under which the depolarization of a small region (patch) in a multicellular ensemble can be reverted by its bioelectrical coupling with the (normally polarized) neighboring cells. We show also that the coupling between genetic and bioelectric networks of non-excitable cells, modulated by average electric potentials at the multicellular ensemble level, can produce oscillatory phenomena. The simulations show the importance of single-cell potentials characteristic of polarized and depolarized states, the relative sizes of the abnormally polarized patch and the rest of the normally polarized ensemble, and intercellular coupling.

Multi-scale modelling of the dynamics of cell colonies: insights into cell-adhesion forces and cancer invasion from in silico simulations.

PubMed

Schlüter, Daniela K; Ramis-Conde, Ignacio; Chaplain, Mark A J

2015-02-06

Studying the biophysical interactions between cells is crucial to understanding how normal tissue develops, how it is structured and also when malfunctions occur. Traditional experiments try to infer events at the tissue level after observing the behaviour of and interactions between individual cells. This approach assumes that cells behave in the same biophysical manner in isolated experiments as they do within colonies and tissues. In this paper, we develop a multi-scale multi-compartment mathematical model that accounts for the principal biophysical interactions and adhesion pathways not only at a cell-cell level but also at the level of cell colonies (in contrast to the traditional approach). Our results suggest that adhesion/separation forces between cells may be lower in cell colonies than traditional isolated single-cell experiments infer. As a consequence, isolated single-cell experiments may be insufficient to deduce important biological processes such as single-cell invasion after detachment from a solid tumour. The simulations further show that kinetic rates and cell biophysical characteristics such as pressure-related cell-cycle arrest have a major influence on cell colony patterns and can allow for the development of protrusive cellular structures as seen in invasive cancer cell lines independent of expression levels of pro-invasion molecules.

Biomechanics of Single Cortical Neurons

PubMed Central

Bernick, Kristin B.; Prevost, Thibault P.; Suresh, Subra; Socrate, Simona

2011-01-01

This study presents experimental results and computational analysis of the large strain dynamic behavior of single neurons in vitro with the objective of formulating a novel quantitative framework for the biomechanics of cortical neurons. Relying on the atomic force microscopy (AFM) technique, novel testing protocols are developed to enable the characterization of neural soma deformability over a range of indentation rates spanning three orders of magnitude – 10, 1, and 0.1 μm/s. Modified spherical AFM probes were utilized to compress the cell bodies of neonatal rat cortical neurons in load, unload, reload and relaxation conditions. The cell response showed marked hysteretic features, strong non-linearities, and substantial time/rate dependencies. The rheological data were complemented with geometrical measurements of cell body morphology, i.e. cross-diameter and height estimates. A constitutive model, validated by the present experiments, is proposed to quantify the mechanical behavior of cortical neurons. The model aimed to correlate empirical findings with measurable degrees of (hyper-) elastic resilience and viscosity at the cell level. The proposed formulation, predicated upon previous constitutive model developments undertaken at the cortical tissue level, was implemented into a three-dimensional finite element framework. The simulated cell response was calibrated to the experimental measurements under the selected test conditions, providing a novel single cell model that could form the basis for further refinements. PMID:20971217

Quantifying intrinsic and extrinsic control of single-cell fates in cancer and stem/progenitor cell pedigrees with competing risks analysis

PubMed Central

Cornwell, J. A.; Hallett, R. M.; der Mauer, S. Auf; Motazedian, A.; Schroeder, T.; Draper, J. S.; Harvey, R. P.; Nordon, R. E.

2016-01-01

The molecular control of cell fate and behaviour is a central theme in biology. Inherent heterogeneity within cell populations requires that control of cell fate is studied at the single-cell level. Time-lapse imaging and single-cell tracking are powerful technologies for acquiring cell lifetime data, allowing quantification of how cell-intrinsic and extrinsic factors control single-cell fates over time. However, cell lifetime data contain complex features. Competing cell fates, censoring, and the possible inter-dependence of competing fates, currently present challenges to modelling cell lifetime data. Thus far such features are largely ignored, resulting in loss of data and introducing a source of bias. Here we show that competing risks and concordance statistics, previously applied to clinical data and the study of genetic influences on life events in twins, respectively, can be used to quantify intrinsic and extrinsic control of single-cell fates. Using these statistics we demonstrate that 1) breast cancer cell fate after chemotherapy is dependent on p53 genotype; 2) granulocyte macrophage progenitors and their differentiated progeny have concordant fates; and 3) cytokines promote self-renewal of cardiac mesenchymal stem cells by symmetric divisions. Therefore, competing risks and concordance statistics provide a robust and unbiased approach for evaluating hypotheses at the single-cell level. PMID:27250534

Multi-scale modelling of the dynamics of cell colonies: insights into cell-adhesion forces and cancer invasion from in silico simulations

PubMed Central

Schlüter, Daniela K.; Ramis-Conde, Ignacio; Chaplain, Mark A. J.

2015-01-01

Studying the biophysical interactions between cells is crucial to understanding how normal tissue develops, how it is structured and also when malfunctions occur. Traditional experiments try to infer events at the tissue level after observing the behaviour of and interactions between individual cells. This approach assumes that cells behave in the same biophysical manner in isolated experiments as they do within colonies and tissues. In this paper, we develop a multi-scale multi-compartment mathematical model that accounts for the principal biophysical interactions and adhesion pathways not only at a cell–cell level but also at the level of cell colonies (in contrast to the traditional approach). Our results suggest that adhesion/separation forces between cells may be lower in cell colonies than traditional isolated single-cell experiments infer. As a consequence, isolated single-cell experiments may be insufficient to deduce important biological processes such as single-cell invasion after detachment from a solid tumour. The simulations further show that kinetic rates and cell biophysical characteristics such as pressure-related cell-cycle arrest have a major influence on cell colony patterns and can allow for the development of protrusive cellular structures as seen in invasive cancer cell lines independent of expression levels of pro-invasion molecules. PMID:25519994

Single-junction solar cells with the optimum band gap for terrestrial concentrator applications

DOEpatents

Wanlass, M.W.

1994-12-27

A single-junction solar cell is described having the ideal band gap for terrestrial concentrator applications. Computer modeling studies of single-junction solar cells have shown that the presence of absorption bands in the direct spectrum has the effect of ''pinning'' the optimum band gap for a wide range of operating conditions at a value of 1.14[+-]0.02 eV. Efficiencies exceeding 30% may be possible at high concentration ratios for devices with the ideal band gap. 7 figures.

Single-junction solar cells with the optimum band gap for terrestrial concentrator applications

DOEpatents

Wanlass, Mark W.

1994-01-01

A single-junction solar cell having the ideal band gap for terrestrial concentrator applications. Computer modeling studies of single-junction solar cells have shown that the presence of absorption bands in the direct spectrum has the effect of "pinning" the optimum band gap for a wide range of operating conditions at a value of 1.14.+-.0.02 eV. Efficiencies exceeding 30% may be possible at high concentration ratios for devices with the ideal band gap.

A single cell model for pretreatment of wood by microwave explosion

Treesearch

Xianjun Li; Yongdong Zhou; Yonglin Yan; Zhiyong Cai; Fu Feng

2010-01-01

A theoretical model was developed to better understand the process of microwave explosion treatment of wood cells. The cell expansion and critical conditions concerning pressure and temperature of ray parenchyma cells in Eucalyptus urophylla were simulated during microwave pretreatment. The results indicate that longitudinal and circumferential stresses were generated...

A photoacoustic technique to measure the properties of single cells

NASA Astrophysics Data System (ADS)

Strohm, Eric M.; Berndl, Elizabeth S. L.; Kolios, Michael C.

2013-03-01

We demonstrate a new technique to non-invasively determine the diameter and sound speed of single cells using a combined ultrasonic and photoacoustic technique. Two cell lines, B16-F1 melanoma cells and MCF7 breast cancer cells were examined using this technique. Using a 200 MHz transducer, the ultrasound backscatter from a single cell in suspension was recorded. Immediately following, the cell was irradiated with a 532 nm laser and the resulting photoacoustic wave recorded by the same transducer. The melanoma cells contain optically absorbing melanin particles, which facilitated photoacoustic wave generation. MCF7 cells have negligible optical absorption at 532 nm; the cells were permeabilized and stained with trypan blue prior to measurements. The measured ultrasound and photoacoustic power spectra were compared to theoretical equations with the cell diameter and sound speed as variables (Anderson scattering model for ultrasound, and a thermoelastic expansion model for photoacoustics). The diameter and sound speed were extracted from the models where the spectral shape matched the measured signals. However the photoacoustic spectrum for the melanoma cell did not match theory, which is likely because melanin particles are located around the cytoplasm, and not within the nucleus. Therefore a photoacoustic finite element model of a cell was developed where the central region was not used to generate a photoacoustic wave. The resulting power spectrum was in better agreement with the measured signal than the thermoelastic expansion model. The MCF7 cell diameter obtained using the spectral matching method was 17.5 μm, similar to the optical measurement of 16 μm, while the melanoma cell diameter obtained was 22 μm, similar to the optical measurement of 21 μm. The sound speed measured from the MCF7 and melanoma cell was 1573 and 1560 m/s, respectively, which is within acceptable values that have been published in literature.

Design guidelines for an umbilical cord blood stem cell therapy quality assessment model

NASA Astrophysics Data System (ADS)

Januszewski, Witold S.; Michałek, Krzysztof; Yagensky, Oleksandr; Wardzińska, Marta

The paper enlists the pivotal guidelines for producing an empirical umbilical cord blood stem cell therapy quality assessment model. The methodology adapted was single equation linear model with domain knowledge derived from MEDAFAR classification. The resulting model is ready for therapeutical application.

Human organomics: a fresh approach to understanding human development using single-cell transcriptomics.

PubMed

Camp, J Gray; Treutlein, Barbara

2017-05-01

Innovative methods designed to recapitulate human organogenesis from pluripotent stem cells provide a means to explore human developmental biology. New technologies to sequence and analyze single-cell transcriptomes can deconstruct these 'organoids' into constituent parts, and reconstruct lineage trajectories during cell differentiation. In this Spotlight article we summarize the different approaches to performing single-cell transcriptomics on organoids, and discuss the opportunities and challenges of applying these techniques to generate organ-level, mechanistic models of human development and disease. Together, these technologies will move past characterization to the prediction of human developmental and disease-related phenomena. © 2017. Published by The Company of Biologists Ltd.

Monitoring the Single-Cell Stress Response of the Diatom Thalassiosira pseudonana by Quantitative Real-Time Reverse Transcription-PCR

PubMed Central

Shi, Xu; Gao, Weimin; Chao, Shih-hui

2013-01-01

Directly monitoring the stress response of microbes to their environments could be one way to inspect the health of microorganisms themselves, as well as the environments in which the microorganisms live. The ultimate resolution for such an endeavor could be down to a single-cell level. In this study, using the diatom Thalassiosira pseudonana as a model species, we aimed to measure gene expression responses of this organism to various stresses at a single-cell level. We developed a single-cell quantitative real-time reverse transcription-PCR (RT-qPCR) protocol and applied it to determine the expression levels of multiple selected genes under nitrogen, phosphate, and iron depletion stress conditions. The results, for the first time, provided a quantitative measurement of gene expression at single-cell levels in T. pseudonana and demonstrated that significant gene expression heterogeneity was present within the cell population. In addition, different expression patterns between single-cell- and bulk-cell-based analyses were also observed for all genes assayed in this study, suggesting that cell response heterogeneity needs to be taken into consideration in order to obtain accurate information that indicates the environmental stress condition. PMID:23315741

Monitoring the single-cell stress response of the diatom Thalassiosira pseudonana by quantitative real-time reverse transcription-PCR.

PubMed

Shi, Xu; Gao, Weimin; Chao, Shih-hui; Zhang, Weiwen; Meldrum, Deirdre R

2013-03-01

Directly monitoring the stress response of microbes to their environments could be one way to inspect the health of microorganisms themselves, as well as the environments in which the microorganisms live. The ultimate resolution for such an endeavor could be down to a single-cell level. In this study, using the diatom Thalassiosira pseudonana as a model species, we aimed to measure gene expression responses of this organism to various stresses at a single-cell level. We developed a single-cell quantitative real-time reverse transcription-PCR (RT-qPCR) protocol and applied it to determine the expression levels of multiple selected genes under nitrogen, phosphate, and iron depletion stress conditions. The results, for the first time, provided a quantitative measurement of gene expression at single-cell levels in T. pseudonana and demonstrated that significant gene expression heterogeneity was present within the cell population. In addition, different expression patterns between single-cell- and bulk-cell-based analyses were also observed for all genes assayed in this study, suggesting that cell response heterogeneity needs to be taken into consideration in order to obtain accurate information that indicates the environmental stress condition.

Estimation of turgor pressure through comparison between single plant cell and pressurized shell mechanics

NASA Astrophysics Data System (ADS)

Durand-Smet, P.; Gauquelin, E.; Chastrette, N.; Boudaoud, A.; Asnacios, A.

2017-10-01

While plant growth is well known to rely on turgor pressure, it is challenging to quantify the contribution of turgor pressure to plant cell rheology. Here we used a custom-made micro-rheometer to quantify the viscoelastic behavior of isolated plant cells while varying their internal turgor pressure. To get insight into how plant cells adapt their internal pressure to the osmolarity of their medium, we compared the mechanical behavior of single plant cells to that of a simple, passive, pressurized shell: a soccer ball. While both systems exhibited the same qualitative behavior, a simple mechanical model allowed us to quantify turgor pressure regulation at the single cell scale.

Characteristics of single Ca(2+) channel kinetics in feline hypertrophied ventricular myocytes.

PubMed

Yang, Xiangjun; Hui, Jie; Jiang, Tingbo; Song, Jianping; Liu, Zhihua; Jiang, Wenping

2002-04-01

To explore the mechanism underlying the prolongation of action potential and delayed inactivation of the L-type Ca(2+) (I(Ca, L)) current in a feline model of left ventricular system hypertension and concomitant hypertrophy. Single Ca(2+) channel properties in myocytes isolated from normal and pressure overloaded cat left ventricles were studied, using patch-clamp techniques. Left ventricular pressure overload was induced by partial ligation of the ascending aorta for 4 - 6 weeks. The amplitude of single Ca(2+) channel current evoked by depolarizing pulses from -40 mV to 0 mV was 1.02 +/- 0.03 pA in normal cells and 1.05 +/- 0.03 pA in hypertrophied cells, and there was no difference in single channel current-voltage relationships between the groups since slope conductance was 26.2 +/- 1.0 pS in normal and hypertrophied cells, respectively. Peak amplitudes of the ensemble-averaged single Ca(2+) channel currents were not different between the two groups of cells. However, the amplitude of this averaged current at the end of the clamp pulse was significantly larger in hypertrophied cells than in normal cells. Open-time histograms revealed that open-time distribution was fitted by a single exponential function in channels of normal cells and by a two exponential function in channels of hypertrophied cells. The number of long-lasting openings was increased in channels of hypertrophied cells, and therefore the calculated mean open time of the channel was significantly longer compared to normal controls. Kinetic changes in the Ca(2+) channel may underlie both hypertrophy-associated delayed inactivation of the Ca(2+) current and, in part, the pressure overload-induced action potential lengthening in this cat model of ventricular left systolic hypertension and hypertrophy.

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.

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

PubMed Central

Sung, Myong-Hee

2013-01-01

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

Cell Migration in 1D and 2D Nanofiber Microenvironments.

PubMed

Estabridis, Horacio M; Jana, Aniket; Nain, Amrinder; Odde, David J

2018-03-01

Understanding how cells migrate in fibrous environments is important in wound healing, immune function, and cancer progression. A key question is how fiber orientation and network geometry influence cell movement. Here we describe a quantitative, modeling-based approach toward identifying the mechanisms by which cells migrate in fibrous geometries having well controlled orientation. Specifically, U251 glioblastoma cells were seeded onto non-electrospinning Spinneret based tunable engineering parameters fiber substrates that consist of networks of suspended 400 nm diameter nanofibers. Cells were classified based on the local fiber geometry and cell migration dynamics observed by light microscopy. Cells were found in three distinct geometries: adhering two a single fiber, adhering to two parallel fibers, and adhering to a network of orthogonal fibers. Cells adhering to a single fiber or two parallel fibers can only move in one dimension along the fiber axis, whereas cells on a network of orthogonal fibers can move in two dimensions. We found that cells move faster and more persistently in 1D geometries than in 2D, with cell migration being faster on parallel fibers than on single fibers. To explain these behaviors mechanistically, we simulated cell migration in the three different geometries using a motor-clutch based model for cell traction forces. Using nearly identical parameter sets for each of the three cases, we found that the simulated cells naturally replicated the reduced migration in 2D relative to 1D geometries. In addition, the modestly faster 1D migration on parallel fibers relative to single fibers was captured using a correspondingly modest increase in the number of clutches to reflect increased surface area of adhesion on parallel fibers. Overall, the integrated modeling and experimental analysis shows that cell migration in response to varying fibrous geometries can be explained by a simple mechanical readout of geometry via a motor-clutch mechanism.

Role of Multicellular Aggregates in Biofilm Formation

PubMed Central

Kragh, Kasper N.; Hutchison, Jaime B.; Melaugh, Gavin; Rodesney, Chris; Roberts, Aled E. L.; Irie, Yasuhiko; Jensen, Peter Ø.; Diggle, Stephen P.; Allen, Rosalind J.

2016-01-01

ABSTRACT In traditional models of in vitro biofilm development, individual bacterial cells seed a surface, multiply, and mature into multicellular, three-dimensional structures. Much research has been devoted to elucidating the mechanisms governing the initial attachment of single cells to surfaces. However, in natural environments and during infection, bacterial cells tend to clump as multicellular aggregates, and biofilms can also slough off aggregates as a part of the dispersal process. This makes it likely that biofilms are often seeded by aggregates and single cells, yet how these aggregates impact biofilm initiation and development is not known. Here we use a combination of experimental and computational approaches to determine the relative fitness of single cells and preformed aggregates during early development of Pseudomonas aeruginosa biofilms. We find that the relative fitness of aggregates depends markedly on the density of surrounding single cells, i.e., the level of competition for growth resources. When competition between aggregates and single cells is low, an aggregate has a growth disadvantage because the aggregate interior has poor access to growth resources. However, if competition is high, aggregates exhibit higher fitness, because extending vertically above the surface gives cells at the top of aggregates better access to growth resources. Other advantages of seeding by aggregates, such as earlier switching to a biofilm-like phenotype and enhanced resilience toward antibiotics and immune response, may add to this ecological benefit. Our findings suggest that current models of biofilm formation should be reconsidered to incorporate the role of aggregates in biofilm initiation. PMID:27006463

Modeling Cell Size Regulation: From Single-Cell-Level Statistics to Molecular Mechanisms and Population-Level Effects.

PubMed

Ho, Po-Yi; Lin, Jie; Amir, Ariel

2018-05-20

Most microorganisms regulate their cell size. In this article, we review some of the mathematical formulations of the problem of cell size regulation. We focus on coarse-grained stochastic models and the statistics that they generate. We review the biologically relevant insights obtained from these models. We then describe cell cycle regulation and its molecular implementations, protein number regulation, and population growth, all in relation to size regulation. Finally, we discuss several future directions for developing understanding beyond phenomenological models of cell size regulation.

On the relationship between cell cycle analysis with ergodic principles and age-structured cell population models.

PubMed

Kuritz, K; Stöhr, D; Pollak, N; Allgöwer, F

2017-02-07

Cyclic processes, in particular the cell cycle, are of great importance in cell biology. Continued improvement in cell population analysis methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell omics made mathematical methods based on ergodic principles a powerful tool in studying these processes. In this paper, we establish the relationship between cell cycle analysis with ergodic principles and age structured population models. To this end, we describe the progression of a single cell through the cell cycle by a stochastic differential equation on a one dimensional manifold in the high dimensional dataspace of cell cycle markers. Given the assumption that the cell population is in a steady state, we derive transformation rules which transform the number density on the manifold to the steady state number density of age structured population models. Our theory facilitates the study of cell cycle dependent processes including local molecular events, cell death and cell division from high dimensional "snapshot" data. Ergodic analysis can in general be applied to every process that exhibits a steady state distribution. By combining ergodic analysis with age structured population models we furthermore provide the theoretic basis for extensions of ergodic principles to distribution that deviate from their steady state. Copyright © 2016 Elsevier Ltd. All rights reserved.

Single cell Hi-C reveals cell-to-cell variability in chromosome structure

PubMed Central

Schoenfelder, Stefan; Yaffe, Eitan; Dean, Wendy; Laue, Ernest D.; Tanay, Amos; Fraser, Peter

2013-01-01

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. PMID:24067610

Reverse-engineering of gene networks for regulating early blood development from single-cell measurements.

PubMed

Wei, Jiangyong; Hu, Xiaohua; Zou, Xiufen; Tian, Tianhai

2017-12-28

Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information. This work designs an integrated approach to reverse-engineer gene networks for regulating early blood development based on singel-cell experimental observations. The wanderlust algorithm is initially used to develop the pseudo-trajectory for the activities of a number of genes. Since the gene expression data in the developed pseudo-trajectory show large fluctuations, we then use Gaussian process regression methods to smooth the gene express data in order to obtain pseudo-trajectories with much less fluctuations. The proposed integrated framework consists of both bioinformatics algorithms to reconstruct the regulatory network and mathematical models using differential equations to describe the dynamics of gene expression. The developed approach is applied to study the network regulating early blood cell development. A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes. Numerical results suggests that the proposed model is able to match experimental data very well. We also examine the networks with more regulatory relations and numerical results show that more regulations may exist. We test the possibility of auto-regulation but numerical simulations do not support the positive auto-regulation. In addition, robustness is used as an importantly additional criterion to select candidate networks. The research results in this work shows that the developed approach is an efficient and effective method to reverse-engineer gene networks using single-cell experimental observations.

Modeling the Effects of Solar Cell Distribution on Optical Cross Section for Solar Panel Simulation

DTIC Science & Technology

2012-09-01

cell material. The solar panel was created as a CAD model and simulated with the imaging facility parameters with TASAT. TASAT uses a BRDF to apply...1 MODELING THE EFFECTS OF SOLAR CELL DISTRIBUTION ON OPTICAL CROSS SECTION FOR SOLAR PANEL SIMULATION Kelly Feirstine Meiling Klein... model of a solar panel with various solar cell tip and tilt distribution statistics. Modeling a solar panel as a single sheet of “solar cell” material

AN IN VITRO MODEL FOR MURINE URETERIC EPITHELIAL CELLS

EPA Science Inventory

This report presents a model developed to study growth and differentiation of primary cultures of ureteric epithelial cells from embryonic C57BL/6N mouse urinary tracts. Single cells were resuspended in medium and plated onto transwells coated with collagen IV and laminin. Basa...

Single-Cell RNA-Seq Reveals Transcriptional Heterogeneity in Latent and Reactivated HIV-Infected Cells.

PubMed

Golumbeanu, Monica; Cristinelli, Sara; Rato, Sylvie; Munoz, Miguel; Cavassini, Matthias; Beerenwinkel, Niko; Ciuffi, Angela

2018-04-24

Despite effective treatment, HIV can persist in latent reservoirs, which represent a major obstacle toward HIV eradication. Targeting and reactivating latent cells is challenging due to the heterogeneous nature of HIV-infected cells. Here, we used a primary model of HIV latency and single-cell RNA sequencing to characterize transcriptional heterogeneity during HIV latency and reactivation. Our analysis identified transcriptional programs leading to successful reactivation of HIV expression. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Advancing haematopoietic stem and progenitor cell biology through single-cell profiling.

PubMed

Hamey, Fiona K; Nestorowa, Sonia; Wilson, Nicola K; Göttgens, Berthold

2016-11-01

Haematopoietic stem and progenitor cells (HSPCs) sit at the top of the haematopoietic hierarchy, and their fate choices need to be carefully controlled to ensure balanced production of all mature blood cell types. As cell fate decisions are made at the level of the individual cells, recent technological advances in measuring gene and protein expression in increasingly large numbers of single cells have been rapidly adopted to study both normal and pathological HSPC function. In this review we emphasise the importance of combining the correct computational models with single-cell experimental techniques, and illustrate how such integrated approaches have been used to resolve heterogeneities in populations, reconstruct lineage differentiation, identify regulatory relationships and link molecular profiling to cellular function. © 2016 Federation of European Biochemical Societies.

Modelling biofilm-induced formation damage and biocide treatment in subsurface geosystems

PubMed Central

Ezeuko, C C; Sen, A; Gates, I D

2013-01-01

Biofilm growth in subsurface porous media, and its treatment with biocides (antimicrobial agents), involves a complex interaction of biogeochemical processes which provide non-trivial mathematical modelling challenges. Although there are literature reports of mathematical models to evaluate biofilm tolerance to biocides, none of these models have investigated biocide treatment of biofilms growing in interconnected porous media with flow. In this paper, we present a numerical investigation using a pore network model of biofilm growth, formation damage and biocide treatment. The model includes three phases (aqueous, adsorbed biofilm, and solid matrix), a single growth-limiting nutrient and a single biocide dissolved in the water. Biofilm is assumed to contain a single species of microbe, in which each cell can be a viable persister, a viable non-persister, or non-viable (dead). Persisters describe small subpopulation of cells which are tolerant to biocide treatment. Biofilm tolerance to biocide treatment is regulated by persister cells and includes ‘innate’ and ‘biocide-induced’ factors. Simulations demonstrate that biofilm tolerance to biocides can increase with biofilm maturity, and that biocide treatment alone does not reverse biofilm-induced formation damage. Also, a successful application of biological permeability conformance treatment involving geologic layers with flow communication is more complicated than simply engineering the attachment of biofilm-forming cells at desired sites. PMID:23164434

Toward improving fine needle aspiration cytology by applying Raman microspectroscopy

NASA Astrophysics Data System (ADS)

Becker-Putsche, Melanie; Bocklitz, Thomas; Clement, Joachim; Rösch, Petra; Popp, Jürgen

2013-04-01

Medical diagnosis of biopsies performed by fine needle aspiration has to be very reliable. Therefore, pathologists/cytologists need additional biochemical information on single cancer cells for an accurate diagnosis. Accordingly, we applied three different classification models for discriminating various features of six breast cancer cell lines by analyzing Raman microspectroscopic data. The statistical evaluations are implemented by linear discriminant analysis (LDA) and support vector machines (SVM). For the first model, a total of 61,580 Raman spectra from 110 single cells are discriminated at the cell-line level with an accuracy of 99.52% using an SVM. The LDA classification based on Raman data achieved an accuracy of 94.04% by discriminating cell lines by their origin (solid tumor versus pleural effusion). In the third model, Raman cell spectra are classified by their cancer subtypes. LDA results show an accuracy of 97.45% and specificities of 97.78%, 99.11%, and 98.97% for the subtypes basal-like, HER2+/ER-, and luminal, respectively. These subtypes are confirmed by gene expression patterns, which are important prognostic features in diagnosis. This work shows the applicability of Raman spectroscopy and statistical data handling in analyzing cancer-relevant biochemical information for advanced medical diagnosis on the single-cell level.

Evaluation of Material Models within LS-DYNA(Registered TradeMark) for a Kevlar/Epoxy Composite Honeycomb

NASA Technical Reports Server (NTRS)

Polanco, Michael A.; Kellas, Sotiris; Jackson, Karen

2009-01-01

The performance of material models to simulate a novel composite honeycomb Deployable Energy Absorber (DEA) was evaluated using the nonlinear explicit dynamic finite element code LS-DYNA(Registered TradeMark). Prototypes of the DEA concept were manufactured using a Kevlar/Epoxy composite material in which the fibers are oriented at +/-45 degrees with respect to the loading axis. The development of the DEA has included laboratory tests at subcomponent and component levels such as three-point bend testing of single hexagonal cells, dynamic crush testing of single multi-cell components, and impact testing of a full-scale fuselage section fitted with a system of DEA components onto multi-terrain environments. Due to the thin nature of the cell walls, the DEA was modeled using shell elements. In an attempt to simulate the dynamic response of the DEA, it was first represented using *MAT_LAMINATED_COMPOSITE_FABRIC, or *MAT_58, in LS-DYNA. Values for each parameter within the material model were generated such that an in-plane isotropic configuration for the DEA material was assumed. Analytical predictions showed that the load-deflection behavior of a single-cell during three-point bending was within the range of test data, but predicted the DEA crush response to be very stiff. In addition, a *MAT_PIECEWISE_LINEAR_PLASTICITY, or *MAT_24, material model in LS-DYNA was developed, which represented the Kevlar/Epoxy composite as an isotropic elastic-plastic material with input from +/-45 degrees tensile coupon data. The predicted crush response matched that of the test and localized folding patterns of the DEA were captured under compression, but the model failed to predict the single-cell three-point bending response.

Single-cell transcriptomics for microbial eukaryotes.

PubMed

Kolisko, Martin; Boscaro, Vittorio; Burki, Fabien; Lynn, Denis H; Keeling, Patrick J

2014-11-17

One of the greatest hindrances to a comprehensive understanding of microbial genomics, cell biology, ecology, and evolution is that most microbial life is not in culture. Solutions to this problem have mainly focused on whole-community surveys like metagenomics, but these analyses inevitably loose information and present particular challenges for eukaryotes, which are relatively rare and possess large, gene-sparse genomes. Single-cell analyses present an alternative solution that allows for specific species to be targeted, while retaining information on cellular identity, morphology, and partitioning of activities within microbial communities. Single-cell transcriptomics, pioneered in medical research, offers particular potential advantages for uncultivated eukaryotes, but the efficiency and biases have not been tested. Here we describe a simple and reproducible method for single-cell transcriptomics using manually isolated cells from five model ciliate species; we examine impacts of amplification bias and contamination, and compare the efficacy of gene discovery to traditional culture-based transcriptomics. Gene discovery using single-cell transcriptomes was found to be comparable to mass-culture methods, suggesting single-cell transcriptomics is an efficient entry point into genomic data from the vast majority of eukaryotic biodiversity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modifying infrared scattering effects of single yeast cells with plasmonic metal mesh

NASA Astrophysics Data System (ADS)

Malone, Marvin A.; Prakash, Suraj; Heer, Joseph M.; Corwin, Lloyd D.; Cilwa, Katherine E.; Coe, James V.

2010-11-01

The scattering effects in the infrared (IR) spectra of single, isolated bread yeast cells (Saccharomyces cerevisiae) on a ZnSe substrate and in metal microchannels have been probed by Fourier transform infrared imaging microspectroscopy. Absolute extinction [(3.4±0.6)×10-7 cm2 at 3178 cm-1], scattering, and absorption cross sections for a single yeast cell and a vibrational absorption spectrum have been determined by comparing it to the scattering properties of single, isolated, latex microspheres (polystyrene, 5.0 μm in diameter) on ZnSe, which are well modeled by the Mie scattering theory. Single yeast cells were then placed into the holes of the IR plasmonic mesh, i.e., metal films with arrays of subwavelength holes, yielding "scatter-free" IR absorption spectra, which have undistorted vibrational lineshapes and a rising generic IR absorption baseline. Absolute extinction, scattering, and absorption spectral profiles were determined for a single, ellipsoidal yeast cell to characterize the interplay of these effects.

Application of finite element substructuring to composite micromechanics. M.S. Thesis - Akron Univ., May 1984

NASA Technical Reports Server (NTRS)

Caruso, J. J.

1984-01-01

Finite element substructuring is used to predict unidirectional fiber composite hygral (moisture), thermal, and mechanical properties. COSMIC NASTRAN and MSC/NASTRAN are used to perform the finite element analysis. The results obtained from the finite element model are compared with those obtained from the simplified composite micromechanics equations. A unidirectional composite structure made of boron/HM-epoxy, S-glass/IMHS-epoxy and AS/IMHS-epoxy are studied. The finite element analysis is performed using three dimensional isoparametric brick elements and two distinct models. The first model consists of a single cell (one fiber surrounded by matrix) to form a square. The second model uses the single cell and substructuring to form a nine cell square array. To compare computer time and results with the nine cell superelement model, another nine cell model is constructed using conventional mesh generation techniques. An independent computer program consisting of the simplified micromechanics equation is developed to predict the hygral, thermal, and mechanical properties for this comparison. The results indicate that advanced techniques can be used advantageously for fiber composite micromechanics.

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.

Evaluation of digital real-time PCR assay as a molecular diagnostic tool for single-cell analysis.

PubMed

Chang, Chia-Hao; Mau-Hsu, Daxen; Chen, Ke-Cheng; Wei, Cheng-Wey; Chiu, Chiung-Ying; Young, Tai-Horng

2018-02-21

In a single-cell study, isolating and identifying single cells are essential, but these processes often require a large investment of time or money. The aim of this study was to isolate and analyse single cells using a novel platform, the PanelChip™ Analysis System, which includes 2500 microwells chip and a digital real-time polymerase chain reaction (dqPCR) assay, in comparison with a standard PCR (qPCR) assay. Through the serial dilution of a known concentration standard, namely pUC19, the accuracy and sensitivity levels of two methodologies were compared. The two systems were tested on the basis of expression levels of the genetic markers vimentin, E-cadherin, N-cadherin and GAPDH in A549 lung carcinoma cells at two known concentrations. Furthermore, the influence of a known PCR inhibitor commonly found in blood samples, heparin, was evaluated in both methodologies. Finally, mathematical models were proposed and separation method of single cells was verified; moreover, gene expression levels during epithelial-mesenchymal transition in single cells under TGFβ1 treatment were measured. The drawn conclusion is that dqPCR performed using PanelChip™ is superior to the standard qPCR in terms of sensitivity, precision, and heparin tolerance. The dqPCR assay is a potential tool for clinical diagnosis and single-cell applications.

Pharmacodynamic Modeling of Cell Cycle Effects for Gemcitabine and Trabectedin Combinations in Pancreatic Cancer Cells

PubMed Central

Miao, Xin; Koch, Gilbert; Ait-Oudhia, Sihem; Straubinger, Robert M.; Jusko, William J.

2016-01-01

Combinations of gemcitabine and trabectedin exert modest synergistic cytotoxic effects on two pancreatic cancer cell lines. Here, systems pharmacodynamic (PD) models that integrate cellular response data and extend a prototype model framework were developed to characterize dynamic changes in cell cycle phases of cancer cell subpopulations in response to gemcitabine and trabectedin as single agents and in combination. Extensive experimental data were obtained for two pancreatic cancer cell lines (MiaPaCa-2 and BxPC-3), including cell proliferation rates over 0–120 h of drug exposure, and the fraction of cells in different cell cycle phases or apoptosis. Cell cycle analysis demonstrated that gemcitabine induced cell cycle arrest in S phase, and trabectedin induced transient cell cycle arrest in S phase that progressed to G2/M phase. Over time, cells in the control group accumulated in G0/G1 phase. Systems cell cycle models were developed based on observed mechanisms and were used to characterize both cell proliferation and cell numbers in the sub G1, G0/G1, S, and G2/M phases in the control and drug-treated groups. The proposed mathematical models captured well both single and joint effects of gemcitabine and trabectedin. Interaction parameters were applied to quantify unexplainable drug-drug interaction effects on cell cycle arrest in S phase and in inducing apoptosis. The developed models were able to identify and quantify the different underlying interactions between gemcitabine and trabectedin, and captured well our large datasets in the dimensions of time, drug concentrations, and cellular subpopulations. PMID:27895579

Efficient production of erythroid, megakaryocytic and myeloid cells, using single cell-derived iPSC colony differentiation.

PubMed

Hansen, Marten; Varga, Eszter; Aarts, Cathelijn; Wust, Tatjana; Kuijpers, Taco; von Lindern, Marieke; van den Akker, Emile

2018-04-28

Hematopoietic differentiation of human induced pluripotent stem cells (iPSCs) provide opportunities not only for fundamental research and disease modelling/drug testing but also for large-scale production of blood effector cells for future clinical application. Although there are multiple ways to differentiate human iPSCs towards hematopoietic lineages, there is a need to develop reproducible and robust protocols. Here we introduce an efficient way to produce three major blood cell types using a standardized differentiation protocol that starts with a single hematopoietic initiation step. This system is feeder-free, avoids EB-formation, starts with a hematopoietic initiation step based on a novel single cell-derived iPSC colony differentiation and produces multi-potential progenitors within 8-10 days. Followed by lineage-specific growth factor supplementation these cells can be matured into well characterized erythroid, megakaryocytic and myeloid cells with high-purity, without transcription factor overexpression or any kind of pre-purification step. This standardized differentiation system provides a simple platform to produce specific blood cells in a reproducible manner for hematopoietic development studies, disease modelling, drug testing and the potential for future therapeutic applications. Copyright © 2018. Published by Elsevier B.V.

An Empirically Calibrated Model of Cell Fate Decision Following Viral Infection

NASA Astrophysics Data System (ADS)

Coleman, Seth; Igoshin, Oleg; Golding, Ido

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

Responses to single photons in visual cells of Limulus

PubMed Central

Borsellino, A.; Fuortes, M. G. F.

1968-01-01

1. A system proposed in a previous article as a model of responses of visual cells has been analysed with the purpose of predicting the features of responses to single absorbed photons. 2. As a result of this analysis, the stochastic variability of responses has been expressed as a function of the amplification of the system. 3. The theoretical predictions have been compared to the results obtained by recording electrical responses of visual cells of Limulus to flashes delivering only few photons. 4. Experimental responses to single photons have been tentatively identified and it was shown that the stochastic variability of these responses is similar to that predicted for a model with a multiplication factor of at least twenty-five. 5. These results lead to the conclusion that the processes responsible for visual responses incorporate some form of amplification. This conclusion may prove useful for identifying the physical mechanisms underlying the transducer action of visual cells. PMID:5664231

cgCorrect: a method to correct for confounding cell-cell variation due to cell growth in single-cell transcriptomics

NASA Astrophysics Data System (ADS)

Blasi, Thomas; Buettner, Florian; Strasser, Michael K.; Marr, Carsten; Theis, Fabian J.

2017-06-01

Accessing gene expression at a single-cell level has unraveled often large heterogeneity among seemingly homogeneous cells, which remains obscured when using traditional population-based approaches. The computational analysis of single-cell transcriptomics data, however, still imposes unresolved challenges with respect to normalization, visualization and modeling the data. One such issue is differences in cell size, which introduce additional variability into the data and for which appropriate normalization techniques are needed. Otherwise, these differences in cell size may obscure genuine heterogeneities among cell populations and lead to overdispersed steady-state distributions of mRNA transcript numbers. We present cgCorrect, a statistical framework to correct for differences in cell size that are due to cell growth in single-cell transcriptomics data. We derive the probability for the cell-growth-corrected mRNA transcript number given the measured, cell size-dependent mRNA transcript number, based on the assumption that the average number of transcripts in a cell increases proportionally to the cell’s volume during the cell cycle. cgCorrect can be used for both data normalization and to analyze the steady-state distributions used to infer the gene expression mechanism. We demonstrate its applicability on both simulated data and single-cell quantitative real-time polymerase chain reaction (PCR) data from mouse blood stem and progenitor cells (and to quantitative single-cell RNA-sequencing data obtained from mouse embryonic stem cells). We show that correcting for differences in cell size affects the interpretation of the data obtained by typically performed computational analysis.

DEsingle for detecting three types of differential expression in single-cell RNA-seq data.

PubMed

Miao, Zhun; Deng, Ke; Wang, Xiaowo; Zhang, Xuegong

2018-04-24

The excessive amount of zeros in single-cell RNA-seq data include "real" zeros due to the on-off nature of gene transcription in single cells and "dropout" zeros due to technical reasons. Existing differential expression (DE) analysis methods cannot distinguish these two types of zeros. We developed an R package DEsingle which employed Zero-Inflated Negative Binomial model to estimate the proportion of real and dropout zeros and to define and detect 3 types of DE genes in single-cell RNA-seq data with higher accuracy. The R package DEsingle is freely available at https://github.com/miaozhun/DEsingle and is under Bioconductor's consideration now. zhangxg@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online.

On the micro-indentation of plant cells in a tissue context

NASA Astrophysics Data System (ADS)

Mosca, Gabriella; Sapala, Aleksandra; Strauss, Soeren; Routier-Kierzkowska, Anne-Lise; Smith, Richard S.

2017-02-01

The effect of geometry on cell stiffness measured with micro-indentation techniques has been explored in single cells, however it is unclear if results on single cells can be readily transferred to indentation experiments performed on a tissue in vivo. Here we explored this question by using simulation models of osmotic treatments and micro-indentation experiments on 3D multicellular tissues with the finite element method. We found that the cellular context does affect measured cell stiffness, and that several cells of context in each direction are required for optimal results. We applied the model to micro-indentation data obtained with cellular force microscopy on the sepal of A. thaliana, and found that differences in measured stiffness could be explained by cellular geometry, and do not necessarily indicate differences in cell wall material properties or turgor pressure.

Radioluminescence Microscopy: Measuring the Heterogeneous Uptake of Radiotracers in Single Living Cells

PubMed Central

Pratx, Guillem; Chen, Kai; Sun, Conroy; Martin, Lynn; Carpenter, Colin M.; Olcott, Peter D.; Xing, Lei

2012-01-01

Radiotracers play an important role in interrogating molecular processes both in vitro and in vivo. However, current methods are limited to measuring average radiotracer uptake in large cell populations and, as a result, lack the ability to quantify cell-to-cell variations. Here we apply a new technique, termed radioluminescence microscopy, to visualize radiotracer uptake in single living cells, in a standard fluorescence microscopy environment. In this technique, live cells are cultured sparsely on a thin scintillator plate and incubated with a radiotracer. Light produced following beta decay is measured using a highly sensitive microscope. Radioluminescence microscopy revealed strong heterogeneity in the uptake of [18F]fluoro-deoxyglucose (FDG) in single cells, which was found consistent with fluorescence imaging of a glucose analog. We also verified that dynamic uptake of FDG in single cells followed the standard two-tissue compartmental model. Last, we transfected cells with a fusion PET/fluorescence reporter gene and found that uptake of FHBG (a PET radiotracer for transgene expression) coincided with expression of the fluorescent protein. Together, these results indicate that radioluminescence microscopy can visualize radiotracer uptake with single-cell resolution, which may find a use in the precise characterization of radiotracers. PMID:23056276

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

PubMed

de Vargas Roditi, Laura; Claassen, Manfred

2015-08-01

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

Gravity Research on Plants: Use of Single-Cell Experimental Models

PubMed Central

Chebli, Youssef; Geitmann, Anja

2011-01-01

Future space missions and implementation of permanent bases on Moon and Mars will greatly depend on the availability of ambient air and sustainable food supply. Therefore, understanding the effects of altered gravity conditions on plant metabolism and growth is vital for space missions and extra-terrestrial human existence. In this mini-review we summarize how plant cells are thought to perceive changes in magnitude and orientation of the gravity vector. The particular advantages of several single-celled model systems for gravity research are explored and an overview over recent advancements and potential use of these systems is provided. PMID:22639598

Computational Modeling of Single-Cell Migration: The Leading Role of Extracellular Matrix Fibers

PubMed Central

Schlüter, Daniela K.; Ramis-Conde, Ignacio; Chaplain, Mark A.J.

2012-01-01

Cell migration is vitally important in a wide variety of biological contexts ranging from embryonic development and wound healing to malignant diseases such as cancer. It is a very complex process that is controlled by intracellular signaling pathways as well as the cell’s microenvironment. Due to its importance and complexity, it has been studied for many years in the biomedical sciences, and in the last 30 years it also received an increasing amount of interest from theoretical scientists and mathematical modelers. Here we propose a force-based, individual-based modeling framework that links single-cell migration with matrix fibers and cell-matrix interactions through contact guidance and matrix remodelling. With this approach, we can highlight the effect of the cell’s environment on its migration. We investigate the influence of matrix stiffness, matrix architecture, and cell speed on migration using quantitative measures that allow us to compare the results to experiments. PMID:22995486

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

Dielectrophoretic spectra of single cells determined by feedback-controlled levitation.

PubMed Central

Kaler, K V; Jones, T B

1990-01-01

In this paper we have utilized the principle of dielectrophoresis (DEP) to develop an apparatus to stably levitate single biological cells using a digital feedback control scheme. Using this apparatus, the positive DEP spectra of both Canola plant protoplast and ligament fibroblast cells have been measured over a wide range of frequencies (1 kHz to 50 MHz) and suspending medium conductivities (11-800 muS/cm). The experimental data thus obtained have been interpreted in terms of a simple spherical cell model. Furthermore, utilizing such a model, we have shown that various cellular parameters of interest can be readily obtained from the measured DEP levitation spectrum. Specifically, the effective membrane capacitance of single cells has been determined. Values of 0.47 +/- 0.03 muF/cm2 for Canola protoplasts and 1.52 +/- 0.26 muF/cm2 for ligament fibroblasts thus obtained are consistent with those determined by other existing electrical methods. Images FIGURE A1 PMID:2317544

On the Thermal Model of Transverse Flow of Unidirectional Materials

NASA Technical Reports Server (NTRS)

Tai, Hsiang

2002-01-01

The thermal model for transverse heat flow of having single filament in a unit cell is extended. In this model, we proposed that two circular filaments in a unit cell of square packing array and obtained the transverse thermal conductivity of an unidirectional material.

Intravital characterization of tumor cell migration in pancreatic cancer

PubMed Central

Beerling, Evelyne; Oosterom, Ilse; Voest, Emile; Lolkema, Martijn; van Rheenen, Jacco

2016-01-01

ABSTRACT Curing pancreatic cancer is difficult as metastases often determine the poor clinical outcome. To gain more insight into the metastatic behavior of pancreatic cancer cells, we characterized migratory cells in primary pancreatic tumors using intravital microscopy. We visualized the migratory behavior of primary tumor cells of a genetically engineered pancreatic cancer mouse model and found that pancreatic tumor cells migrate with a mesenchymal morphology as single individual cells or collectively as a stream of non-cohesive single motile cells. These findings may improve our ability to conceive treatments that block metastatic behavior. PMID:28243522

A Cellular Automata-based Model for Simulating Restitution Property in a Single Heart Cell.

PubMed

Sabzpoushan, Seyed Hojjat; Pourhasanzade, Fateme

2011-01-01

Ventricular fibrillation is the cause of the most sudden mortalities. Restitution is one of the specific properties of ventricular cell. The recent findings have clearly proved the correlation between the slope of restitution curve with ventricular fibrillation. This; therefore, mandates the modeling of cellular restitution to gain high importance. A cellular automaton is a powerful tool for simulating complex phenomena in a simple language. A cellular automaton is a lattice of cells where the behavior of each cell is determined by the behavior of its neighboring cells as well as the automata rule. In this paper, a simple model is depicted for the simulation of the property of restitution in a single cardiac cell using cellular automata. At first, two state variables; action potential and recovery are introduced in the automata model. In second, automata rule is determined and then recovery variable is defined in such a way so that the restitution is developed. In order to evaluate the proposed model, the generated restitution curve in our study is compared with the restitution curves from the experimental findings of valid sources. Our findings indicate that the presented model is not only capable of simulating restitution in cardiac cell, but also possesses the capability of regulating the restitution curve.

Hypoxia-Targeting Drug Evofosfamide (TH-302) Enhances Sunitinib Activity in Neuroblastoma Xenograft Models.

PubMed

Kumar, Sushil; Sun, Jessica D; Zhang, Libo; Mokhtari, Reza Bayat; Wu, Bing; Meng, Fanying; Liu, Qian; Bhupathi, Deepthi; Wang, Yan; Yeger, Herman; Hart, Charles; Baruchel, Sylvain

2018-05-23

Antiangiogenic therapy has shown promising results in preclinical and clinical trials. However, tumor cells acquire resistance to this therapy by gaining ability to survive and proliferate under hypoxia induced by antiangiogenic therapy. Combining antiangiogenic therapy with hypoxia-activated prodrugs can overcome this limitation. Here, we have tested the combination of antiangiogenic drug sunitinib in combination with hypoxia-activated prodrug evofosfamide in neuroblastoma. In vitro, neuroblastoma cell line SK-N-BE(2) was 40-folds sensitive to evofosfamide under hypoxia compared to normoxia. In IV metastatic model, evofosfamide significantly increased mice survival compared to the vehicle (P=.02). In SK-N-BE(2) subcutaneous xenograft model, we tested two different treatment regimens using 30 mg/kg sunitinib and 50 mg/kg evofosfamide. Here, sunitinib therapy when started along with evofosfamide treatment showed higher efficacy compared to single agents in subcutaneous SK-N-BE(2) xenograft model, whereas sunitinib when started 7 days after evofosfamide treatment did not have any advantage compared to treatment with either single agent. Immunofluorescence of tumor sections revealed higher number of apoptotic cells and hypoxic areas compared to either single agent when both treatments were started together. Treatment with 80 mg/kg sunitinib with 50 mg/kg evofosfamide was significantly superior to single agents in both xenograft and metastatic models. This study confirms the preclinical efficacy of sunitinib and evofosfamide in murine models of aggressive neuroblastoma. Sunitinib enhances the efficacy of evofosfamide by increasing hypoxic areas, and evofosfamide targets hypoxic tumor cells. Consequently, each drug enhances the activity of the other. Copyright © 2018. Published by Elsevier Inc.

Estimating intrinsic and extrinsic noise from single-cell gene expression measurements

PubMed Central

Fu, Audrey Qiuyan; Pachter, Lior

2017-01-01

Gene expression is stochastic and displays variation (“noise”) both within and between cells. Intracellular (intrinsic) variance can be distinguished from extracellular (extrinsic) variance by applying the law of total variance to data from two-reporter assays that probe expression of identically regulated gene pairs in single cells. We examine established formulas [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.] for the estimation of intrinsic and extrinsic noise and provide interpretations of them in terms of a hierarchical model. This allows us to derive alternative estimators that minimize bias or mean squared error. We provide a geometric interpretation of these results that clarifies the interpretation in [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.]. We also demonstrate through simulation and re-analysis of published data that the distribution assumptions underlying the hierarchical model have to be satisfied for the estimators to produce sensible results, which highlights the importance of normalization. PMID:27875323

Identification of innate lymphoid cells in single-cell RNA-Seq data.

PubMed

Suffiotti, Madeleine; Carmona, Santiago J; Jandus, Camilla; Gfeller, David

2017-07-01

Innate lymphoid cells (ILCs) consist of natural killer (NK) cells and non-cytotoxic ILCs that are broadly classified into ILC1, ILC2, and ILC3 subtypes. These cells recently emerged as important early effectors of innate immunity for their roles in tissue homeostasis and inflammation. Over the last few years, ILCs have been extensively studied in mouse and human at the functional and molecular level, including gene expression profiling. However, sorting ILCs with flow cytometry for gene expression analysis is a delicate and time-consuming process. Here we propose and validate a novel framework for studying ILCs at the transcriptomic level using single-cell RNA-Seq data. Our approach combines unsupervised clustering and a new cell type classifier trained on mouse ILC gene expression data. We show that this approach can accurately identify different ILCs, especially ILC2 cells, in human lymphocyte single-cell RNA-Seq data. Our new model relies only on genes conserved across vertebrates, thereby making it in principle applicable in any vertebrate species. Considering the rapid increase in throughput of single-cell RNA-Seq technology, our work provides a computational framework for studying ILC2 cells in single-cell transcriptomic data and may help exploring their conservation in distant vertebrate species.

Simultaneous genomic identification and profiling of a single cell using semiconductor-based next generation sequencing.

PubMed

Watanabe, Manabu; Kusano, Junko; Ohtaki, Shinsaku; Ishikura, Takashi; Katayama, Jin; Koguchi, Akira; Paumen, Michael; Hayashi, Yoshiharu

2014-09-01

Combining single-cell methods and next-generation sequencing should provide a powerful means to understand single-cell biology and obviate the effects of sample heterogeneity. Here we report a single-cell identification method and seamless cancer gene profiling using semiconductor-based massively parallel sequencing. A549 cells (adenocarcinomic human alveolar basal epithelial cell line) were used as a model. Single-cell capture was performed using laser capture microdissection (LCM) with an Arcturus® XT system, and a captured single cell and a bulk population of A549 cells (≈ 10(6) cells) were subjected to whole genome amplification (WGA). For cell identification, a multiplex PCR method (AmpliSeq™ SNP HID panel) was used to enrich 136 highly discriminatory SNPs with a genotype concordance probability of 10(31-35). For cancer gene profiling, we used mutation profiling that was performed in parallel using a hotspot panel for 50 cancer-related genes. Sequencing was performed using a semiconductor-based bench top sequencer. The distribution of sequence reads for both HID and Cancer panel amplicons was consistent across these samples. For the bulk population of cells, the percentages of sequence covered at coverage of more than 100 × were 99.04% for the HID panel and 98.83% for the Cancer panel, while for the single cell percentages of sequence covered at coverage of more than 100 × were 55.93% for the HID panel and 65.96% for the Cancer panel. Partial amplification failure or randomly distributed non-amplified regions across samples from single cells during the WGA procedures or random allele drop out probably caused these differences. However, comparative analyses showed that this method successfully discriminated a single A549 cancer cell from a bulk population of A549 cells. Thus, our approach provides a powerful means to overcome tumor sample heterogeneity when searching for somatic mutations.

Acquired resistance to combination treatment through loss of synergy with MEK and PI3K inhibitors in colorectal cancer

PubMed Central

Bhattacharya, Bhaskar; Low, Sarah Hong Hui; Chong, Mei Ling; Chia, Dilys; Koh, King Xin; Sapari, Nur Sabrina; Kaye, Stanley; Hung, Huynh; Benoukraf, Touati; Soong, Richie

2016-01-01

Historically, understanding of acquired resistance (AQR) to combination treatment has been based on knowledge of resistance to its component agents. To test whether an altered drug interaction could be an additional factor in AQR to combination treatment, models of AQR to combination and single agent MEK and PI3K inhibitor treatment were generated. Combination indices indicated combination treatment of PI3K and MEK inhibitors remained synergistic in cells with AQR to single agent but not combination AQR cells. Differences were also observed between the models in cellular phenotypes, pathway signaling and drug cross-resistance. Genomics implicated TGFB2-EDN1 overexpression as candidate determinants in models of AQR to combination treatment. Supplementation of endothelin in parental cells converted synergism to antagonism. Silencing of TGFB2 or EDN1 in cells with AQR conferred synergy between PI3K and MEK inhibitor. These results highlight that AQR to combination treatment may develop through alternative mechanisms to those of single agent treatment, including a change in drug interaction. PMID:27081080

Voronoi cell patterns: Theoretical model and applications

NASA Astrophysics Data System (ADS)

González, Diego Luis; Einstein, T. L.

2011-11-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We use our model to describe the Voronoi cell patterns of several systems. Specifically, we study the island nucleation with irreversible attachment, the 1D car-parking problem, the formation of second-level administrative divisions, and the pattern formed by the Paris Métro stations.

SCOUP: a probabilistic model based on the Ornstein-Uhlenbeck process to analyze single-cell expression data during differentiation.

PubMed

Matsumoto, Hirotaka; Kiryu, Hisanori

2016-06-08

Single-cell technologies make it possible to quantify the comprehensive states of individual cells, and have the power to shed light on cellular differentiation in particular. Although several methods have been developed to fully analyze the single-cell expression data, there is still room for improvement in the analysis of differentiation. In this paper, we propose a novel method SCOUP to elucidate differentiation process. Unlike previous dimension reduction-based approaches, SCOUP describes the dynamics of gene expression throughout differentiation directly, including the degree of differentiation of a cell (in pseudo-time) and cell fate. SCOUP is superior to previous methods with respect to pseudo-time estimation, especially for single-cell RNA-seq. SCOUP also successfully estimates cell lineage more accurately than previous method, especially for cells at an early stage of bifurcation. In addition, SCOUP can be applied to various downstream analyses. As an example, we propose a novel correlation calculation method for elucidating regulatory relationships among genes. We apply this method to a single-cell RNA-seq data and detect a candidate of key regulator for differentiation and clusters in a correlation network which are not detected with conventional correlation analysis. We develop a stochastic process-based method SCOUP to analyze single-cell expression data throughout differentiation. SCOUP can estimate pseudo-time and cell lineage more accurately than previous methods. We also propose a novel correlation calculation method based on SCOUP. SCOUP is a promising approach for further single-cell analysis and available at https://github.com/hmatsu1226/SCOUP.

Wound Repair: Toward Understanding and Integration of Single-Cell and Multicellular Wound Responses

PubMed Central

Sonnemann, Kevin J.; Bement, William M.

2016-01-01

The importance of wound healing to medicine and biology has long been evident, and consequently, wound healing has been the subject of intense investigation for many years. However, several relatively recent developments have added new impetus to wound repair research: the increasing application of model systems; the growing recognition that single cells have a robust, complex, and medically relevant wound healing response; and the emerging recognition that different modes of wound repair bear an uncanny resemblance to other basic biological processes such as morphogenesis and cytokinesis. In this review, each of these developments is described, and their significance for wound healing research is considered. In addition, overlapping mechanisms of single-cell and multicellular wound healing are highlighted, and it is argued that they are more similar than is often recognized. Based on this and other information, a simple model to explain the evolutionary relationships of cytokinesis, single-cell wound repair, multicellular wound repair, and developmental morphogenesis is proposed. Finally, a series of important, but as yet unanswered, questions is posed. PMID:21721944

Direct Correlation between Motile Behavior and Protein Abundance in Single Cells

PubMed Central

Gillet, Sébastien; Frankel, Nicholas W.; Weibel, Douglas B.

2016-01-01

Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with in situ hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in Escherichia coli motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB) at different levels, we quantitatively mapped motile phenotype (tumble bias) to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage. PMID:27599206

A particle-based model to simulate the micromechanics of single-plant parenchyma cells and aggregates

NASA Astrophysics Data System (ADS)

Van Liedekerke, P.; Ghysels, P.; Tijskens, E.; Samaey, G.; Smeedts, B.; Roose, D.; Ramon, H.

2010-06-01

This paper is concerned with addressing how plant tissue mechanics is related to the micromechanics of cells. To this end, we propose a mesh-free particle method to simulate the mechanics of both individual plant cells (parenchyma) and cell aggregates in response to external stresses. The model considers two important features in the plant cell: (1) the cell protoplasm, the interior liquid phase inducing hydrodynamic phenomena, and (2) the cell wall material, a viscoelastic solid material that contains the protoplasm. In this particle framework, the cell fluid is modeled by smoothed particle hydrodynamics (SPH), a mesh-free method typically used to address problems with gas and fluid dynamics. In the solid phase (cell wall) on the other hand, the particles are connected by pairwise interactions holding them together and preventing the fluid to penetrate the cell wall. The cell wall hydraulic conductivity (permeability) is built in as well through the SPH formulation. Although this model is also meant to be able to deal with dynamic and even violent situations (leading to cell wall rupture or cell-cell debonding), we have concentrated on quasi-static conditions. The results of single-cell compression simulations show that the conclusions found by analytical models and experiments can be reproduced at least qualitatively. Relaxation tests revealed that plant cells have short relaxation times (1 µs-10 µs) compared to mammalian cells. Simulations performed on cell aggregates indicated an influence of the cellular organization to the tissue response, as was also observed in experiments done on tissues with a similar structure.

Fibroblast Growth Factor-based Signaling through Synthetic Heparan Sulfate Blocks Copolymers Studied Using High Cell Density Three-dimensional Cell Printing*

PubMed Central

Sterner, Eric; Masuko, Sayaka; Li, Guoyun; Li, Lingyun; Green, Dixy E.; Otto, Nigel J.; Xu, Yongmei; DeAngelis, Paul L.; Liu, Jian; Dordick, Jonathan S.; Linhardt, Robert J.

2014-01-01

Four well-defined heparan sulfate (HS) block copolymers containing S-domains (high sulfo group content) placed adjacent to N-domains (low sulfo group content) were chemoenzymatically synthesized and characterized. The domain lengths in these HS block co-polymers were ∼40 saccharide units. Microtiter 96-well and three-dimensional cell-based microarray assays utilizing murine immortalized bone marrow (BaF3) cells were developed to evaluate the activity of these HS block co-polymers. Each recombinant BaF3 cell line expresses only a single type of fibroblast growth factor receptor (FGFR) but produces neither HS nor fibroblast growth factors (FGFs). In the presence of different FGFs, BaF3 cell proliferation showed clear differences for the four HS block co-polymers examined. These data were used to examine the two proposed signaling models, the symmetric FGF2-HS2-FGFR2 ternary complex model and the asymmetric FGF2-HS1-FGFR2 ternary complex model. In the symmetric FGF2-HS2-FGFR2 model, two acidic HS chains bind in a basic canyon located on the top face of the FGF2-FGFR2 protein complex. In this model the S-domains at the non-reducing ends of the two HS proteoglycan chains are proposed to interact with the FGF2-FGFR2 protein complex. In contrast, in the asymmetric FGF2-HS1-FGFR2 model, a single HS chain interacts with the FGF2-FGFR2 protein complex through a single S-domain that can be located at any position within an HS chain. Our data comparing a series of synthetically prepared HS block copolymers support a preference for the symmetric FGF2-HS2-FGFR2 ternary complex model. PMID:24563485

Modeling and Simulation of a Dual-Junction CIGS Solar Cell Using Silvaco ATLAS

DTIC Science & Technology

2012-12-01

junction Copper Indium Gallium Selenide (CIGS) photovoltaic cell is investigated in this thesis. Research into implementing a dual-junction solar cell...Silvaco ATLASTM model of a single CIGS cell was created by utilizing actual solar cell parameters (such as layer thicknesses, gallium ratio, doping...THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT The potential of designing a dual-junction Copper Indium Gallium Selenide (CIGS) photovoltaic

Modeling integrated photovoltaic–electrochemical devices using steady-state equivalent circuits

PubMed Central

Winkler, Mark T.; Cox, Casandra R.; Nocera, Daniel G.; Buonassisi, Tonio

2013-01-01

We describe a framework for efficiently coupling the power output of a series-connected string of single-band-gap solar cells to an electrochemical process that produces storable fuels. We identify the fundamental efficiency limitations that arise from using solar cells with a single band gap, an arrangement that describes the use of currently economic solar cell technologies such as Si or CdTe. Steady-state equivalent circuit analysis permits modeling of practical systems. For the water-splitting reaction, modeling defines parameters that enable a solar-to-fuels efficiency exceeding 18% using laboratory GaAs cells and 16% using all earth-abundant components, including commercial Si solar cells and Co- or Ni-based oxygen evolving catalysts. Circuit analysis also provides a predictive tool: given the performance of the separate photovoltaic and electrochemical systems, the behavior of the coupled photovoltaic–electrochemical system can be anticipated. This predictive utility is demonstrated in the case of water oxidation at the surface of a Si solar cell, using a Co–borate catalyst.

Label-free isolation of a prostate cancer cell among blood cells and the single-cell measurement of drug accumulation using an integrated microfluidic chip.

PubMed

Khamenehfar, A; Beischlag, T V; Russell, P J; Ling, M T P; Nelson, C; Li, P C H

2015-11-01

Circulating tumor cells (CTCs) are found in the blood of patients with cancer. Although these cells are rare, they can provide useful information for chemotherapy. However, isolation of these rare cells from blood is technically challenging because they are small in numbers. An integrated microfluidic chip, dubbed CTC chip, was designed and fabricated for conducting tumor cell isolation. As CTCs usually show multidrug resistance (MDR), the effect of MDR inhibitors on chemotherapeutic drug accumulation in the isolated single tumor cell is measured. As a model of CTC isolation, human prostate cancer cells were mixed with mouse blood cells and the label-free isolation of the tumor cells was conducted based on cell size difference. The major advantages of the CTC chip are the ability for fast cell isolation, followed by multiple rounds of single-cell measurements, suggesting a potential assay for detecting the drug responses based on the liquid biopsy of cancer patients.

Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data.

PubMed

Buettner, Florian; Moignard, Victoria; Göttgens, Berthold; Theis, Fabian J

2014-07-01

High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data. We use the Gaussian process latent variable model framework to account for censoring by introducing an appropriate noise model and allowing a different kernel for each dimension. We evaluate this new approach for two typical qPCR datasets (of mouse embryonic stem cells and blood stem/progenitor cells, respectively) by performing linear and non-linear probabilistic PCA. Taking the censoring into account results in a 2D representation of the data, which better reflects its known structure: in both datasets, our new approach results in a better separation of known cell types and is able to reveal subpopulations in one dataset that could not be resolved using standard PCA. The implementation was based on the existing Gaussian process latent variable model toolbox (https://github.com/SheffieldML/GPmat); extensions for noise models and kernels accounting for censoring are available at http://icb.helmholtz-muenchen.de/censgplvm. © The Author 2014. Published by Oxford University Press. All rights reserved.

Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data

PubMed Central

Buettner, Florian; Moignard, Victoria; Göttgens, Berthold; Theis, Fabian J.

2014-01-01

Motivation: High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data. Results: We use the Gaussian process latent variable model framework to account for censoring by introducing an appropriate noise model and allowing a different kernel for each dimension. We evaluate this new approach for two typical qPCR datasets (of mouse embryonic stem cells and blood stem/progenitor cells, respectively) by performing linear and non-linear probabilistic PCA. Taking the censoring into account results in a 2D representation of the data, which better reflects its known structure: in both datasets, our new approach results in a better separation of known cell types and is able to reveal subpopulations in one dataset that could not be resolved using standard PCA. Availability and implementation: The implementation was based on the existing Gaussian process latent variable model toolbox (https://github.com/SheffieldML/GPmat); extensions for noise models and kernels accounting for censoring are available at http://icb.helmholtz-muenchen.de/censgplvm. Contact: fbuettner.phys@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24618470

High-performance imaging of stem cells using single-photon emissions

NASA Astrophysics Data System (ADS)

Wagenaar, Douglas J.; Moats, Rex A.; Hartsough, Neal E.; Meier, Dirk; Hugg, James W.; Yang, Tang; Gazit, Dan; Pelled, Gadi; Patt, Bradley E.

2011-10-01

Radiolabeled cells have been imaged for decades in the field of autoradiography. Recent advances in detector and microelectronics technologies have enabled the new field of "digital autoradiography" which remains limited to ex vivo specimens of thin tissue slices. The 3D field-of-view (FOV) of single cell imaging can be extended to millimeters if the low energy (10-30 keV) photon emissions of radionuclides are used for single-photon nuclear imaging. This new microscope uses a coded aperture foil made of highly attenuating elements such as gold or platinum to form the image as a kind of "lens". The detectors used for single-photon emission microscopy are typically silicon detectors with a pixel pitch less than 60 μm. The goal of this work is to image radiolabeled mesenchymal stem cells in vivo in an animal model of tendon repair processes. Single-photon nuclear imaging is an attractive modality for translational medicine since the labeled cells can be imaged simultaneously with the reparative processes by using the dual-isotope imaging technique. The details our microscope's two-layer gold aperture and the operation of the energy-dispersive, pixellated silicon detector are presented along with the first demonstration of energy discrimination with a 57Co source. Cell labeling techniques have been augmented by genetic engineering with the sodium-iodide symporter, a type of reporter gene imaging method that enables in vivo uptake of free 99mTc or an iodine isotope at a time point days or weeks after the insertion of the genetically modified stem cells into the animal model. This microscopy work in animal research may expand to the imaging of reporter-enabled stem cells simultaneously with the expected biological repair process in human clinical trials of stem cell therapies.

Integrated QSAR study for inhibitors of hedgehog signal pathway against multiple cell lines:a collaborative filtering method

PubMed Central

2012-01-01

Background The Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway. Results In this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have proposed several possible chemical modifications to improve the inhibitor affinity towards multiple targets in the Hedgehog Signaling Pathway. Conclusions Our model with the feature selection strategy presented here is efficient, robust, and flexible, and can be easily extended to model large-scale multiple cell line/QSAR data. The data and scripts for collaborative QSAR modeling are available in the Additional file 1. PMID:22849868

Integrated QSAR study for inhibitors of Hedgehog Signal Pathway against multiple cell lines:a collaborative filtering method.

PubMed

Gao, Jun; Che, Dongsheng; Zheng, Vincent W; Zhu, Ruixin; Liu, Qi

2012-07-31

The Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway. In this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have proposed several possible chemical modifications to improve the inhibitor affinity towards multiple targets in the Hedgehog Signaling Pathway. Our model with the feature selection strategy presented here is efficient, robust, and flexible, and can be easily extended to model large-scale multiple cell line/QSAR data. The data and scripts for collaborative QSAR modeling are available in the Additional file 1.

Embryonic stem cells improve skeletal muscle recovery after extreme atrophy in mice.

PubMed

Artioli, Guilherme Giannini; De Oliveira Silvestre, João Guilherme; Guilherme, João Paulo Limongi França; Baptista, Igor Luchini; Ramos, Gracielle Vieira; Da Silva, Willian José; Miyabara, Elen Haruka; Moriscot, Anselmo Sigari

2015-03-01

We injected embryonic stem cells into mouse tibialis anterior muscles subjected to botulinum toxin injections as a model for reversible neurogenic atrophy. Muscles were exposed to botulinum toxin for 4 weeks and allowed to recover for up to 6 weeks. At the onset of recovery, a single muscle injection of embryonic stem cells was administered. The myofiber cross-sectional area, single twitch force, peak tetanic force, time-to-peak force, and half-relaxation time were determined. Although the stem cell injection did not affect the myofiber cross-sectional area gain in recovering muscles, most functional parameters improved significantly compared with those of recovering muscles that did not receive the stem cell injection. Muscle function recovery was accelerated by embryonic stem cell delivery in this durable neurogenic atrophy model. We conclude that stem cells should be considered a potential therapeutic tool for recovery after extreme skeletal muscle atrophy. © 2014 Wiley Periodicals, Inc.

Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing.

PubMed

Han, Xiaoping; Chen, Haide; Huang, Daosheng; Chen, Huidong; Fei, Lijiang; Cheng, Chen; Huang, He; Yuan, Guo-Cheng; Guo, Guoji

2018-04-05

Human pluripotent stem cells (hPSCs) provide powerful models for studying cellular differentiations and unlimited sources of cells for regenerative medicine. However, a comprehensive single-cell level differentiation roadmap for hPSCs has not been achieved. We use high throughput single-cell RNA-sequencing (scRNA-seq), based on optimized microfluidic circuits, to profile early differentiation lineages in the human embryoid body system. We present a cellular-state landscape for hPSC early differentiation that covers multiple cellular lineages, including neural, muscle, endothelial, stromal, liver, and epithelial cells. Through pseudotime analysis, we construct the developmental trajectories of these progenitor cells and reveal the gene expression dynamics in the process of cell differentiation. We further reprogram primed H9 cells into naïve-like H9 cells to study the cellular-state transition process. We find that genes related to hemogenic endothelium development are enriched in naïve-like H9. Functionally, naïve-like H9 show higher potency for differentiation into hematopoietic lineages than primed cells. Our single-cell analysis reveals the cellular-state landscape of hPSC early differentiation, offering new insights that can be harnessed for optimization of differentiation protocols.

Finite Element Analysis of Single Cell Stiffness Measurements Using PZT-Integrated Buckling Nanoneedles.

PubMed

Rad, Maryam Alsadat; Tijjani, Auwal Shehu; Ahmad, Mohd Ridzuan; Auwal, Shehu Muhammad

2016-12-23

This paper proposes a new technique for real-time single cell stiffness measurement using lead zirconate titanate (PZT)-integrated buckling nanoneedles. The PZT and the buckling part of the nanoneedle have been modelled and validated using the ABAQUS software. The two parts are integrated together to function as a single unit. After calibration, the stiffness, Young's modulus, Poisson's ratio and sensitivity of the PZT-integrated buckling nanoneedle have been determined to be 0.7100 N·m -1 , 123.4700 GPa, 0.3000 and 0.0693 V·m·N -1 , respectively. Three Saccharomyces cerevisiae cells have been modelled and validated based on compression tests. The average global stiffness and Young's modulus of the cells are determined to be 10.8867 ± 0.0094 N·m -1 and 110.7033 ± 0.0081 MPa, respectively. The nanoneedle and the cell have been assembled to measure the local stiffness of the single Saccharomyces cerevisiae cells The local stiffness, Young's modulus and PZT output voltage of the three different size Saccharomyces cerevisiae have been determined at different environmental conditions. We investigated that, at low temperature the stiffness value is low to adapt to the change in the environmental condition. As a result, Saccharomyces cerevisiae becomes vulnerable to viral and bacterial attacks. Therefore, the proposed technique will serve as a quick and accurate process to diagnose diseases at early stage in a cell for effective treatment.

BK/TD models for analyzing in vitro impedance data on cytotoxicity.

PubMed

Teng, S; Barcellini-Couget, S; Beaudouin, R; Brochot, C; Desousa, G; Rahmani, R; Pery, A R R

2015-06-01

The ban of animal testing has enhanced the development of new in vitro technologies for cosmetics safety assessment. Impedance metrics is one such technology which enables monitoring of cell viability in real time. However, analyzing real time data requires moving from static to dynamic toxicity assessment. In the present study, we built mechanistic biokinetic/toxicodynamic (BK/TD) models to analyze the time course of cell viability in cytotoxicity assay using impedance. These models account for the fate of the tested compounds during the assay. BK/TD models were applied to analyze HepaRG cell viability, after single (48 h) and repeated (4 weeks) exposures to three hepatotoxic compounds (coumarin, isoeugenol and benzophenone-2). The BK/TD models properly fit the data used for their calibration that was obtained for single or repeated exposure. Only for one out of the three compounds, the models calibrated with a single exposure were able to predict repeated exposure data. We therefore recommend the use of long-term exposure in vitro data in order to adequately account for chronic hepatotoxic effects. The models we propose here are capable of being coupled with human biokinetic models in order to relate dose exposure and human hepatotoxicity. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Early transcriptional and epigenetic regulation of CD8+ T cell differentiation revealed by single-cell RNA-seq

PubMed Central

Kakaradov, Boyko; Arsenio, Janilyn; Widjaja, Christella E.; He, Zhaoren; Aigner, Stefan; Metz, Patrick J.; Yu, Bingfei; Wehrens, Ellen J.; Lopez, Justine; Kim, Stephanie H.; Zuniga, Elina I.; Goldrath, Ananda W.; Chang, John T.; Yeo, Gene W.

2017-01-01

SUMMARY During microbial infection, responding CD8+ T lymphocytes differentiate into heterogeneous subsets that together provide immediate and durable protection. To elucidate the dynamic transcriptional changes that underlie this process, we applied a single-cell RNA sequencing approach and analyzed individual CD8+ T lymphocytes sequentially throughout the course of a viral infection in vivo. Our analyses revealed a striking transcriptional divergence among cells that had undergone their first division and identified previously unknown molecular determinants controlling CD8+ T lymphocyte fate specification. These findings suggest a model of terminal effector cell differentiation initiated by an early burst of transcriptional activity and subsequently refined by epigenetic silencing of transcripts associated with memory lymphocytes, highlighting the power and necessity of single-cell approaches. PMID:28218746

Coupling between apical tension and basal adhesion allow epithelia to collectively sense and respond to substrate topography over long distances.

PubMed

Broaders, Kyle E; Cerchiari, Alec E; Gartner, Zev J

2015-12-01

Epithelial sheets fold into complex topographies that contribute to their function in vivo. Cells can sense and respond to substrate topography in their immediate vicinity by modulating their interfacial mechanics, but the extent to which these mechanical properties contribute to their ability to sense substrate topography across length scales larger than a single cell has not been explored in detail. To study the relationship between the interfacial mechanics of single cells and their collective behavior as tissues, we grew cell-sheets on substrates engraved with surface features spanning macroscopic length-scales. We found that many epithelial cell-types sense and respond to substrate topography, even when it is locally nearly planar. Cells clear or detach from regions of local negative curvature, but not from regions with positive or no curvature. We investigated this phenomenon using a finite element model where substrate topography is coupled to epithelial response through a balance of tissue contractility and adhesive forces. The model correctly predicts the focal sites of cell-clearing and epithelial detachment. Furthermore, the model predicts that local tissue response to substrate curvature is a function of the surrounding topography of the substrate across long distances. Analysis of cell-cell and cell-substrate contact angles suggests a relationship between these single-cell interfacial properties, epithelial interfacial properties, and collective epithelial response to substrate topography. Finally, we show that contact angles change upon activation of oncogenes or inhibition of cell-contractility, and that these changes correlate with collective epithelial response. Our results demonstrate that in mechanically integrated epithelial sheets, cell contractility can be transmitted through multiple cells and focused by substrate topography to affect a behavioral response at distant sites.

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.

The structure and function of cell membranes examined by atomic force microscopy and single-molecule force spectroscopy.

PubMed

Shan, Yuping; Wang, Hongda

2015-06-07

The cell membrane is one of the most complicated biological complexes, and long-term fierce debates regarding the cell membrane persist because of technical hurdles. With the rapid development of nanotechnology and single-molecule techniques, our understanding of cell membranes has substantially increased. Atomic force microscopy (AFM) has provided several unprecedented advances (e.g., high resolution, three-dimensional and in situ measurements) in the study of cell membranes and has been used to systematically dissect the membrane structure in situ from both sides of membranes; as a result, novel models of cell membranes have recently been proposed. This review summarizes the new progress regarding membrane structure using in situ AFM and single-molecule force spectroscopy (SMFS), which may shed light on the study of the structure and functions of cell membranes.

Analysis of gene expression in single live neurons.

PubMed Central

Eberwine, J; Yeh, H; Miyashiro, K; Cao, Y; Nair, S; Finnell, R; Zettel, M; Coleman, P

1992-01-01

We present here a method for broadly characterizing single cells at the molecular level beyond the more common morphological and transmitter/receptor classifications. The RNA from defined single cells is amplified by microinjecting primer, nucleotides, and enzyme into acutely dissociated cells from a defined region of rat brain. Further processing yields amplified antisense RNA. A second round of amplification results in greater than 10(6)-fold amplification of the original starting material, which is adequate for analysis--e.g., use as a probe, making of cDNA libraries, etc. We demonstrate this method by constructing expression profiles of single live cells from rat hippocampus. This profiling suggests that cells that appear to be morphologically similar may show marked differences in patterns of expression. In addition, we characterize several mRNAs from a single cell, some of which were previously undescribed, perhaps due to "rarity" when averaged over many cell types. Electrophysiological analysis coupled with molecular biology within the same cell will facilitate a better understanding of how changes at the molecular level are manifested in functional properties. This approach should be applicable to a wide variety of studies, including development, mutant models, aging, and neurodegenerative disease. Images PMID:1557406

A short review of variants calling for single-cell-sequencing data with applications.

PubMed

Wei, Zhuohui; Shu, Chang; Zhang, Changsheng; Huang, Jingying; Cai, Hongmin

2017-11-01

The field of single-cell sequencing is fleetly expanding, and many techniques have been developed in the past decade. With this technology, biologists can study not only the heterogeneity between two adjacent cells in the same tissue or organ, but also the evolutionary relationships and degenerative processes in a single cell. Calling variants is the main purpose in analyzing single cell sequencing (SCS) data. Currently, some popular methods used for bulk-cell-sequencing data analysis are tailored directly to be applied in dealing with SCS data. However, SCS requires an extra step of genome amplification to accumulate enough quantity for satisfying sequencing needs. The amplification yields large biases and thus raises challenge for using the bulk-cell-sequencing methods. In order to provide guidance for the development of specialized analyzed methods as well as using currently developed tools for SNS, this paper aims to bridge the gap. In this paper, we firstly introduced two popular genome amplification methods and compared their capabilities. Then we introduced a few popular models for calling single-nucleotide polymorphisms and copy-number variations. Finally, break-through applications of SNS were summarized to demonstrate its potential in researching cell evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Microfluidic guillotine for single-cell wound repair studies

NASA Astrophysics Data System (ADS)

Blauch, Lucas R.; Gai, Ya; Khor, Jian Wei; Sood, Pranidhi; Marshall, Wallace F.; Tang, Sindy K. Y.

2017-07-01

Wound repair is a key feature distinguishing living from nonliving matter. Single cells are increasingly recognized to be capable of healing wounds. The lack of reproducible, high-throughput wounding methods has hindered single-cell wound repair studies. This work describes a microfluidic guillotine for bisecting single Stentor coeruleus cells in a continuous-flow manner. Stentor is used as a model due to its robust repair capacity and the ability to perform gene knockdown in a high-throughput manner. Local cutting dynamics reveals two regimes under which cells are bisected, one at low viscous stress where cells are cut with small membrane ruptures and high viability and one at high viscous stress where cells are cut with extended membrane ruptures and decreased viability. A cutting throughput up to 64 cells per minute—more than 200 times faster than current methods—is achieved. The method allows the generation of more than 100 cells in a synchronized stage of their repair process. This capacity, combined with high-throughput gene knockdown in Stentor, enables time-course mechanistic studies impossible with current wounding methods.

A lineage CLOUD for neoblasts.

PubMed

Tran, Thao Anh; Gentile, Luca

2018-05-10

In planarians, pluripotency can be studied in vivo in the adult animal, making these animals a unique model system where pluripotency-based regeneration (PBR)-and its therapeutic potential-can be investigated. This review focuses on recent findings to build a cloud model of fate restriction likelihood for planarian stem and progenitor cells. Recently, a computational approach based on functional and molecular profiling at the single cell level was proposed for human hematopoietic stem cells. Based on data generated both in vivo and ex vivo, we hypothesized that planarian stem cells could acquire multiple direction lineage biases, following a "badlands" landscape. Instead of a discrete tree-like hierarchy, where the potency of stem/progenitor cells reduces stepwise, we propose a Continuum of LOw-primed UnDifferentiated Planarian Stem/Progenitor Cells (CLOUD-PSPCs). Every subclass of neoblast/progenitor cells is a cloud of likelihood, as the single cell transcriptomics data indicate. The CLOUD-HSPCs concept was substantiated by in vitro data from cell culture; therefore, to confirm the CLOUD-PSPCs model, the planarian community needs to develop new tools, like live cell tracking. Future studies will allow a deeper understanding of PBR in planarian, and the possible implications for regenerative therapies in human. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sci-Thur AM: YIS – 06: A Monte Carlo study of macro- and microscopic dose descriptors and the microdosimetric spread using detailed cellular models

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

Oliver, Patricia; Thomson, Rowan

2016-08-15

Purpose: To develop Monte Carlo models of cell clusters to investigate the relationships between macro- and microscopic dose descriptors, quantify the microdosimetric spread in energy deposition for subcellular targets, and determine how these results depend on the computational model. Methods: Microscopic tissue structure is modelled as clusters of 13 to 150 cells, with cell (nuclear) radii between 5 and 10 microns (2 and 9 microns). Energy imparted per unit mass (specific energy or dose) is scored in the nucleus (D{sub nuc}) and cytoplasm (D{sub cyt}) for incident photon energies from 20 to 370 keV. Dose-to-water (D{sub w,m}) and dose-to-medium (D{submore » m,m}) are compared to D{sub nuc} and D{sub cyt}. Single cells and single nuclear cavities are also simulated. Results: D{sub nuc} and D{sub cyt} are sensitive to the surrounding environment with deviations of up to 13% for a single nucleus/cell compared with a multicellular cluster. These dose descriptors vary with cell and nucleus size by up to 10%. D{sub nuc} and D{sub cyt} differ from D{sub w,m} and D{sub m,m} by up to 32%. The microdosimetric spread is sensitive to whether cells are arranged randomly or in a hexagonal lattice, and whether subcellular compartment sizes are sampled from a normal distribution or are constant throughout the cluster. Conclusions: D{sub nuc} and D{sub cyt} are sensitive to cell morphology, elemental composition and the presence of surrounding cells. The microdosimetric spread was investigated using realistic elemental compositions for the nucleus and cytoplasm, and depends strongly on subcellular compartment size, source energy and dose.« less

Motility-Driven Glass and Jamming Transitions in Biological Tissues

NASA Astrophysics Data System (ADS)

Bi, Dapeng; Yang, Xingbo; Marchetti, M. Cristina; Manning, M. Lisa

2016-04-01

Cell motion inside dense tissues governs many biological processes, including embryonic development and cancer metastasis, and recent experiments suggest that these tissues exhibit collective glassy behavior. To make quantitative predictions about glass transitions in tissues, we study a self-propelled Voronoi model that simultaneously captures polarized cell motility and multibody cell-cell interactions in a confluent tissue, where there are no gaps between cells. We demonstrate that the model exhibits a jamming transition from a solidlike state to a fluidlike state that is controlled by three parameters: the single-cell motile speed, the persistence time of single-cell tracks, and a target shape index that characterizes the competition between cell-cell adhesion and cortical tension. In contrast to traditional particulate glasses, we are able to identify an experimentally accessible structural order parameter that specifies the entire jamming surface as a function of model parameters. We demonstrate that a continuum soft glassy rheology model precisely captures this transition in the limit of small persistence times and explain how it fails in the limit of large persistence times. These results provide a framework for understanding the collective solid-to-liquid transitions that have been observed in embryonic development and cancer progression, which may be associated with epithelial-to-mesenchymal transition in these tissues.

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

Theoretical analysis of insulin-dependent glucose uptake heterogeneity in 3D bioreactor cell culture.

PubMed

Magrofuoco, Enrico; Elvassore, Nicola; Doyle, Francis J

2012-01-01

Three-dimensional (3D) cell cultures in bioreactors are becoming relevant as models for biological and physiological in vitro studies. In such systems, mathematical models can assist the experiment design that links the macroscopic properties to single-cell responses. We investigated the relationship between biochemical stimuli and cell response within a 3D cell culture in scaffold with heterogeneous porosity. Specifically, we studied the effect of insulin on the local glucose metabolism as a function of 3D pore size distribution. The multiscale mathematical model combines the mass transport within a 3D scaffold and a signaling pathways model. It considers the scaffold heterogeneity, and it describes spatiotemporal concentration of metabolites, biochemical stimuli, and cell density. The signaling model was integrated into this model, linking the local insulin concentration at cell membrane to the glucose uptake rate through glucose transporter type 4 (GLUT4) translocation from the cytosol to the cell membrane. The integrated model determines the cell response heterogeneities in a single channel, hence the biological response distribution in a 3D system. It also provides macroscopic outcomes to evaluate the feasibility of an experimental measurement of the system response. From our analysis, it became apparent that the flow rate is the most important operative variable, and that an optimum value ensures a fast and detectable cell response. This model on insulin-dependent glucose consumption rate offers insight into the cell metabolism physiology, which is a fundamental requirement for the study metabolic disorder such as Type 2 diabetes mellitus, in which the physiological insulin-dependent glucose metabolism is impaired. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

INDICATORS OF GENETIC DAMAGE IN MODEL STREAM FISH USING CONTROLLED LABORATORY EXPOSURES

EPA Science Inventory

The micronucleus (MN) and single cell gel electrophoresis (SCG) assays are being applied to peripheral blood cells from several fish species using model genotoxicants and envirornmentally relevant pollutants. In initial studies, bluegill sunfish (Lepomis macrochirus, 4 to 5 per ...

An analytical-numerical approach for parameter determination of a five-parameter single-diode model of photovoltaic cells and modules

NASA Astrophysics Data System (ADS)

Hejri, Mohammad; Mokhtari, Hossein; Azizian, Mohammad Reza; Söder, Lennart

2016-04-01

Parameter extraction of the five-parameter single-diode model of solar cells and modules from experimental data is a challenging problem. These parameters are evaluated from a set of nonlinear equations that cannot be solved analytically. On the other hand, a numerical solution of such equations needs a suitable initial guess to converge to a solution. This paper presents a new set of approximate analytical solutions for the parameters of a five-parameter single-diode model of photovoltaic (PV) cells and modules. The proposed solutions provide a good initial point which guarantees numerical analysis convergence. The proposed technique needs only a few data from the PV current-voltage characteristics, i.e. open circuit voltage Voc, short circuit current Isc and maximum power point current and voltage Im; Vm making it a fast and low cost parameter determination technique. The accuracy of the presented theoretical I-V curves is verified by experimental data.

Feasibility of a workflow for the molecular characterization of single cells by next generation sequencing.

PubMed

Salvianti, Francesca; Rotunno, Giada; Galardi, Francesca; De Luca, Francesca; Pestrin, Marta; Vannucchi, Alessandro Maria; Di Leo, Angelo; Pazzagli, Mario; Pinzani, Pamela

2015-09-01

The purpose of the study was to explore the feasibility of a protocol for the isolation and molecular characterization of single circulating tumor cells (CTCs) from cancer patients using a single-cell next generation sequencing (NGS) approach. To reach this goal we used as a model an artificial sample obtained by spiking a breast cancer cell line (MDA-MB-231) into the blood of a healthy donor. Tumor cells were enriched and enumerated by CellSearch(®) and subsequently isolated by DEPArray™ to obtain single or pooled pure samples to be submitted to the analysis of the mutational status of multiple genes involved in cancer. Upon whole genome amplification, samples were analysed by NGS on the Ion Torrent PGM™ system (Life Technologies) using the Ion AmpliSeq™ Cancer Hotspot Panel v2 (Life Technologies), designed to investigate genomic "hot spot" regions of 50 oncogenes and tumor suppressor genes. We successfully sequenced five single cells, a pool of 5 cells and DNA from a cellular pellet of the same cell line with a mean depth of the sequencing reaction ranging from 1581 to 3479 reads. We found 27 sequence variants in 18 genes, 15 of which already reported in the COSMIC or dbSNP databases. We confirmed the presence of two somatic mutations, in the BRAF and TP53 gene, which had been already reported for this cells line, but also found new mutations and single nucleotide polymorphisms. Three variants were common to all the analysed samples, while 18 were present only in a single cell suggesting a high heterogeneity within the same cell line. This paper presents an optimized workflow for the molecular characterization of multiple genes in single cells by NGS. The described pipeline can be easily transferred to the study of single CTCs from oncologic patients.

Bayesian approach to MSD-based analysis of particle motion in live cells.

PubMed

Monnier, Nilah; Guo, Syuan-Ming; Mori, Masashi; He, Jun; Lénárt, Péter; Bathe, Mark

2012-08-08

Quantitative tracking of particle motion using live-cell imaging is a powerful approach to understanding the mechanism of transport of biological molecules, organelles, and cells. However, inferring complex stochastic motion models from single-particle trajectories in an objective manner is nontrivial due to noise from sampling limitations and biological heterogeneity. Here, we present a systematic Bayesian approach to multiple-hypothesis testing of a general set of competing motion models based on particle mean-square displacements that automatically classifies particle motion, properly accounting for sampling limitations and correlated noise while appropriately penalizing model complexity according to Occam's Razor to avoid over-fitting. We test the procedure rigorously using simulated trajectories for which the underlying physical process is known, demonstrating that it chooses the simplest physical model that explains the observed data. Further, we show that computed model probabilities provide a reliability test for the downstream biological interpretation of associated parameter values. We subsequently illustrate the broad utility of the approach by applying it to disparate biological systems including experimental particle trajectories from chromosomes, kinetochores, and membrane receptors undergoing a variety of complex motions. This automated and objective Bayesian framework easily scales to large numbers of particle trajectories, making it ideal for classifying the complex motion of large numbers of single molecules and cells from high-throughput screens, as well as single-cell-, tissue-, and organism-level studies. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Efficiency of primary saliva secretion: an analysis of parameter dependence in dynamic single-cell and acinus models, with application to aquaporin knockout studies

PubMed Central

Maclaren, Oliver J.; Sneyd, James; Crampin, Edmund J.

2012-01-01

Secretion from the salivary glands is driven by osmosis following the establishment of osmotic gradients between the lumen, the cell and the interstitium by active ion transport. We consider a dynamic model of osmotically-driven primary saliva secretion, and use singular perturbation approaches and scaling assumptions to reduce the model. Our analysis shows that isosmotic secretion is the most efficient secretion regime, and that this holds for single isolated cells and for multiple cells assembled into an acinus. For typical parameter variations, we rule out any significant synergistic effect on total water secretion of an acinar arrangement of cells about a single shared lumen. Conditions for the attainment of isosmotic secretion are considered, and we derive an expression for how the concentration gradient between the interstitium and the lumen scales with water and chloride transport parameters. Aquaporin knockout studies are interpreted in the context of our analysis and further investigated using simulations of transport efficiency with different membrane water permeabilities. We conclude that recent claims that aquaporin knockout studies can be interpreted as evidence against a simple osmotic mechanism are not supported by our work. Many of the results that we obtain are independent of specific transporter details, and our analysis can be easily extended to apply to models that use other proposed ionic mechanisms of saliva secretion. PMID:22258315

Number of infection events per cell during HIV-1 cell-free infection.

PubMed

Ito, Yusuke; Remion, Azaria; Tauzin, Alexandra; Ejima, Keisuke; Nakaoka, Shinji; Iwasa, Yoh; Iwami, Shingo; Mammano, Fabrizio

2017-07-26

HIV-1 accumulates changes in its genome through both recombination and mutation during the course of infection. For recombination to occur, a single cell must be infected by two HIV strains. These coinfection events were experimentally demonstrated to occur more frequently than would be expected for independent infection events and do not follow a random distribution. Previous mathematical modeling approaches demonstrated that differences in target cell susceptibility can explain the non-randomness, both in the context of direct cell-to-cell transmission, and in the context of free virus transmission (Q. Dang et al., Proc. Natl. Acad. Sci. USA 101:632-7, 2004: K. M. Law et al., Cell reports 15:2711-83, 2016). Here, we build on these notions and provide a more detailed and extensive quantitative framework. We developed a novel mathematical model explicitly considering the heterogeneity of target cells and analysed datasets of cell-free HIV-1 single and double infection experiments in cell culture. Particularly, in contrast to the previous studies, we took into account the different susceptibility of the target cells as a continuous distribution. Interestingly, we showed that the number of infection events per cell during cell-free HIV-1 infection follows a negative-binomial distribution, and our model reproduces these datasets.

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.

Controlled graphene encapsulation: a nanoscale shield for characterising single bacterial cells in liquid.

PubMed

Li, Jiayao; Zheng, Changxi; Liu, Boyin; Chou, Tsengming; Kim, Yeonuk; Qiu, Shi; Li, Jian; Yan, Wenyi; Fu, Jing

2018-06-11

High-resolution single-cell imaging in their native or near-native state has received considerable interest for decades. In this research, we present an innovative approach that can be employed to study both morphological and nano-mechanical properties of hydrated single bacterial cells. The proposed strategy is to encapsulate wet cells with monolayer graphene with a newly developed water membrane approach, followed by imaging with both electron microscopy (EM) and atomic force microscopy (AFM). A computational framework was developed to provide additional insights, with the detailed nanoindentation process on graphene modeled based on finite element method. The model was first validated by calibration with polymer materials of known properties, and the contribution of graphene was then studied and corrected to determine the actual moduli of the encapsulated hydrated sample. Aapplication of the proposed approach was performed on hydrated bacterial cells (Klebsiella pneumoniae) to correlate the structural and mechanical information. EM and EDS (energy-dispersive X-ray spectroscopy) imaging confirmed that the cells in their near-native stage can be studied inside the miniatured environment enabled with graphene encapsulation. The actual moduli of the encapsulated hydrated cells were determined based on the developed computational model in parallel, with results comparable with those acquired with Wet-AFM. It is expected that the successful establishment of controlled graphene encapsulation offers a new route for probing liquid/live cells with scanning probe microscopy, as well as correlative imaging of hydrated samples for both biological and material sciences. © 2018 IOP Publishing Ltd.

Emergence of cytotoxic resistance in cancer cell populations: Single-cell mechanisms and population-level consequences

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

Lorenzi, Tommaso; Chisholm, Rebecca H.; Lorz, Alexander

We formulate an individual-based model and a population model of phenotypic evolution, under cytotoxic drugs, in a cancer cell population structured by the expression levels of survival-potential and proliferation-potential. We apply these models to a recently studied experimental system. Our results suggest that mechanisms based on fundamental laws of biology can reversibly push an actively-proliferating, and drug-sensitive, cell population to transition into a weakly-proliferative and drug-tolerant state, which will eventually facilitate the emergence of more potent, proliferating and drug-tolerant cells.

The Activation and Inactivation of Mature CD4 T cells: A Case for Peripheral Self–Nonself Discrimination

PubMed Central

Bretscher, P A

2014-01-01

The establishment of central tolerance to most self-antigens results in a repertoire of mature peripheral lymphocytes specific for foreign and peripheral self-antigens. The framework that single, mature lymphocytes are inactivated by antigen, whereas their activation requires lymphocyte cooperation, accounts for diverse observations and incorporates a mechanism of peripheral tolerance. This framework accounts for the generalizations that the sustained activation by antigen of most B cells and CD8 T cells requires CD4 T helper cells; in the absence of CD4 T cells, antigen can inactivate these B cells and CD8 T cells. In this sense, CD4 T cells are the guardians of the fate of most B cells and CD8 T cells when they encounter antigen. I argue here that the single-lymphocyte/multiple-lymphocyte framework for the inactivation/activation of lymphocytes also applies to CD4 T cells. I consider within this framework a model for the activation/inactivation of CD4 T cells that is consistent with the large majority of contemporary observations, including significant clinical observations. I outline the grounds why I feel this model is more plausible than the contemporary and predominant pathogen-associated molecular pattern (PAMP) and Danger Models for CD4 T cell activation. These models are based upon what I consider the radical premise that self–nonself discrimination does not exist at the level of mature CD4 T cells. I explain why I feel this feature renders the PAMP and Danger Models somewhat implausible. The model I propose, in contrast, is conservative in that it embodies such a process of self–nonself discrimination. PMID:24684567

Integrating discrete stochastic models and single-cell experiments to infer predictive models of MAPK-induced transcription dynamics

NASA Astrophysics Data System (ADS)

Munsky, Brian

2015-03-01

MAPK signal-activated transcription plays central roles in myriad biological processes including stress adaptation responses and cell fate decisions. Recent single-cell and single-molecule experiments have advanced our ability to quantify the spatial, temporal, and stochastic fluctuations for such signals and their downstream effects on transcription regulation. This talk explores how integrating such experiments with discrete stochastic computational analyses can yield quantitative and predictive understanding of transcription regulation in both space and time. We use single-molecule mRNA fluorescence in situ hybridization (smFISH) experiments to reveal locations and numbers of multiple endogenous mRNA species in 100,000's of individual cells, at different times and under different genetic and environmental perturbations. We use finite state projection methods to precisely and efficiently compute the full joint probability distributions of these mRNA, which capture measured spatial, temporal and correlative fluctuations. By combining these experimental and computational tools with uncertainty quantification, we systematically compare models of varying complexity and select those which give optimally precise and accurate predictions in new situations. We use these tools to explore two MAPK-activated gene regulation pathways. In yeast adaptation to osmotic shock, we analyze Hog1 kinase activation of transcription for three different genes STL1 (osmotic stress), CTT1 (oxidative stress) and HSP12 (heat shock). In human osteosarcoma cells under serum induction, we analyze ERK activation of c-Fos transcription.

Cell-cycle dynamics of chromosomal organisation at single-cell resolution

PubMed Central

Nagano, Takashi; Lubling, Yaniv; Várnai, Csilla; Dudley, Carmel; Leung, Wing; Baran, Yael; Mendelson-Cohen, Netta; Wingett, Steven; Fraser, Peter; Tanay, Amos

2017-01-01

Summary Chromosomes in proliferating metazoan cells undergo dramatic structural metamorphoses every cell cycle, alternating between highly condensed mitotic structures facilitating chromosome segregation, and decondensed interphase structures accommodating transcription, gene silencing and DNA replication. Here we use single-cell Hi-C to study chromosome conformations in thousands of individual cells, and discover a continuum of cis-interaction profiles that finely position individual cells along the cell cycle. We show that chromosomal compartments, topological associated domains (TADs), contact insulation and long-range loops, all defined by bulk Hi-C maps, are governed by distinct cell-cycle dynamics. In particular, DNA replication correlates with build-up of compartments and reduction in TAD insulation, while loops are generally stable from G1 through S and G2. Whole-genome 3D structural models reveal a radial architecture of chromosomal compartments with distinct epigenomic signatures. Our single-cell data thereby allow for re-interpretation of chromosome conformation maps through the prism of the cell cycle. PMID:28682332

Issues associated with modelling of proton exchange membrane fuel cell by computational fluid dynamics

NASA Astrophysics Data System (ADS)

Bednarek, Tomasz; Tsotridis, Georgios

2017-03-01

The objective of the current study is to highlight possible limitations and difficulties associated with Computational Fluid Dynamics in PEM single fuel cell modelling. It is shown that an appropriate convergence methodology should be applied for steady-state solutions, due to inherent numerical instabilities. A single channel fuel cell model has been taken as numerical example. Results are evaluated for quantitative as well qualitative points of view. The contribution to the polarization curve of the different fuel cell components such as bi-polar plates, gas diffusion layers, catalyst layers and membrane was investigated via their effects on the overpotentials. Furthermore, the potential losses corresponding to reaction kinetics, due to ohmic and mas transport limitations and the effect of the exchange current density and open circuit voltage, were also investigated. It is highlighted that the lack of reliable and robust input data is one of the issues for obtaining accurate results.

Exclusive Liquid Repellency: An Open Multi-Liquid-Phase Technology for Rare Cell Culture and Single-Cell Processing.

PubMed

Li, Chao; Yu, Jiaquan; Schehr, Jennifer; Berry, Scott M; Leal, Ticiana A; Lang, Joshua M; Beebe, David J

2018-05-23

The concept of high liquid repellency in multi-liquid-phase systems (e.g., aqueous droplets in an oil background) has been applied to areas of biomedical research to realize intrinsic advantages not available in single-liquid-phase systems. Such advantages have included minimizing analyte loss, facile manipulation of single-cell samples, elimination of biofouling, and ease of use regarding loading and retrieving of the sample. In this paper, we present generalized design rules for predicting the wettability of solid-liquid-liquid systems (especially for discrimination between exclusive liquid repellency (ELR) and finite liquid repellency) to extend the applications of ELR. We then apply ELR to two model systems with open microfluidic design in cell biology: (1) in situ underoil culture and combinatorial coculture of mammalian cells in order to demonstrate directed single-cell multiencapsulation with minimal waste of samples as compared to stochastic cell seeding and (2) isolation of a pure population of circulating tumor cells, which is required for certain downstream analyses including sequencing and gene expression profiling.

Detection of angiotensin II binding to single adrenal zona glomerulosa cells by confocal Raman microspectroscopy

NASA Astrophysics Data System (ADS)

McCoy, Michael J.; Habermann, Timothy J.; Hanke, Craig J.; Adar, Fran; Campbell, William B.; Nithipatikom, Kasem

1999-04-01

We developed a confocal Raman microspectroscopic technique to study ligand-receptor bindings in single cells using Raman-labeled ligands and surface-enhanced Raman scattering (SERS). The adrenal zona glomerulosa (ZG) cells were used as a model in this study. ZG cells have a high density of angiotensin II (AII) receptors on the cellular membrane. There are two identified subtypes of AII receptors,namely AT1 and AT2 receptors. AII is a peptidic hormone, which upon binding to its receptors, stimulates the release of aldosterone from ZG cells. The cellular localization of these receptors subtypes was detected in single ZG cells by using immunocomplexation of receptors with specific antibodies and confocal Raman microspectroscopy. In the binding study, we used biotin-labeled AII to bind to its receptors in ZG cells. Then, avidin and Raman-labeled AII. The binding was measure directly on the single ZG cells. The results showed that the binding was displaced with unlabeled AII and specific AII antagonists. This is a rapid and sensitive technique for detection of cellular ligand bindings as well as antagonists screening in drug discovery.

Single-cell RNA-seq and computational analysis using temporal mixture modelling resolves Th1/Tfh fate bifurcation in malaria

PubMed Central

Lönnberg, Tapio; Svensson, Valentine; James, Kylie R.; Fernandez-Ruiz, Daniel; Sebina, Ismail; Montandon, Ruddy; Soon, Megan S. F.; Fogg, Lily G.; Nair, Arya Sheela; Liligeto, Urijah; Stubbington, Michael J. T.; Ly, Lam-Ha; Bagger, Frederik Otzen; Zwiessele, Max; Lawrence, Neil D.; Souza-Fonseca-Guimaraes, Fernando; Bunn, Patrick T.; Engwerda, Christian R.; Heath, William R.; Billker, Oliver; Stegle, Oliver; Haque, Ashraful; Teichmann, Sarah A.

2017-01-01

Differentiation of naïve CD4+ T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to extensive heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo. By using single-cell transcriptomics and computational analysis using a temporal mixtures of Gaussian processes model, termed GPfates, we reconstructed the developmental trajectories of Th1 and Tfh cells during blood-stage Plasmodium infection in mice. By tracking clonality using endogenous TCR sequences, we first demonstrated that Th1/Tfh bifurcation had occurred at both population and single-clone levels. Next, we identified genes whose expression was associated with Th1 or Tfh fates, and demonstrated a T-cell intrinsic role for Galectin-1 in supporting a Th1 differentiation. We also revealed the close molecular relationship between Th1 and IL-10-producing Tr1 cells in this infection. Th1 and Tfh fates emerged from a highly proliferative precursor that upregulated aerobic glycolysis and accelerated cell cycling as cytokine expression began. Dynamic gene expression of chemokine receptors around bifurcation predicted roles for cell-cell in driving Th1/Tfh fates. In particular, we found that precursor Th cells were coached towards a Th1 but not a Tfh fate by inflammatory monocytes. Thus, by integrating genomic and computational approaches, our study has provided two unique resources, a database www.PlasmoTH.org, which facilitates discovery of novel factors controlling Th1/Tfh fate commitment, and more generally, GPfates, a modelling framework for characterizing cell differentiation towards multiple fates. PMID:28345074

Computational modelling of mesoscale dislocation patterning and plastic deformation of single crystals

NASA Astrophysics Data System (ADS)

Xia, Shengxu; El-Azab, Anter

2015-07-01

We present a continuum dislocation dynamics model that predicts the formation of dislocation cell structure in single crystals at low strains. The model features a set of kinetic equations of the curl type that govern the space and time evolution of the dislocation density in the crystal. These kinetic equations are coupled to stress equilibrium and deformation kinematics using the eigenstrain approach. A custom finite element method has been developed to solve the coupled system of equations of dislocation kinetics and crystal mechanics. The results show that, in general, dislocations self-organize in patterns under their mutual interactions. However, the famous dislocation cell structure has been found to form only when cross slip is implemented in the model. Cross slip is also found to lower the yield point, increase the hardening rate, and sustain an increase in the dislocation density over the hardening regime. Analysis of the cell structure evolution reveals that the average cell size decreases with the applied stress, which is consistent with the similitude principle.

Forces in yeast flocculation

NASA Astrophysics Data System (ADS)

El-Kirat-Chatel, Sofiane; Beaussart, Audrey; Vincent, Stéphane P.; Abellán Flos, Marta; Hols, Pascal; Lipke, Peter N.; Dufrêne, Yves F.

2015-01-01

In the baker's yeast Saccharomyces cerevisiae, cell-cell adhesion (``flocculation'') is conferred by a family of lectin-like proteins known as the flocculin (Flo) proteins. Knowledge of the adhesive and mechanical properties of flocculins is important for understanding the mechanisms of yeast adhesion, and may help controlling yeast behaviour in biotechnology. We use single-molecule and single-cell atomic force microscopy (AFM) to explore the nanoscale forces engaged in yeast flocculation, focusing on the role of Flo1 as a prototype of flocculins. Using AFM tips labelled with mannose, we detect single flocculins on Flo1-expressing cells, showing they are widely exposed on the cell surface. When subjected to force, individual Flo1 proteins display two distinct force responses, i.e. weak lectin binding forces and strong unfolding forces reflecting the force-induced extension of hydrophobic tandem repeats. We demonstrate that cell-cell adhesion bonds also involve multiple weak lectin interactions together with strong unfolding forces, both associated with Flo1 molecules. Single-molecule and single-cell data correlate with microscale cell adhesion behaviour, suggesting strongly that Flo1 mechanics is critical for yeast flocculation. These results favour a model in which not only weak lectin-sugar interactions are involved in yeast flocculation but also strong hydrophobic interactions resulting from protein unfolding.

A Multiscale Computational Model Combining a Single Crystal Plasticity Constitutive Model with the Generalized Method of Cells (GMC) for Metallic Polycrystals.

PubMed

Ghorbani Moghaddam, Masoud; Achuthan, Ajit; Bednarcyk, Brett A; Arnold, Steven M; Pineda, Evan J

2016-05-04

A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level, i.e. , each individual grain. Two-three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities.

A Multiscale Computational Model Combining a Single Crystal Plasticity Constitutive Model with the Generalized Method of Cells (GMC) for Metallic Polycrystals

PubMed Central

Ghorbani Moghaddam, Masoud; Achuthan, Ajit; Bednarcyk, Brett A.; Arnold, Steven M.; Pineda, Evan J.

2016-01-01

A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level, i.e., each individual grain. Two–three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities. PMID:28773458

Probing the target search of DNA-binding proteins in mammalian cells using TetR as model searcher

NASA Astrophysics Data System (ADS)

Normanno, Davide; Boudarène, Lydia; Dugast-Darzacq, Claire; Chen, Jiji; Richter, Christian; Proux, Florence; Bénichou, Olivier; Voituriez, Raphaël; Darzacq, Xavier; Dahan, Maxime

2015-07-01

Many cellular functions rely on DNA-binding proteins finding and associating to specific sites in the genome. Yet the mechanisms underlying the target search remain poorly understood, especially in the case of the highly organized mammalian cell nucleus. Using as a model Tet repressors (TetRs) searching for a multi-array locus, we quantitatively analyse the search process in human cells with single-molecule tracking and single-cell protein-DNA association measurements. We find that TetRs explore the nucleus and reach their target by 3D diffusion interspersed with transient interactions with non-cognate sites, consistent with the facilitated diffusion model. Remarkably, nonspecific binding times are broadly distributed, underlining a lack of clear delimitation between specific and nonspecific interactions. However, the search kinetics is not determined by diffusive transport but by the low association rate to nonspecific sites. Altogether, our results provide a comprehensive view of the recruitment dynamics of proteins at specific loci in mammalian cells.

Volumetric Stress-Strain Analysis of Optohydrodynamically Suspended Biological Cells

PubMed Central

Liang, Yu; Saha, Asit K.

2011-01-01

Ongoing investigations are exploring the biomechanical properties of isolated and suspended biological cells in pursuit of understanding single-cell mechanobiology. An optical tweezer with minimal applied laser power has positioned biologic cells at the geometric center of a microfluidic cross-junction, creating a novel optohydrodynamic trap. The resulting fluid flow environment facilitates unique multiaxial loading of single cells with site-specific normal and shear stresses resulting in a physical albeit extensional state. A recent two-dimensional analysis has explored the cytoskeletal strain response due to these fluid-induced stresses [Wilson and Kohles, 2010, “Two-Dimensional Modeling of Nanomechanical Stresses-Strains in Healthy and Diseased Single-Cells During Microfluidic Manipulation,” J Nanotechnol Eng Med, 1(2), p. 021005]. Results described a microfluidic environment having controlled nanometer and piconewton resolution. In this present study, computational fluid dynamics combined with multiphysics modeling has further characterized the applied fluid stress environment and the solid cellular strain response in three dimensions to accompany experimental cell stimulation. A volumetric stress-strain analysis was applied to representative living cell biomechanical data. The presented normal and shear stress surface maps will guide future microfluidic experiments as well as provide a framework for characterizing cytoskeletal structure influencing the stress to strain response. PMID:21186894

Assessing similarity to primary tissue and cortical layer identity in induced pluripotent stem cell-derived cortical neurons through single-cell transcriptomics

PubMed Central

Handel, Adam E.; Chintawar, Satyan; Lalic, Tatjana; Whiteley, Emma; Vowles, Jane; Giustacchini, Alice; Argoud, Karene; Sopp, Paul; Nakanishi, Mahito; Bowden, Rory; Cowley, Sally; Newey, Sarah; Akerman, Colin; Ponting, Chris P.; Cader, M. Zameel

2016-01-01

Induced pluripotent stem cell (iPSC)-derived cortical neurons potentially present a powerful new model to understand corticogenesis and neurological disease. Previous work has established that differentiation protocols can produce cortical neurons, but little has been done to characterize these at cellular resolution. In particular, it is unclear to what extent in vitro two-dimensional, relatively disordered culture conditions recapitulate the development of in vivo cortical layer identity. Single-cell multiplex reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was used to interrogate the expression of genes previously implicated in cortical layer or phenotypic identity in individual cells. Totally, 93.6% of single cells derived from iPSCs expressed genes indicative of neuronal identity. High proportions of single neurons derived from iPSCs expressed glutamatergic receptors and synaptic genes. And, 68.4% of iPSC-derived neurons expressing at least one layer marker could be assigned to a laminar identity using canonical cortical layer marker genes. We compared single-cell RNA-seq of our iPSC-derived neurons to available single-cell RNA-seq data from human fetal and adult brain and found that iPSC-derived cortical neurons closely resembled primary fetal brain cells. Unexpectedly, a subpopulation of iPSC-derived neurons co-expressed canonical fetal deep and upper cortical layer markers. However, this appeared to be concordant with data from primary cells. Our results therefore provide reassurance that iPSC-derived cortical neurons are highly similar to primary cortical neurons at the level of single cells but suggest that current layer markers, although effective, may not be able to disambiguate cortical layer identity in all cells. PMID:26740550

Accurate cell counts in live mouse embryos using optical quadrature and differential interference contrast microscopy

NASA Astrophysics Data System (ADS)

Warger, William C., II; Newmark, Judith A.; Zhao, Bing; Warner, Carol M.; DiMarzio, Charles A.

2006-02-01

Present imaging techniques used in in vitro fertilization (IVF) clinics are unable to produce accurate cell counts in developing embryos past the eight-cell stage. We have developed a method that has produced accurate cell counts in live mouse embryos ranging from 13-25 cells by combining Differential Interference Contrast (DIC) and Optical Quadrature Microscopy. Optical Quadrature Microscopy is an interferometric imaging modality that measures the amplitude and phase of the signal beam that travels through the embryo. The phase is transformed into an image of optical path length difference, which is used to determine the maximum optical path length deviation of a single cell. DIC microscopy gives distinct cell boundaries for cells within the focal plane when other cells do not lie in the path to the objective. Fitting an ellipse to the boundary of a single cell in the DIC image and combining it with the maximum optical path length deviation of a single cell creates an ellipsoidal model cell of optical path length deviation. Subtracting the model cell from the Optical Quadrature image will either show the optical path length deviation of the culture medium or reveal another cell underneath. Once all the boundaries are used in the DIC image, the subtracted Optical Quadrature image is analyzed to determine the cell boundaries of the remaining cells. The final cell count is produced when no more cells can be subtracted. We have produced exact cell counts on 5 samples, which have been validated by Epi-Fluorescence images of Hoechst stained nuclei.

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

PubMed

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

2014-08-01

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

Gene expression distribution deconvolution in single-cell RNA sequencing.

PubMed

Wang, Jingshu; Huang, Mo; Torre, Eduardo; Dueck, Hannah; Shaffer, Sydney; Murray, John; Raj, Arjun; Li, Mingyao; Zhang, Nancy R

2018-06-26

Single-cell RNA sequencing (scRNA-seq) enables the quantification of each gene's expression distribution across cells, thus allowing the assessment of the dispersion, nonzero fraction, and other aspects of its distribution beyond the mean. These statistical characterizations of the gene expression distribution are critical for understanding expression variation and for selecting marker genes for population heterogeneity. However, scRNA-seq data are noisy, with each cell typically sequenced at low coverage, thus making it difficult to infer properties of the gene expression distribution from raw counts. Based on a reexamination of nine public datasets, we propose a simple technical noise model for scRNA-seq data with unique molecular identifiers (UMI). We develop deconvolution of single-cell expression distribution (DESCEND), a method that deconvolves the true cross-cell gene expression distribution from observed scRNA-seq counts, leading to improved estimates of properties of the distribution such as dispersion and nonzero fraction. DESCEND can adjust for cell-level covariates such as cell size, cell cycle, and batch effects. DESCEND's noise model and estimation accuracy are further evaluated through comparisons to RNA FISH data, through data splitting and simulations and through its effectiveness in removing known batch effects. We demonstrate how DESCEND can clarify and improve downstream analyses such as finding differentially expressed genes, identifying cell types, and selecting differentiation markers. Copyright © 2018 the Author(s). Published by PNAS.

Visualization of Arenavirus RNA Species in Individual Cells by Single-Molecule Fluorescence In Situ Hybridization Suggests a Model of Cyclical Infection and Clearance during Persistence.

PubMed

King, Benjamin R; Samacoits, Aubin; Eisenhauer, Philip L; Ziegler, Christopher M; Bruce, Emily A; Zenklusen, Daniel; Zimmer, Christophe; Mueller, Florian; Botten, Jason

2018-06-15

Lymphocytic choriomeningitis mammarenavirus (LCMV) is an enveloped, negative-strand RNA virus that causes serious disease in humans but establishes an asymptomatic, lifelong infection in reservoir rodents. Different models have been proposed to describe how arenaviruses regulate the replication and transcription of their bisegmented, single-stranded RNA genomes, particularly during persistent infection. However, these models were based largely on viral RNA profiling data derived from entire populations of cells. To better understand LCMV replication and transcription at the single-cell level, we established a high-throughput, single-molecule fluorescence in situ hybridization (smFISH) image acquisition and analysis pipeline and examined viral RNA species at discrete time points from virus entry through the late stages of persistent infection in vitro We observed the transcription of viral nucleoprotein and polymerase mRNAs from the incoming S and L segment genomic RNAs, respectively, within 1 h of infection, whereas the transcription of glycoprotein mRNA from the S segment antigenome required ∼4 to 6 h. This confirms the temporal separation of viral gene expression expected due to the ambisense coding strategy of arenaviruses and also suggests that antigenomic RNA contained in virions is not transcriptionally active upon entry. Viral replication and transcription peaked at 36 h postinfection, followed by a progressive loss of viral RNAs over the next several days. During persistence, the majority of cells showed repeating cyclical waves of viral transcription and replication followed by the clearance of viral RNA. Thus, our data support a model of LCMV persistence whereby infected cells can spontaneously clear infection and become reinfected by viral reservoir cells that remain in the population. IMPORTANCE Arenaviruses are human pathogens that can establish asymptomatic, lifelong infections in their rodent reservoirs. Several models have been proposed to explain how arenavirus spread is restricted within host rodents, including the periodic accumulation and loss of replication-competent, but transcriptionally incompetent, viral genomes. A limitation of previous studies was the inability to enumerate viral RNA species at the single-cell level. We developed a high-throughput, smFISH assay and used it to quantitate lymphocytic choriomeningitis mammarenavirus (LCMV) replicative and transcriptional RNA species in individual cells at distinct time points following infection. Our findings support a model whereby productively infected cells can clear infection, including viral RNAs and antigen, and later be reinfected. This information improves our understanding of the timing and possible regulation of LCMV genome replication and transcription during infection. Importantly, the smFISH assay and data analysis pipeline developed here is easily adaptable to other RNA viruses. Copyright © 2018 American Society for Microbiology.

Single cell wound generates electric current circuit and cell membrane potential variations that requires calcium influx.

PubMed

Luxardi, Guillaume; Reid, Brian; Maillard, Pauline; Zhao, Min

2014-07-24

Breaching of the cell membrane is one of the earliest and most common causes of cell injury, tissue damage, and disease. If the compromise in cell membrane is not repaired quickly, irreversible cell damage, cell death and defective organ functions will result. It is therefore fundamentally important to efficiently repair damage to the cell membrane. While the molecular aspects of single cell wound healing are starting to be deciphered, its bio-physical counterpart has been poorly investigated. Using Xenopus laevis oocytes as a model for single cell wound healing, we describe the temporal and spatial dynamics of the wound electric current circuitry and the temporal dynamics of cell membrane potential variation. In addition, we show the role of calcium influx in controlling electric current circuitry and cell membrane potential variations. (i) Upon wounding a single cell: an inward electric current appears at the wound center while an outward electric current is observed at its sides, illustrating the wound electric current circuitry; the cell membrane is depolarized; calcium flows into the cell. (ii) During cell membrane re-sealing: the wound center current density is maintained for a few minutes before decreasing; the cell membrane gradually re-polarizes; calcium flow into the cell drops. (iii) In conclusion, calcium influx is required for the formation and maintenance of the wound electric current circuitry, for cell membrane re-polarization and for wound healing.

Single agent and synergistic combinatorial efficacy of first-in-class small molecule imipridone ONC201 in hematological malignancies.

PubMed

Prabhu, Varun V; Talekar, Mala K; Lulla, Amriti R; Kline, C Leah B; Zhou, Lanlan; Hall, Junior; Van den Heuvel, A Pieter J; Dicker, David T; Babar, Jawad; Grupp, Stephan A; Garnett, Mathew J; McDermott, Ultan; Benes, Cyril H; Pu, Jeffrey J; Claxton, David F; Khan, Nadia; Oster, Wolfgang; Allen, Joshua E; El-Deiry, Wafik S

2018-01-01

ONC201, founding member of the imipridone class of small molecules, is currently being evaluated in advancer cancer clinical trials. We explored single agent and combinatorial efficacy of ONC201 in preclinical models of hematological malignancies. ONC201 demonstrated (GI50 1-8 µM) dose- and time-dependent efficacy in acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL), mantle cell lymphoma (MCL), Burkitt's lymphoma, anaplastic large cell lymphoma (ALCL), cutaneous T-cell lymphoma (CTCL), Hodgkin's lymphoma (nodular sclerosis) and multiple myeloma (MM) cell lines including cells resistant to standard of care (dexamethasone in MM) and primary samples. ONC201 induced caspase-dependent apoptosis that involved activation of the integrated stress response (ATF4/CHOP) pathway, inhibition of Akt phosphorylation, Foxo3a activation, downregulation of cyclin D1, IAP and Bcl-2 family members. ONC201 synergistically reduced cell viability in combination with cytarabine and 5-azacytidine in AML cells. ONC201 combined with cytarabine in a Burkitt's lymphoma xenograft model induced tumor growth inhibition that was superior to either agent alone. ONC201 synergistically combined with bortezomib in MM, MCL and ALCL cells and with ixazomib or dexamethasone in MM cells. ONC201 combined with bortezomib in a Burkitt's lymphoma xenograft model reduced tumor cell density and improved CHOP induction compared to either agent alone. These results serve as a rationale for ONC201 single-agent trials in relapsed/refractory acute leukemia, non-Hodgkin's lymphoma, MM and combination trial with dexamethasone in MM, provide pharmacodynamic biomarkers and identify further synergistic combinatorial regimens that can be explored in the clinic.

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

PubMed

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

2014-09-01

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

Selective Gene Transfection of Individual Cells In Vitro with Plasmonic Nanobubbles

PubMed Central

Lukianova-Hleb, Ekaterina; Samaniego, Adam P.; Wen, Jianguo; Metelitsa, Leonid; Chang, Chung-Che; Lapotko, Dmitri

2011-01-01

Gene delivery and transfection of eukaryotic cells is widely used for research and for developing gene cell therapy. However, the existing methods lack selectivity, efficacy and safety when heterogeneous cell systems must be treated. We report a new method that employs plasmonic nanobubbles (PNBs) for delivery and transfection. A PNB is a novel, tunable cellular agent with a dual mechanical and optical action due to the formation of the vapor nanobubble around a transiently heated gold nanoparticle upon its exposure to a laser pulse. PNBs enabled the mechanical injection of the extracellular cDNA plasmid into the cytoplasm of individual target living cells, cultured leukemia cells and human CD34+CD117+ stem cells and expression of a green fluorescent protein (GFP) in those cells. PNB generation and lifetime correlated with the expression of green fluorescent protein in PNB-treated cells. Optical scattering by PNBs additionally provided the detection of the target cells and the guidance of cDNA injection at single cell level. In both cell models PNBs demonstrated a gene transfection effect in a single pulse treatment with high selectivity, efficacy and safety. Thus, PNBs provided targeted gene delivery at the single cell level in a single pulse procedure that can be used for safe and effective gene therapy. PMID:21315120

Selective gene transfection of individual cells in vitro with plasmonic nanobubbles.

PubMed

Lukianova-Hleb, Ekaterina Y; Samaniego, Adam P; Wen, Jianguo; Metelitsa, Leonid S; Chang, Chung-Che; Lapotko, Dmitri O

2011-06-10

Gene delivery and transfection of eukaryotic cells are widely used for research and for developing gene cell therapy. However, the existing methods lack selectivity, efficacy and safety when heterogeneous cell systems must be treated. We report a new method that employs plasmonic nanobubbles (PNBs) for delivery and transfection. A PNB is a novel, tunable cellular agent with a dual mechanical and optical action due to the formation of the vapor nanobubble around a transiently heated gold nanoparticle upon its exposure to a laser pulse. PNBs enabled the mechanical injection of the extracellular cDNA plasmid into the cytoplasm of individual target living cells, cultured leukemia cells and human CD34+ CD117+ stem cells and expression of a green fluorescent protein (GFP) in those cells. PNB generation and lifetime correlated with the expression of green fluorescent protein in PNB-treated cells. Optical scattering by PNBs additionally provided the detection of the target cells and the guidance of cDNA injection at single cell level. In both cell models PNBs demonstrated a gene transfection effect in a single pulse treatment with high selectivity, efficacy and safety. Thus, PNBs provided targeted gene delivery at the single cell level in a single pulse procedure that can be used for safe and effective gene therapy. Copyright © 2011 Elsevier B.V. All rights reserved.

Electrical coupling of single cardiac rat myocytes to field-effect and bipolar transistors.

PubMed

Kind, Thomas; Issing, Matthias; Arnold, Rüdiger; Müller, Bernt

2002-12-01

A novel bipolar transistor for extracellular recording the electrical activity of biological cells is presented, and the electrical behavior compared with the field-effect transistor (FET). Electrical coupling is examined between single cells separated from the heart of adults rats (cardiac myocytes) and both types of transistors. To initiate a local extracellular voltage, the cells are periodically stimulated by a patch pipette in voltage clamp and current clamp mode. The local extracellular voltage is measured by the planar integrated electronic sensors: the bipolar and the FET. The small signal transistor currents correspond to the local extracellular voltage. The two types of sensor transistors used here were developed and manufactured in the laboratory of our institute. The manufacturing process and the interfaces between myocytes and transistors are described. The recordings are interpreted by way of simulation based on the point-contact model and the single cardiac myocyte model.

Finite Element Analysis of Single Cell Stiffness Measurements Using PZT-Integrated Buckling Nanoneedles

PubMed Central

Rad, Maryam Alsadat; Tijjani, Auwal Shehu; Ahmad, Mohd Ridzuan; Auwal, Shehu Muhammad

2016-01-01

This paper proposes a new technique for real-time single cell stiffness measurement using lead zirconate titanate (PZT)-integrated buckling nanoneedles. The PZT and the buckling part of the nanoneedle have been modelled and validated using the ABAQUS software. The two parts are integrated together to function as a single unit. After calibration, the stiffness, Young’s modulus, Poisson’s ratio and sensitivity of the PZT-integrated buckling nanoneedle have been determined to be 0.7100 N·m−1, 123.4700 GPa, 0.3000 and 0.0693 V·m·N−1, respectively. Three Saccharomyces cerevisiae cells have been modelled and validated based on compression tests. The average global stiffness and Young’s modulus of the cells are determined to be 10.8867 ± 0.0094 N·m−1 and 110.7033 ± 0.0081 MPa, respectively. The nanoneedle and the cell have been assembled to measure the local stiffness of the single Saccharomyces cerevisiae cells The local stiffness, Young’s modulus and PZT output voltage of the three different size Saccharomyces cerevisiae have been determined at different environmental conditions. We investigated that, at low temperature the stiffness value is low to adapt to the change in the environmental condition. As a result, Saccharomyces cerevisiae becomes vulnerable to viral and bacterial attacks. Therefore, the proposed technique will serve as a quick and accurate process to diagnose diseases at early stage in a cell for effective treatment. PMID:28025571

A generalized target theory and its applications.

PubMed

Zhao, Lei; Mi, Dong; Hu, Bei; Sun, Yeqing

2015-09-28

Different radiobiological models have been proposed to estimate the cell-killing effects, which are very important in radiotherapy and radiation risk assessment. However, most applied models have their own scopes of application. In this work, by generalizing the relationship between "hit" and "survival" in traditional target theory with Yager negation operator in Fuzzy mathematics, we propose a generalized target model of radiation-induced cell inactivation that takes into account both cellular repair effects and indirect effects of radiation. The simulation results of the model and the rethinking of "the number of targets in a cell" and "the number of hits per target" suggest that it is only necessary to investigate the generalized single-hit single-target (GSHST) in the present theoretical frame. Analysis shows that the GSHST model can be reduced to the linear quadratic model and multitarget model in the low-dose and high-dose regions, respectively. The fitting results show that the GSHST model agrees well with the usual experimental observations. In addition, the present model can be used to effectively predict cellular repair capacity, radiosensitivity, target size, especially the biologically effective dose for the treatment planning in clinical applications.

Performance analysis of high-concentrated multi-junction solar cells in hot climate

NASA Astrophysics Data System (ADS)

Ghoneim, Adel A.; Kandil, Kandil M.; Alzanki, Talal H.; Alenezi, Mohammad R.

2018-03-01

Multi-junction concentrator solar cells are a promising technology as they can fulfill the increasing energy demand with renewable sources. Focusing sunlight upon the aperture of multi-junction photovoltaic (PV) cells can generate much greater power densities than conventional PV cells. So, concentrated PV multi-junction solar cells offer a promising way towards achieving minimum cost per kilowatt-hour. However, these cells have many aspects that must be fixed to be feasible for large-scale energy generation. In this work, a model is developed to analyze the impact of various atmospheric factors on concentrator PV performance. A single-diode equivalent circuit model is developed to examine multi-junction cells performance in hot weather conditions, considering the impacts of both temperature and concentration ratio. The impacts of spectral variations of irradiance on annual performance of various high-concentrated photovoltaic (HCPV) panels are examined, adapting spectra simulations using the SMARTS model. Also, the diode shunt resistance neglected in the existing models is considered in the present model. The present results are efficiently validated against measurements from published data to within 2% accuracy. Present predictions show that the single-diode model considering the shunt resistance gives accurate and reliable results. Also, aerosol optical depth (AOD) and air mass are most important atmospheric parameters having a significant impact on HCPV cell performance. In addition, the electrical efficiency (η) is noticed to increase with concentration to a certain concentration degree after which it decreases. Finally, based on the model predictions, let us conclude that the present model could be adapted properly to examine HCPV cells' performance over a broad range of operating conditions.

Identification of unique release kinetics of serotonin from guinea-pig and human enterochromaffin cells

PubMed Central

Raghupathi, Ravinarayan; Duffield, Michael D; Zelkas, Leah; Meedeniya, Adrian; Brookes, Simon J H; Sia, Tiong Cheng; Wattchow, David A; Spencer, Nick J; Keating, Damien J

2013-01-01

The major source of serotonin (5-HT) in the body is the enterochromaffin (EC) cells lining the intestinal mucosa of the gastrointestinal tract. Despite the fact that EC cells synthesise ∼95% of total body 5-HT, and that this 5-HT has important paracrine and endocrine roles, no studies have investigated the mechanisms of 5-HT release from single primary EC cells. We have developed a rapid primary culture of guinea-pig and human EC cells, allowing analysis of single EC cell function using electrophysiology, electrochemistry, Ca2+ imaging, immunocytochemistry and 3D modelling. Ca2+ enters EC cells upon stimulation and triggers quantal 5-HT release via L-type Ca2+ channels. Real time amperometric techniques reveal that EC cells release 5-HT at rest and this release increases upon stimulation. Surprisingly for an endocrine cell storing 5-HT in large dense core vesicles (LDCVs), EC cells release 70 times less 5-HT per fusion event than catecholamine released from similarly sized LDCVs in endocrine chromaffin cells, and the vesicle release kinetics instead resembles that observed in mammalian synapses. Furthermore, we measured EC cell density along the gastrointestinal tract to create three-dimensional (3D) simulations of 5-HT diffusion using the minimal number of variables required to understand the physiological relevance of single cell 5-HT release in the whole-tissue milieu. These models indicate that local 5-HT levels are likely to be maintained around the activation threshold for mucosal 5-HT receptors and that this is dependent upon stimulation and location within the gastrointestinal tract. This is the first study demonstrating single cell 5-HT release in primary EC cells. The mode of 5-HT release may represent a unique mode of exocytosis amongst endocrine cells and is functionally relevant to gastrointestinal sensory and motor function. PMID:24099799

Isoform-level gene expression patterns in single-cell RNA-sequencing data.

PubMed

Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Pawitan, Yudi; Rantalainen, Mattias

2018-02-27

RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data. We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in three independent datasets. We assigned the pattern types to each of 16,562 isoform-pairs from 4,929 genes. Among those, 26% of the discovered patterns were significant (p<0.05), while remaining patterns are possibly effects of transcriptional bursting, drop-out and stochastic biological heterogeneity. Furthermore, 32% of genes discovered through differential-pattern analysis were not detected by differential-expression analysis. The effect of drop-out events, mean expression level, and properties of the expression distribution on the performances of ISOP were also investigated through simulated datasets. To conclude, ISOP provides a novel approach for characterization of isoformlevel preference, commitment and heterogeneity in single-cell RNA-sequencing data. The ISOP method has been implemented as a R package and is available at https://github.com/nghiavtr/ISOP under a GPL-3 license. mattias.rantalainen@ki.se. Supplementary data are available at Bioinformatics online.

Single cell isolation process with laser induced forward transfer.

PubMed

Deng, Yu; Renaud, Philippe; Guo, Zhongning; Huang, Zhigang; Chen, Ying

2017-01-01

A viable single cell is crucial for studies of single cell biology. In this paper, laser-induced forward transfer (LIFT) was used to isolate individual cell with a closed chamber designed to avoid contamination and maintain humidity. Hela cells were used to study the impact of laser pulse energy, laser spot size, sacrificed layer thickness and working distance. The size distribution, number and proliferation ratio of separated cells were statistically evaluated. Glycerol was used to increase the viscosity of the medium and alginate were introduced to soften the landing process. The role of laser pulse energy, the spot size and the thickness of titanium in energy absorption in LIFT process was theoretically analyzed with Lambert-Beer and a thermal conductive model. After comprehensive analysis, mechanical damage was found to be the dominant factor affecting the size and proliferation ratio of the isolated cells. An orthogonal experiment was conducted, and the optimal conditions were determined as: laser pulse energy, 9 μJ; spot size, 60 μm; thickness of titanium, 12 nm; working distance, 700 μm;, glycerol, 2% and alginate depth, greater than 1 μm. With these conditions, along with continuous incubation, a single cell could be transferred by the LIFT with one shot, with limited effect on cell size and viability. LIFT conducted in a closed chamber under optimized condition is a promising method for reliably isolating single cells.

Biomaterial science meets computational biology.

PubMed

Hutmacher, Dietmar W; Little, J Paige; Pettet, Graeme J; Loessner, Daniela

2015-05-01

There is a pressing need for a predictive tool capable of revealing a holistic understanding of fundamental elements in the normal and pathological cell physiology of organoids in order to decipher the mechanoresponse of cells. Therefore, the integration of a systems bioengineering approach into a validated mathematical model is necessary to develop a new simulation tool. This tool can only be innovative by combining biomaterials science with computational biology. Systems-level and multi-scale experimental data are incorporated into a single framework, thus representing both single cells and collective cell behaviour. Such a computational platform needs to be validated in order to discover key mechano-biological factors associated with cell-cell and cell-niche interactions.

Combining Microinjection and Immunoblotting to Analyze MAP Kinase Phosphorylation in Single Starfish Oocytes and Eggs

NASA Astrophysics Data System (ADS)

Carroll, David J.; Hua, Wei

The starfish oocyte has proven useful for studies involving microinjection because it is relatively large (190 μm) and optically clear. These oocytes are easily obtained from the ovary arrested at prophase of meiosis I, making them useful as a model system for the study of cell cycle-related events. In this chapter, a method for combining microinjection with immunoblotting of single cells is described. Individual starfish oocytes are injected, removed from the microinjection chamber, and analyzed by immunoblotting for the dual-phosphorylated form of mitogen-activated protein kinase (MAPK). This method will allow for experiments testing the regulation of MAPK in single cells and for the manipulation of these cells by a quantitative microinjection technique.

Marker-free detection of progenitor cell differentiation by analysis of Brownian motion in micro-wells.

PubMed

Sekhavati, Farzad; Endele, Max; Rappl, Susanne; Marel, Anna-Kristina; Schroeder, Timm; Rädler, Joachim O

2015-02-01

The kinetics of stem and progenitor cell differentiation at the single-cell level provides essential clues to the complexity of the underlying decision-making circuits. In many hematopoietic progenitor cells, differentiation is accompanied by the expression of lineage-specific markers and by a transition from a non-adherent to an adherent state. Here, using the granulocyte-macrophage progenitor (GMP) as a model, we introduce a label-free approach that allows one to follow the course of this transition in hundreds of single cells in parallel. We trap single cells in patterned arrays of micro-wells and use phase-contrast time-lapse movies to distinguish non-adherent from adherent cells by an analysis of Brownian motion. This approach allowed us to observe the kinetics of induced differentiation of primary bone-marrow-derived GMPs into macrophages. The time lapse started 2 hours after addition of the cytokine M-CSF, and nearly 80% of the population had accomplished the transition within the first 20 h. The analysis of Brownian motion proved to be a sensitive and robust tool for monitoring the transition, and thus provides a high-throughput method for the study of cell differentiation at the single-cell level.

Single-Cell Analysis Reveals Early Manifestation of Cancerous Phenotype in Pre-Malignant Esophageal Cells

PubMed Central

Wang, Jiangxin; Shi, Xu; Johnson, Roger H.; Kelbauskas, Laimonas; Zhang, Weiwen; Meldrum, Deirdre R.

2013-01-01

Cellular heterogeneity plays a pivotal role in a variety of functional processes in vivo including carcinogenesis. However, our knowledge about cell-to-cell diversity and how differences in individual cells manifest in alterations at the population level remains very limited mainly due to the lack of appropriate tools enabling studies at the single-cell level. We present a study on changes in cellular heterogeneity in the context of pre-malignant progression in response to hypoxic stress. Utilizing pre-malignant progression of Barrett’s esophagus (BE) as a disease model system we studied molecular mechanisms underlying the progression from metaplastic to dysplastic (pre-cancerous) stage. We used newly developed methods enabling measurements of cell-to-cell differences in copy numbers of mitochondrial DNA, expression levels of a set of mitochondrial and nuclear genes involved in hypoxia response pathways, and mitochondrial membrane potential. In contrast to bulk cell studies reported earlier, our study shows significant differences between metaplastic and dysplastic BE cells in both average values and single-cell parameter distributions of mtDNA copy numbers, mitochondrial function, and mRNA expression levels of studied genes. Based on single-cell data analysis, we propose that mitochondria may be one of the key factors in pre-malignant progression in BE. PMID:24116039

Evaluation of a Mouse Embryonic Stem Cell Adherent Cell Differentiation and Cytotoxicity (ACDC) assay (Keystone Sym)

EPA Science Inventory

Our goal is to establish an in vitro model system to evaluate chemical effects using a single stem cell culture technique that would improve throughput and provide quantitative markers of differentiation and cell number. To this end, we have used an adherent cell differentiation ...

Bi-specific splice-switching PMO oligonucleotides conjugated via a single peptide active in a mouse model of Duchenne muscular dystrophy

PubMed Central

Shabanpoor, Fazel; McClorey, Graham; Saleh, Amer F.; Järver, Peter; Wood, Matthew J.A.; Gait, Michael J.

2015-01-01

The potential for therapeutic application of splice-switching oligonucleotides (SSOs) to modulate pre-mRNA splicing is increasingly evident in a number of diseases. However, the primary drawback of this approach is poor cell and in vivo oligonucleotide uptake efficacy. Biological activities can be significantly enhanced through the use of synthetically conjugated cationic cell penetrating peptides (CPPs). Studies to date have focused on the delivery of a single SSO conjugated to a CPP, but here we describe the conjugation of two phosphorodiamidate morpholino oligonucleotide (PMO) SSOs to a single CPP for simultaneous delivery and pre-mRNA targeting of two separate genes, exon 23 of the Dmd gene and exon 5 of the Acvr2b gene, in a mouse model of Duchenne muscular dystrophy. Conjugations of PMOs to a single CPP were carried out through an amide bond in one case and through a triazole linkage (‘click chemistry’) in the other. The most active bi-specific CPP–PMOs demonstrated comparable exon skipping levels for both pre-mRNA targets when compared to individual CPP–PMO conjugates both in cell culture and in vivo in the mdx mouse model. Thus, two SSOs with different target sequences conjugated to a single CPP are biologically effective and potentially suitable for future therapeutic exploitation. PMID:25468897

Cell refractive index for cell biology and disease diagnosis: past, present and future.

PubMed

Liu, P Y; Chin, L K; Ser, W; Chen, H F; Hsieh, C-M; Lee, C-H; Sung, K-B; Ayi, T C; Yap, P H; Liedberg, B; Wang, K; Bourouina, T; Leprince-Wang, Y

2016-02-21

Cell refractive index is a key biophysical parameter, which has been extensively studied. It is correlated with other cell biophysical properties including mechanical, electrical and optical properties, and not only represents the intracellular mass and concentration of a cell, but also provides important insight for various biological models. Measurement techniques developed earlier only measure the effective refractive index of a cell or a cell suspension, providing only limited information on cell refractive index and hence hindering its in-depth analysis and correlation. Recently, the emergence of microfluidic, photonic and imaging technologies has enabled the manipulation of a single cell and the 3D refractive index of a single cell down to sub-micron resolution, providing powerful tools to study cells based on refractive index. In this review, we provide an overview of cell refractive index models and measurement techniques including microfluidic chip-based techniques for the last 50 years, present the applications and significance of cell refractive index in cell biology, hematology, and pathology, and discuss future research trends in the field, including 3D imaging methods, integration with microfluidics and potential applications in new and breakthrough research areas.

In vitro generation of three-dimensional substrate-adherent embryonic stem cell-derived neural aggregates for application in animal models of neurological disorders.

PubMed

Hargus, Gunnar; Cui, Yi-Fang; Dihné, Marcel; Bernreuther, Christian; Schachner, Melitta

2012-05-01

In vitro-differentiated embryonic stem (ES) cells comprise a useful source for cell replacement therapy, but the efficiency and safety of a translational approach are highly dependent on optimized protocols for directed differentiation of ES cells into the desired cell types in vitro. Furthermore, the transplantation of three-dimensional ES cell-derived structures instead of a single-cell suspension may improve graft survival and function by providing a beneficial microenvironment for implanted cells. To this end, we have developed a new method to efficiently differentiate mouse ES cells into neural aggregates that consist predominantly (>90%) of postmitotic neurons, neural progenitor cells, and radial glia-like cells. When transplanted into the excitotoxically lesioned striatum of adult mice, these substrate-adherent embryonic stem cell-derived neural aggregates (SENAs) showed significant advantages over transplanted single-cell suspensions of ES cell-derived neural cells, including improved survival of GABAergic neurons, increased cell migration, and significantly decreased risk of teratoma formation. Furthermore, SENAs mediated functional improvement after transplantation into animal models of Parkinson's disease and spinal cord injury. This unit describes in detail how SENAs are efficiently derived from mouse ES cells in vitro and how SENAs are isolated for transplantation. Furthermore, methods are presented for successful implantation of SENAs into animal models of Huntington's disease, Parkinson's disease, and spinal cord injury to study the effects of stem cell-derived neural aggregates in a disease context in vivo.

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

NASA Astrophysics Data System (ADS)

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

2011-02-01

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

Effect of Morphologic Features of Neurons on the Extracellular Electric Potential: A Simulation Study Using Cable Theory and Electro-Quasi-Static Equations.

PubMed

Bestel, R; Appali, R; van Rienen, U; Thielemann, C

2017-11-01

Microelectrode arrays serve as an indispensable tool in electro-physiological research to study the electrical activity of neural cells, enabling measurements of single cell as well as network communication analysis. Recent experimental studies have reported that the neuronal geometry has an influence on electrical signaling and extracellular recordings. However, the corresponding mechanisms are not yet fully understood and require further investigation. Allowing systematic parameter studies, computational modeling provides the opportunity to examine the underlying effects that influence extracellular potentials. In this letter, we present an in silico single cell model to analyze the effect of geometrical variability on the extracellular electric potentials. We describe finite element models of a single neuron with varying geometric complexity in three-dimensional space. The electric potential generation of the neuron is modeled using Hodgkin-Huxley equations. The signal propagation is described with electro-quasi-static equations, and results are compared with corresponding cable equation descriptions. Our results show that both the geometric dimensions and the distribution of ion channels of a neuron are critical factors that significantly influence both the amplitude and shape of extracellular potentials.

Time-lapse electrical impedance spectroscopy for monitoring the cell cycle of single immobilized S. pombe cells.

PubMed

Zhu, Zhen; Frey, Olivier; Haandbaek, Niels; Franke, Felix; Rudolf, Fabian; Hierlemann, Andreas

2015-11-26

As a complement and alternative to optical methods, wide-band electrical impedance spectroscopy (EIS) enables multi-parameter, label-free and real-time detection of cellular and subcellular features. We report on a microfluidics-based system designed to reliably capture single rod-shaped Schizosaccharomyces pombe cells by applying suction through orifices in a channel wall. The system enables subsequent culturing of immobilized cells in an upright position, while dynamic changes in cell-cycle state and morphology were continuously monitored through EIS over a broad frequency range. Besides measuring cell growth, clear impedance signals for nuclear division have been obtained. The EIS system has been characterized with respect to sensitivity and detection limits. The spatial resolution in measuring cell length was 0.25 μm, which corresponds to approximately a 5-min interval of cell growth under standard conditions. The comprehensive impedance data sets were also used to determine the occurrence of nuclear division and cytokinesis. The obtained results have been validated through concurrent confocal imaging and plausibilized through comparison with finite-element modeling data. The possibility to monitor cellular and intracellular features of single S. pombe cells during the cell cycle at high spatiotemporal resolution renders the presented microfluidics-based EIS system a suitable tool for dynamic single-cell investigations.

Time-lapse electrical impedance spectroscopy for monitoring the cell cycle of single immobilized S. pombe cells

PubMed Central

Zhu, Zhen; Frey, Olivier; Haandbaek, Niels; Franke, Felix; Rudolf, Fabian; Hierlemann, Andreas

2015-01-01

As a complement and alternative to optical methods, wide-band electrical impedance spectroscopy (EIS) enables multi-parameter, label-free and real-time detection of cellular and subcellular features. We report on a microfluidics-based system designed to reliably capture single rod-shaped Schizosaccharomyces pombe cells by applying suction through orifices in a channel wall. The system enables subsequent culturing of immobilized cells in an upright position, while dynamic changes in cell-cycle state and morphology were continuously monitored through EIS over a broad frequency range. Besides measuring cell growth, clear impedance signals for nuclear division have been obtained. The EIS system has been characterized with respect to sensitivity and detection limits. The spatial resolution in measuring cell length was 0.25 μm, which corresponds to approximately a 5-min interval of cell growth under standard conditions. The comprehensive impedance data sets were also used to determine the occurrence of nuclear division and cytokinesis. The obtained results have been validated through concurrent confocal imaging and plausibilized through comparison with finite-element modeling data. The possibility to monitor cellular and intracellular features of single S. pombe cells during the cell cycle at high spatiotemporal resolution renders the presented microfluidics-based EIS system a suitable tool for dynamic single-cell investigations. PMID:26608589

Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

PubMed Central

Kachalo, Sëma; Naveed, Hammad; Cao, Youfang; Zhao, Jieling; Liang, Jie

2015-01-01

Geometric and mechanical properties of individual cells and interactions among neighboring cells are the basis of formation of tissue patterns. Understanding the complex interplay of cells is essential for gaining insight into embryogenesis, tissue development, and other emerging behavior. Here we describe a cell model and an efficient geometric algorithm for studying the dynamic process of tissue formation in 2D (e.g. epithelial tissues). Our approach improves upon previous methods by incorporating properties of individual cells as well as detailed description of the dynamic growth process, with all topological changes accounted for. Cell size, shape, and division plane orientation are modeled realistically. In addition, cell birth, cell growth, cell shrinkage, cell death, cell division, cell collision, and cell rearrangements are now fully accounted for. Different models of cell-cell interactions, such as lateral inhibition during the process of growth, can be studied in detail. Cellular pattern formation for monolayered tissues from arbitrary initial conditions, including that of a single cell, can also be studied in detail. Computational efficiency is achieved through the employment of a special data structure that ensures access to neighboring cells in constant time, without additional space requirement. We have successfully generated tissues consisting of more than 20,000 cells starting from 2 cells within 1 hour. We show that our model can be used to study embryogenesis, tissue fusion, and cell apoptosis. We give detailed study of the classical developmental process of bristle formation on the epidermis of D. melanogaster and the fundamental problem of homeostatic size control in epithelial tissues. Simulation results reveal significant roles of solubility of secreted factors in both the bristle formation and the homeostatic control of tissue size. Our method can be used to study broad problems in monolayered tissue formation. Our software is publicly available. PMID:25974182

Process and design considerations for high-efficiency solar cells

NASA Technical Reports Server (NTRS)

Rohati, A.; Rai-Choudhury, P.

1985-01-01

This paper shows that oxide surface passivation coupled with optimum multilayer anti-reflective coating can provide approx. 3% (absolute) improvement in solar cell efficiency. Use of single-layer AR coating, without passivation, gives cell efficiencies in the range of 15 to 15.5% on high-quality, 4 ohm-cm as well as 0.1 to 0.2 ohm-cm float-zone silicon. Oxide surface passivation alone raises the cell efficiency to or = 17%. An optimum double-layer AR coating on oxide-passivated cells provides an additional approx. 5 to 10% improvement over a single-layer AR-coated cell, resulting in cell efficiencies in excess of 18%. Experimentally observed improvements are supported by model calculations and an approach to or = 20% efficient cells is discussed.

Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing.

PubMed

Casasent, Anna K; Schalck, Aislyn; Gao, Ruli; Sei, Emi; Long, Annalyssa; Pangburn, William; Casasent, Tod; Meric-Bernstam, Funda; Edgerton, Mary E; Navin, Nicholas E

2018-01-11

Ductal carcinoma in situ (DCIS) is an early-stage breast cancer that infrequently progresses to invasive ductal carcinoma (IDC). Genomic evolution has been difficult to delineate during invasion due to intratumor heterogeneity and the low number of tumor cells in the ducts. To overcome these challenges, we developed Topographic Single Cell Sequencing (TSCS) to measure genomic copy number profiles of single tumor cells while preserving their spatial context in tissue sections. We applied TSCS to 1,293 single cells from 10 synchronous patients with both DCIS and IDC regions in addition to exome sequencing. Our data reveal a direct genomic lineage between in situ and invasive tumor subpopulations and further show that most mutations and copy number aberrations evolved within the ducts prior to invasion. These results support a multiclonal invasion model, in which one or more clones escape the ducts and migrate into the adjacent tissues to establish the invasive carcinomas. Copyright © 2017 Elsevier Inc. All rights reserved.

Regulation of cell fate determination by single-repeat R3 MYB transcription factors in Arabidopsis

PubMed Central

Wang, Shucai; Chen, Jin-Gui

2014-01-01

MYB transcription factors regulate multiple aspects of plant growth and development. Among the large family of MYB transcription factors, single-repeat R3 MYBs are characterized by their short sequence (<120 amino acids) consisting largely of the single MYB DNA-binding repeat. In the model plant Arabidopsis, R3 MYBs mediate lateral inhibition during epidermal patterning and are best characterized for their regulatory roles in trichome and root hair development. R3 MYBs act as negative regulators for trichome formation but as positive regulators for root hair development. In this article, we provide a comprehensive review on the role of R3 MYBs in the regulation of cell type specification in the model plant Arabidopsis. PMID:24782874

Regulation of Cell Fate Determination by Single-Repeat R3 MYB Transcription Factors in Arabidopsis

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

Wang, Shucai; Chen, Jay

2014-01-01

MYB transcription factors regulate multiple aspects of plant growth and development. Among the large family of MYB transcription factors, single-repeat R3 MYB are characterized by their short sequence (<120 amino acids) consisting largely of the single MYB DNA-binding repeat. In the model plant Arabidopsis, R3 MYBs mediate lateral inhibition during epidermal patterning and are best characterized for their regulatory roles in trichome and root hair development. R3 MYBs act as negative regulators for trichome formation but as positive regulators for root hair development. In this article, we provide a comprehensive review on the role of R3 MYBs in the regulationmore » of cell type specification in the model plant Arabidopsis.« less

Communication: phase transitions, criticality, and three-phase coexistence in constrained cell models.

PubMed

Nayhouse, Michael; Kwon, Joseph Sang-Il; Orkoulas, G

2012-05-28

In simulation studies of fluid-solid transitions, the solid phase is usually modeled as a constrained system in which each particle is confined to move in a single Wigner-Seitz cell. The constrained cell model has been used in the determination of fluid-solid coexistence via thermodynamic integration and other techniques. In the present work, the phase diagram of such a constrained system of Lennard-Jones particles is determined from constant-pressure simulations. The pressure-density isotherms exhibit inflection points which are interpreted as the mechanical stability limit of the solid phase. The phase diagram of the constrained system contains a critical and a triple point. The temperature and pressure at the critical and the triple point are both higher than those of the unconstrained system due to the reduction in the entropy caused by the single occupancy constraint.

Neutral competition of stem cells is skewed by proliferative changes downstream of Hh and Hpo.

PubMed

Amoyel, Marc; Simons, Benjamin D; Bach, Erika A

2014-10-16

Neutral competition, an emerging feature of stem cell homeostasis, posits that individual stem cells can be lost and replaced by their neighbors stochastically, resulting in chance dominance of a clone at the niche. A single stem cell with an oncogenic mutation could bias this process and clonally spread the mutation throughout the stem cell pool. The Drosophila testis provides an ideal system for testing this model. The niche supports two stem cell populations that compete for niche occupancy. Here, we show that cyst stem cells (CySCs) conform to the paradigm of neutral competition and that clonal deregulation of either the Hedgehog (Hh) or Hippo (Hpo) pathway allows a single CySC to colonize the niche. We find that the driving force behind such behavior is accelerated proliferation. Our results demonstrate that a single stem cell colonizes its niche through oncogenic mutation by co-opting an underlying homeostatic process. © 2014 The Authors.

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

PubMed Central

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

2017-01-01

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

Interrogation of inhibitor of nuclear factor κB α/nuclear factor κB (IκBα/NF-κB) negative feedback loop dynamics: from single cells to live animals in vivo.

PubMed

Moss, Britney L; Elhammali, Adnan; Fowlkes, Tiffanie; Gross, Shimon; Vinjamoori, Anant; Contag, Christopher H; Piwnica-Worms, David

2012-09-07

Full understanding of the biological significance of negative feedback processes requires interrogation at multiple scales as follows: in single cells, cell populations, and live animals in vivo. The transcriptionally coupled IκBα/NF-κB negative feedback loop, a pivotal regulatory node of innate immunity and inflammation, represents a model system for multiscalar reporters. Using a κB(5)→IκBα-FLuc bioluminescent reporter, we rigorously evaluated the dynamics of ΙκBα degradation and subsequent NF-κB transcriptional activity in response to diverse modes of TNFα stimulation. Modulating TNFα concentration or pulse duration yielded complex, reproducible, and differential ΙκBα dynamics in both cell populations and live single cells. Tremendous heterogeneity in the transcriptional amplitudes of individual responding cells was observed, which was greater than the heterogeneity in the transcriptional kinetics of responsive cells. Furthermore, administration of various TNFα doses in vivo generated ΙκBα dynamic profiles in the liver resembling those observed in single cells and populations of cells stimulated with TNFα pulses. This suggested that dose modulation of circulating TNFα was perceived by hepatocytes in vivo as pulses of increasing duration. Thus, a robust bioluminescent reporter strategy enabled rigorous quantitation of NF-κB/ΙκBα dynamics in both live single cells and cell populations and furthermore, revealed reproducible behaviors that informed interpretation of in vivo studies.

High-performance single cell genetic analysis using microfluidic emulsion generator arrays.

PubMed

Zeng, Yong; Novak, Richard; Shuga, Joe; Smith, Martyn T; Mathies, Richard A

2010-04-15

High-throughput genetic and phenotypic analysis at the single cell level is critical to advance our understanding of the molecular mechanisms underlying cellular function and dysfunction. Here we describe a high-performance single cell genetic analysis (SCGA) technique that combines high-throughput microfluidic emulsion generation with single cell multiplex polymerase chain reaction (PCR). Microfabricated emulsion generator array (MEGA) devices containing 4, 32, and 96 channels are developed to confer a flexible capability of generating up to 3.4 x 10(6) nanoliter-volume droplets per hour. Hybrid glass-polydimethylsiloxane diaphragm micropumps integrated into the MEGA chips afford uniform droplet formation, controlled generation frequency, and effective transportation and encapsulation of primer functionalized microbeads and cells. A multiplex single cell PCR method is developed to detect and quantify both wild type and mutant/pathogenic cells. In this method, microbeads functionalized with multiple forward primers targeting specific genes from different cell types are used for solid-phase PCR in droplets. Following PCR, the droplets are lysed and the beads are pooled and rapidly analyzed by multicolor flow cytometry. Using Escherichia coli bacterial cells as a model, we show that this technique enables digital detection of pathogenic E. coli O157 cells in a high background of normal K12 cells, with a detection limit on the order of 1/10(5). This result demonstrates that multiplex SCGA is a promising tool for high-throughput quantitative digital analysis of genetic variation in complex populations.

High-Performance Single Cell Genetic Analysis Using Microfluidic Emulsion Generator Arrays

PubMed Central

Zeng, Yong; Novak, Richard; Shuga, Joe; Smith, Martyn T.; Mathies, Richard A.

2010-01-01

High-throughput genetic and phenotypic analysis at the single cell level is critical to advance our understanding of the molecular mechanisms underlying cellular function and dysfunction. Here we describe a high-performance single cell genetic analysis (SCGA) technique that combines high-throughput microfluidic emulsion generation with single cell multiplex PCR. Microfabricated emulsion generator array (MEGA) devices containing 4, 32 and 96 channels are developed to confer a flexible capability of generating up to 3.4 × 106 nanoliter-volume droplets per hour. Hybrid glass-polydimethylsiloxane diaphragm micropumps integrated into the MEGA chips afford uniform droplet formation, controlled generation frequency, and effective transportation and encapsulation of primer functionalized microbeads and cells. A multiplex single cell PCR method is developed to detect and quantify both wild type and mutant/pathogenic cells. In this method, microbeads functionalized with multiple forward primers targeting specific genes from different cell types are used for solid-phase PCR in droplets. Following PCR, the droplets are lysed, the beads are pooled and rapidly analyzed by multi-color flow cytometry. Using E. coli bacterial cells as a model, we show that this technique enables digital detection of pathogenic E. coli O157 cells in a high background of normal K12 cells, with a detection limit on the order of 1:105. This result demonstrates that multiplex SCGA is a promising tool for high-throughput quantitative digital analysis of genetic variation in complex populations. PMID:20192178

Single-cell sequencing reveals karyotype heterogeneity in murine and human malignancies.

PubMed

Bakker, Bjorn; Taudt, Aaron; Belderbos, Mirjam E; Porubsky, David; Spierings, Diana C J; de Jong, Tristan V; Halsema, Nancy; Kazemier, Hinke G; Hoekstra-Wakker, Karina; Bradley, Allan; de Bont, Eveline S J M; van den Berg, Anke; Guryev, Victor; Lansdorp, Peter M; Colomé-Tatché, Maria; Foijer, Floris

2016-05-31

Chromosome instability leads to aneuploidy, a state in which cells have abnormal numbers of chromosomes, and is found in two out of three cancers. In a chromosomal instable p53 deficient mouse model with accelerated lymphomagenesis, we previously observed whole chromosome copy number changes affecting all lymphoma cells. This suggests that chromosome instability is somehow suppressed in the aneuploid lymphomas or that selection for frequently lost/gained chromosomes out-competes the CIN-imposed mis-segregation. To distinguish between these explanations and to examine karyotype dynamics in chromosome instable lymphoma, we use a newly developed single-cell whole genome sequencing (scWGS) platform that provides a complete and unbiased overview of copy number variations (CNV) in individual cells. To analyse these scWGS data, we develop AneuFinder, which allows annotation of copy number changes in a fully automated fashion and quantification of CNV heterogeneity between cells. Single-cell sequencing and AneuFinder analysis reveals high levels of copy number heterogeneity in chromosome instability-driven murine T-cell lymphoma samples, indicating ongoing chromosome instability. Application of this technology to human B cell leukaemias reveals different levels of karyotype heterogeneity in these cancers. Our data show that even though aneuploid tumours select for particular and recurring chromosome combinations, single-cell analysis using AneuFinder reveals copy number heterogeneity. This suggests ongoing chromosome instability that other platforms fail to detect. As chromosome instability might drive tumour evolution, karyotype analysis using single-cell sequencing technology could become an essential tool for cancer treatment stratification.

A Computational Study of the Development of Epithelial Acini: I. Sufficient Conditions for the Formation of a Hollow Structure

PubMed Central

Rejniak, Katarzyna A.; Anderson, Alexander R.A.

2013-01-01

Normal hollow epithelial acini are 3-dimensional culture structures that resemble the architecture and functions of normal breast glands and lobules. This experimental model enables in vitro investigations of genotypic and molecular abnormalities associated with epithelial cancers. However, the way in which the acinar structure is formed is not yet completely understood. Gaining more information about consecutive stages of acini development—starting from a single cell that gives rise to a cluster of randomly oriented cells, followed by cell differentiation that leads to a layer of polarised cells enclosing the hollow lumen—will provide insight into the transformations of eukaryotic cells that are necessary for their successful arrangement into an epithelium. In this paper, we introduce a two-dimensional single-cell-based model representing the cross section of a typical acinus. Using this model, we investigate mechanisms that lead to the unpolarised cell growth, cell polarisation, stabilisation of the acinar structure and maintenance of the hollow lumen and discuss the sufficient conditions for each stage of acinar formation. In the follow-up paper (Rejniak and Anderson, A computational study of the development of epithelial acini. II. Necessary conditions for structure and lumen stability), we investigate what morphological changes are observable in the growing acini when some assumptions of this model are relaxed. PMID:18188652

Automatic Stem Cell Detection in Microscopic Whole Mouse Cryo-imaging

PubMed Central

Wuttisarnwattana, Patiwet; Gargesha, Madhusudhana; Hof, Wouter van’t; Cooke, Kenneth R.

2016-01-01

With its single cell sensitivity over volumes as large as or larger than a mouse, cryo-imaging enables imaging of stem cell biodistribution, homing, engraftment, and molecular mechanisms. We developed and evaluated a highly automated software tool to detect fluorescently labeled stem cells within very large (~200GB) cryo-imaging datasets. Cell detection steps are: preprocess, remove immaterial regions, spatially filter to create features, identify candidate pixels, classify pixels using bagging decision trees, segment cell patches, and perform 3D labeling. There are options for analysis and visualization. To train the classifier, we created synthetic images by placing realistic digital cell models onto cryo-images of control mice devoid of cells. Very good cell detection results were (precision=98.49%, recall=99.97%) for synthetic cryo-images, (precision=97.81%, recall=97.71%) for manually evaluated, actual cryo-images, and <1% false positives in control mice. An α-multiplier applied to features allows one to correct for experimental variations in cell brightness due to labeling. On dim cells (37% of standard brightness), with correction, we improved recall (49.26%→99.36%) without a significant drop in precision (99.99%→99.75%). With tail vein injection, multipotent adult progenitor cells in a graft-versus-host-disease model in the first days post injection were predominantly found in lung, liver, spleen, and bone marrow. Distribution was not simply related to blood flow. The lung contained clusters of cells while other tissues contained single cells. Our methods provided stem cell distribution anywhere in mouse with single cell sensitivity. Methods should provide a rational means of evaluating dosing, delivery methods, cell enhancements, and mechanisms for therapeutic cells. PMID:26552080

Curcumin exerts its antitumor effects in a context dependent fashion.

PubMed

Kreutz, Dominique; Sinthuvanich, Chomdao; Bileck, Andrea; Janker, Lukas; Muqaku, Besnik; Slany, Astrid; Gerner, Christopher

2018-06-30

Proteome profiling profoundly contributes to the understanding of cell response mechanisms to drug actions. Such knowledge may become a key to improve personalized medicine. In the present study, the effects of the natural remedy curcumin on breast cancer model systems were investigated. MCF-7, ZR-75-1 and TGF-β1 pretreated fibroblasts, mimicking cancer-associated fibroblasts (CAFs), were treated independently as well as in tumor cell/CAF co-cultures. Remarkably, co-culturing with CAF-like cells (CLCs) induced different proteome alterations in MCF-7 and ZR-75-1 cells, respectively. Curcumin significantly induced HMOX1 in single cell type models and co-cultures. However, other curcumin effects differed. In the MCF-7/CLC co-culture, curcumin significantly down-regulated RC3H1, a repressor of inflammatory signaling. In the ZR-75-1/CLC co-culture, curcumin significantly down-regulated PEG10, an anti-apoptotic protein, and induced RRAGA, a pro-apoptotic protein involved in TNF-alpha signaling. Furthermore, curcumin induced AKR1C2, an important enzyme for progesterone metabolism. None of these specific curcumin effects were observed in single cell type cultures. All high-resolution mass spectrometry data are available via ProteomeXchange with the identifier PXD008719. The present data demonstrate that curcumin induces proteome alterations, potentially accounting for its known antitumor effects, in a strongly context-dependent fashion. Better means to understand and potentially predict individual variations of drug effects are urgently required. The present proteome profiling study of curcumin effects demonstrates the massive impact of the cell microenvironment on cell responses to drug action. Co-culture models apparently provide more biologically relevant information regarding curcumin effects than single cell type cultures. Copyright © 2018. Published by Elsevier B.V.

Toll-like receptor-2 agonist-allergen coupling efficiently redirects Th2 cell responses and inhibits allergic airway eosinophilia.

PubMed

Krishnaswamy, Jayendra Kumar; Jirmo, Adan Chari; Baru, Abdul Mannan; Ebensen, Thomas; Guzmán, Carlos A; Sparwasser, Tim; Behrens, Georg M N

2012-12-01

Toll-like receptor (TLR) agonists beneficially modulate allergic airway inflammation. However, the efficiency of TLR agonists varies considerably, and their exact cellular mechanisms (especially of TLR 2/6 agonists) are incompletely understood. We investigated at a cellular level whether the administration of the pharmacologically improved TLR2/6 agonist S-[2,3-bispalmitoyiloxy-(2R)-propyl]-R-cysteinyl-amido-monomethoxy polyethylene glycol (BPP) conjugated to antigenic peptide (BPP-OVA) could divert an existing Th2 response and influence airway eosinophilia. The effects of BPP-OVA on airway inflammation were assessed in a classic murine sensitization/challenge model and an adoptive transfer model, which involved the adoptive transfer of in vitro differentiated ovalbumin (OVA)-specific Th2 cells. Functional T-cell stimulation by lung dendritic cells (DCs) was determined both in vitro and in vivo, combined with a cytokine secretion analysis. A single mucosal application of BPP-OVA efficiently delivered antigen, led to TLR2-mediated DC activation, and resulted in OVA-specific T-cell proliferation via lung DCs in vivo. In alternative models of allergic airway disease, a single administration of BPP-OVA before OVA challenge (but not BPP alone) significantly reduced airway eosinophilia, most likely through altered antigen-specific T-cell stimulation via DCs. Analyses of adoptively transferred Th2-biased cells after BPP-OVA administration in vivo suggested that BPP-OVA guides antigen-specific Th2 cells to produce significantly higher amounts of IFN-γ upon allergen challenge. In conclusion, our data show for the first time that a single mucosal administration of a TLR 2/6 agonist-allergen conjugate can provoke IFN-γ responses in Th2-biased cells and alleviate allergic airway inflammation.

Old and new results about single-photon sensitivity in human vision

NASA Astrophysics Data System (ADS)

Nelson, Philip C.

2016-04-01

It is sometimes said that ‘our eyes can see single photons’. This article begins by finding a more precise version of that claim and reviewing evidence gathered for it up to around 1985 in two distinct realms, those of human psychophysics and single-cell physiology. Finding a single framework that accommodates both kinds of result is then a nontrivial challenge, and one that sets severe quantitative constraints on any model of dim-light visual processing. This article presents one such model and compares it to a recent experiment.

Intra- and Interdimeric Caspase-8 Self-Cleavage Controls Strength and Timing of CD95-Induced Apoptosis

PubMed Central

Kallenberger, Stefan M.; Beaudouin, Joël; Claus, Juliane; Fischer, Carmen; Sorger, Peter K.; Legewie, Stefan; Eils, Roland

2014-01-01

Apoptosis in response to the ligand CD95L (also known as Fas ligand) is initiated by caspase-8, which is activated by dimerization and self-cleavage at death-inducing signaling complexes (DISCs). Previous work indicated that the degree of substrate cleavage by caspase-8 determines whether a cell dies or survives in response to a death stimulus. To determine how a death ligand stimulus is effectively translated into caspase-8 activity, we assessed this activity over time in single cells with compartmentalized probes that are cleaved by caspase-8, and used multiscale modeling to simultaneously describe single-cell and population data with an ensemble of single-cell models. We derived and experimentally validated a minimal model in which cleavage of caspase-8 in the enzymatic domain occurs in an interdimeric manner through interaction between DISCs, whereas prodomain cleavage sites are cleaved in an intradimeric manner within DISCs. Modeling indicated that sustained membrane-bound caspase-8 activity is followed by transient cytosolic activity, which can be interpreted as a molecular timer mechanism reflected by a limited lifetime of active caspase-8. The activation of caspase-8 by combined intra- and interdimeric cleavage ensures weak signaling at low concentrations of CD95L and strongly accelerated activation at higher ligand concentrations, thereby contributing to precise control of apoptosis. PMID:24619646

Mammalian DNA single-strand break repair: an X-ra(y)ted affair.

PubMed

Caldecott, K W

2001-05-01

The genetic stability of living cells is continuously threatened by the presence of endogenous reactive oxygen species and other genotoxic molecules. Of particular threat are the thousands of DNA single-strand breaks that arise in each cell, each day, both directly from disintegration of damaged sugars and indirectly from the excision repair of damaged bases. If un-repaired, single-strand breaks can be converted into double-strand breaks during DNA replication, potentially resulting in chromosomal rearrangement and genetic deletion. Consequently, cells have adopted multiple pathways to ensure the rapid and efficient removal of single-strand breaks. A general feature of these pathways appears to be the extensive employment of protein-protein interactions to stimulate both the individual component steps and the overall repair reaction. Our current understanding of DNA single-strand break repair is discussed, and testable models for the architectural coordination of this important process are presented. Copyright 2001 John Wiley & Sons, Inc.

Application of Ce3+ single-doped complexes as solar spectral downshifters for enhancing photoelectric conversion efficiencies of a-Si-based solar cells

NASA Astrophysics Data System (ADS)

Song, Pei; Jiang, Chun

2013-05-01

The effect on photoelectric conversion efficiency of an a-Si-based solar cell by applying a solar spectral downshifter of rare earth ion Ce3+ single-doped complexes including yttrium aluminum garnet Y3Al5O12 single crystals, nanostructured ceramics, microstructured ceramics and B2O3-SiO2-Gd2O3-BaO glass is studied. The photoluminescence excitation spectra in the region 360-460 nm convert effectively into photoluminescence emission spectra in the region 450-550 nm where a-Si-based solar cells exhibit a higher spectral response. When these Ce3+ single-doped complexes are placed on the top of an a-Si-based solar cell as precursors for solar spectral downshifting, theoretical relative photoelectric conversion efficiencies of nc-Si:H and a-Si:H solar cells approach 1.09-1.13 and 1.04-1.07, respectively, by means of AMPS-1D numerical modeling, potentially benefiting an a-Si-based solar cell with a photoelectric efficiency improvement.

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

PubMed

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

2014-06-01

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

Single event upsets in semiconductor devices induced by highly ionising particles.

PubMed

Sannikov, A V

2004-01-01

A new model of single event upsets (SEUs), created in memory cells by heavy ions and high energy hadrons, has been developed. The model takes into account the spatial distribution of charge collection efficiency over the cell area not considered in previous approaches. Three-dimensional calculations made by the HADRON code have shown good agreement with experimental data for the energy dependence of proton SEU cross sections, sensitive depths and other SEU observables. The model is promising for prediction of SEU rates for memory chips exposed in space and in high-energy experiments as well as for the development of a high-energy neutron dosemeter based on the SEU effect.

From single cells to tissue architecture-a bottom-up approach to modelling the spatio-temporal organisation of complex multi-cellular systems.

PubMed

Galle, J; Hoffmann, M; Aust, G

2009-01-01

Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.

Single Cell Mathematical Model Successfully Replicates Key Features of GBM: Go-Or-Grow Is Not Necessary.

PubMed

Scribner, Elizabeth; Fathallah-Shaykh, Hassan M

2017-01-01

Glioblastoma (GBM) is a malignant brain tumor that continues to be associated with neurological morbidity and poor survival times. Brain invasion is a fundamental property of malignant glioma cells. The Go-or-Grow (GoG) phenotype proposes that cancer cell motility and proliferation are mutually exclusive. Here, we construct and apply a single glioma cell mathematical model that includes motility and angiogenesis and lacks the GoG phenotype. Simulations replicate key features of GBM including its multilayer structure (i.e.edema, enhancement, and necrosis), its progression patterns associated with bevacizumab treatment, and replicate the survival times of GBM treated or untreated with bevacizumab. These results suggest that the GoG phenotype is not a necessary property for the formation of the multilayer structure, recurrence patterns, and the poor survival times of patients diagnosed with GBM.

Cell-model prediction of the melting of a Lennard-Jones solid

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

Holian, B.L.

The classical free energy of the Lennard-Jones 6-12 solid is computed from a single-particle anharmonic cell model with a correction to the entropy given by the classical correlational entropy of quasiharmonic lattice dynamics. The free energy of the fluid is obtained from the Hansen-Ree analytic fit to Monte Carlo equation-of-state calculations. The resulting predictions of the solid-fluid coexistence curves by this corrected cell model of the solid are in excellent agreement with the computer experiments.

Elucidating the identity and behavior of spermatogenic stem cells in the mouse testis.

PubMed

Yoshida, Shosei

2012-09-01

Spermatogenesis in mice and other mammalians is supported by a robust stem cell system. Stem cells maintain themselves and continue to produce progeny that will differentiate into sperm over a long period. The pioneering studies conducted from the 1950s to the 1970s, which were based largely on extensive morphological analyses, have established the fundamentals of mammalian spermatogenesis and its stem cells. The prevailing so-called A(single) (A(s)) model, which was originally established in 1971, proposes that singly isolated A(s) spermatogonia are in fact the stem cells. In 1994, the first functional stem cell assay was established based on the formation of repopulating colonies after transplantation in germ cell-depleted host testes, which substantially accelerated the understanding of spermatogenic stem cells. However, because testicular tissues are dissociated into single-cell suspension before transplantation, it was impossible to evaluate the A(s) and other classical models solely by this technique. From 2007 onwards, functional assessment of stem cells without destroying the tissue architecture has become feasible by means of pulse-labeling and live-imaging strategies. Results obtained from these experiments have been challenging the classical thought of stem cells, in which stem cells are a limited number of specialized cells undergoing asymmetric division to produce one self-renewing and one differentiating daughter cells. In contrast, the emerging data suggest that an extended and heterogeneous population of cells exhibiting different degrees of self-renewing and differentiating probabilities forms a reversible, flexible, and stochastic stem cell system as a population. These features may lead to establishment of a more universal principle on stem cells that is shared by other systems.

Employment of single-diode model to elucidate the variations in photovoltaic parameters under different electrical and thermal conditions

PubMed Central

Hameed, Shilan S.; Aziz, Fakhra; Sulaiman, Khaulah; Ahmad, Zubair

2017-01-01

In this research work, numerical simulations are performed to correlate the photovoltaic parameters with various internal and external factors influencing the performance of solar cells. Single-diode modeling approach is utilized for this purpose and theoretical investigations are compared with the reported experimental evidences for organic and inorganic solar cells at various electrical and thermal conditions. Electrical parameters include parasitic resistances (Rs and Rp) and ideality factor (n), while thermal parameters can be defined by the cells temperature (T). A comprehensive analysis concerning broad spectral variations in the short circuit current (Isc), open circuit voltage (Voc), fill factor (FF) and efficiency (η) is presented and discussed. It was generally concluded that there exists a good agreement between the simulated results and experimental findings. Nevertheless, the controversial consequence of temperature impact on the performance of organic solar cells necessitates the development of a complementary model which is capable of well simulating the temperature impact on these devices performance. PMID:28793325

A critical examination of the numerology of antigen-binding cells: evidence for multiple receptor specificities on single cells.

PubMed

Miller, A

1977-01-01

The data available from other laboratories as well as our own on the frequency of cells recognizing major histocompatibility antigens or conventional protein and hapten antigens is critically evaluated. The frequency of specific binding for a large number of antigens is sufficiently high to support the idea that at least part of the antigen-binding cell population must have multiple specificities. Our results suggest that these multiple specific cells result from single cells synthesizing and displaying as many as 50-100 species of receptor, each at a frequency of 10(4) per cell. A model involving gene expansion of constant-region genes is suggested and some auxilliary evidence consistent with such C-gene expansion is presented.

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

PubMed Central

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

2014-01-01

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

Single-cell transcriptome of early embryos and cultured embryonic stem cells of cynomolgus monkeys

PubMed Central

Nakamura, Tomonori; Yabuta, Yukihiro; Okamoto, Ikuhiro; Sasaki, Kotaro; Iwatani, Chizuru; Tsuchiya, Hideaki; Saitou, Mitinori

2017-01-01

In mammals, the development of pluripotency and specification of primordial germ cells (PGCs) have been studied predominantly using mice as a model organism. However, divergences among mammalian species for such processes have begun to be recognized. Between humans and mice, pre-implantation development appears relatively similar, but the manner and morphology of post-implantation development are significantly different. Nevertheless, the embryogenesis just after implantation in primates, including the specification of PGCs, has been unexplored due to the difficulties in analyzing the embryos at relevant developmental stages. Here, we present a comprehensive single-cell transcriptome dataset of pre- and early post-implantation embryo cells, PGCs and embryonic stem cells (ESCs) of cynomolgus monkeys as a model of higher primates. The identities of each transcriptome were also validated rigorously by other way such as immunofluorescent analysis. The information reported here will serve as a foundation for our understanding of a wide range of processes in the developmental biology of primates, including humans. PMID:28649393

Effect of heat shock and recovery temperature on variability of single cell lag time of Cronobacter turicensis.

PubMed

Xu, Y Zh; Métris, A; Stasinopoulos, D M; Forsythe, S J; Sutherland, J P

2015-02-01

The effect of heat stress and subsequent recovery temperature on the individual cellular lag of Cronobacter turicensis was analysed using optical density measurements. Low numbers of cells were obtained through serial dilution and the time to reach an optical density of 0.035 was determined. Assuming the lag of a single cell follows a shifted Gamma distribution with a fixed shape parameter, the effect of recovery temperature on the individual lag of untreated and sublethally heat treated cells of Cr. turicensis were modelled. It was found that the shift parameter (Tshift) increased asymptotically as the temperature decreased while the logarithm of the scale parameter (θ) decreased linearly with recovery temperature. To test the validity of the model in food, growth of low numbers of untreated and heat treated Cr. turicensis in artificially contaminated infant first milk was measured experimentally and compared with predictions obtained by Monte Carlo simulations. Although the model for untreated cells slightly underestimated the actual growth in first milk at low temperatures, the model for heat treated cells was in agreement with the data derived from the challenge tests and provides a basis for reliable quantitative microbiological risk assessments for Cronobacter spp. in infant milk. Copyright © 2014 Elsevier Ltd. All rights reserved.

Model-based cell number quantification using online single-oxygen sensor data for tissue engineering perfusion bioreactors.

PubMed

Lambrechts, T; Papantoniou, I; Sonnaert, M; Schrooten, J; Aerts, J-M

2014-10-01

Online and non-invasive quantification of critical tissue engineering (TE) construct quality attributes in TE bioreactors is indispensable for the cost-effective up-scaling and automation of cellular construct manufacturing. However, appropriate monitoring techniques for cellular constructs in bioreactors are still lacking. This study presents a generic and robust approach to determine cell number and metabolic activity of cell-based TE constructs in perfusion bioreactors based on single oxygen sensor data in dynamic perfusion conditions. A data-based mechanistic modeling technique was used that is able to correlate the number of cells within the scaffold (R(2)  = 0.80) and the metabolic activity of the cells (R(2)  = 0.82) to the dynamics of the oxygen response to step changes in the perfusion rate. This generic non-destructive measurement technique is effective for a large range of cells, from as low as 1.0 × 10(5) cells to potentially multiple millions of cells, and can open-up new possibilities for effective bioprocess monitoring. © 2014 Wiley Periodicals, Inc.

Design and optimization of reverse-transcription quantitative PCR experiments.

PubMed

Tichopad, Ales; Kitchen, Rob; Riedmaier, Irmgard; Becker, Christiane; Ståhlberg, Anders; Kubista, Mikael

2009-10-01

Quantitative PCR (qPCR) is a valuable technique for accurately and reliably profiling and quantifying gene expression. Typically, samples obtained from the organism of study have to be processed via several preparative steps before qPCR. We estimated the errors of sample withdrawal and extraction, reverse transcription (RT), and qPCR that are introduced into measurements of mRNA concentrations. We performed hierarchically arranged experiments with 3 animals, 3 samples, 3 RT reactions, and 3 qPCRs and quantified the expression of several genes in solid tissue, blood, cell culture, and single cells. A nested ANOVA design was used to model the experiments, and relative and absolute errors were calculated with this model for each processing level in the hierarchical design. We found that intersubject differences became easily confounded by sample heterogeneity for single cells and solid tissue. In cell cultures and blood, the noise from the RT and qPCR steps contributed substantially to the overall error because the sampling noise was less pronounced. We recommend the use of sample replicates preferentially to any other replicates when working with solid tissue, cell cultures, and single cells, and we recommend the use of RT replicates when working with blood. We show how an optimal sampling plan can be calculated for a limited budget. .

A Babcock-Leighton solar dynamo model with multi-cellular meridional circulation in advection- and diffusion-dominated regimes

NASA Astrophysics Data System (ADS)

Belucz, B.; Dikpati, M.; Forgacs-Dajka, E.

2014-12-01

Babcock-Leighton type solar dynamo models with single cell meridional circulation are successful in reproducing many solarcycle features, and recently such a model was applied for solarcycle 24 amplitude prediction. It seems that cycle 24 amplitudeforecast may not be validated. One of the reasons is the assumption of a single cell meridional circulation. Recent observations andtheoretical models of meridional circulation do not indicate a single-celledflow pattern. So it is nessecary to examine the role of complexmulti-cellular circulation patterns in a Babcock-Leighton solar dynamo model in the advection and diffusion dominated regimes.By simulating a Babcock-Leighton solar dynamo model with multi-cellularflow, we show that the presence of a weak, second, high-latitudereverse cell speeds up the cycle and slighty enhances the poleward branch in the butterfly diagram, whereas the presence of a second cellin depth reverses the tilt of the butterfly wing and leads to ananti-solar type feature. If, instead, the butterfly diagram isconstructed from the middle of the convection zone in that case, a solar-like pattern can be retrieved. All the above cases behavequalitatively similar in advection and diffusion-dominated regimes.However, our dynamo with a meridional circulation containing fourcells in latitude behaves distinctly different in the two regimes, producing a solar-like butterfly diagram with fast cycles indiffusion-dominated regime, and a complex branches in the butterflydiagram in the advection-dominated regime. Another interestingfinding from our studies is that a four-celled flow pattern containing two in radius and two in latitude always producesquadrupolar parity as the relaxed solution.

A modular network for legged locomotion

NASA Astrophysics Data System (ADS)

Golubitsky, Martin; Stewart, Ian; Buono, Pietro-Luciano; Collins, J. J.

1998-04-01

In this paper we use symmetry methods to study networks of coupled cells, which are models for central pattern generators (CPGs). In these models the cells obey identical systems of differential equations and the network specifies how cells are coupled. Previously, Collins and Stewart showed that the phase relations of many of the standard gaits of quadrupeds and hexapods can be obtained naturally via Hopf bifurcation in small networks. For example, the networks they used to study quadrupeds all had four cells, with the understanding that each cell determined the phase of the motion of one leg. However, in their work it seemed necessary to employ several different four-oscillator networks to obtain all of the standard quadrupedal gaits. We show that this difficulty with four-oscillator networks is unavoidable, but that the problems can be overcome by using a larger network. Specifically, we show that the standard gaits of a quadruped, including walk, trot and pace, cannot all be realized by a single four-cell network without introducing unwanted conjugacies between trot and pace - conjugacies that imply a dynamic equivalence between these gaits that seems inconsistent with observations. In this sense a single network with four cells cannot model the CPG of a quadruped. We also introduce a single eight-cell network that can model all of the primary gaits of quadrupeds without these unwanted conjugacies. Moreover, this network is modular in that it naturally generalizes to provide models of gaits in hexapods, centipedes, and millipedes. The analysis of models for many-legged animals shows that wave-like motions, similar to those obtained by Kopell and Ermentrout, can be expected. However, our network leads to a prediction that the wavelength of the wave motion will divide twice the length of the animal. Indeed, we reproduce illustrations of wave-like motions in centipedes where the animal is approximately one-and-a-half wavelength long - motions that are consistent with this prediction. We discuss the implications of these results for the development of modular control networks for adaptive legged robots.

Role of Cell-to-Cell Variability in Activating a Positive Feedback Antiviral Response in Human Dendritic Cells

PubMed Central

Hu, Jianzhong; Nudelman, German; Shimoni, Yishai; Kumar, Madhu; Ding, Yaomei; López, Carolina; Hayot, Fernand; Wetmur, James G.; Sealfon, Stuart C.

2011-01-01

In the first few hours following Newcastle disease viral infection of human monocyte-derived dendritic cells, the induction of IFNB1 is extremely low and the secreted type I interferon response is below the limits of ELISA assay. However, many interferon-induced genes are activated at this time, for example DDX58 (RIGI), which in response to viral RNA induces IFNB1. We investigated whether the early induction of IFNBI in only a small percentage of infected cells leads to low level IFN secretion that then induces IFN-responsive genes in all cells. We developed an agent-based mathematical model to explore the IFNBI and DDX58 temporal dynamics. Simulations showed that a small number of early responder cells provide a mechanism for efficient and controlled activation of the DDX58-IFNBI positive feedback loop. The model predicted distributions of single cell responses that were confirmed by single cell mRNA measurements. The results suggest that large cell-to-cell variation plays an important role in the early innate immune response, and that the variability is essential for the efficient activation of the IFNB1 based feedback loop. PMID:21347441

Stem cell-derived models to improve mechanistic understanding and prediction of human drug-induced liver injury.

PubMed

Goldring, Christopher; Antoine, Daniel J; Bonner, Frank; Crozier, Jonathan; Denning, Chris; Fontana, Robert J; Hanley, Neil A; Hay, David C; Ingelman-Sundberg, Magnus; Juhila, Satu; Kitteringham, Neil; Silva-Lima, Beatriz; Norris, Alan; Pridgeon, Chris; Ross, James A; Young, Rowena Sison; Tagle, Danilo; Tornesi, Belen; van de Water, Bob; Weaver, Richard J; Zhang, Fang; Park, B Kevin

2017-02-01

Current preclinical drug testing does not predict some forms of adverse drug reactions in humans. Efforts at improving predictability of drug-induced tissue injury in humans include using stem cell technology to generate human cells for screening for adverse effects of drugs in humans. The advent of induced pluripotent stem cells means that it may ultimately be possible to develop personalized toxicology to determine interindividual susceptibility to adverse drug reactions. However, the complexity of idiosyncratic drug-induced liver injury means that no current single-cell model, whether of primary liver tissue origin, from liver cell lines, or derived from stem cells, adequately emulates what is believed to occur during human drug-induced liver injury. Nevertheless, a single-cell model of a human hepatocyte which emulates key features of a hepatocyte is likely to be valuable in assessing potential chemical risk; furthermore, understanding how to generate a relevant hepatocyte will also be critical to efforts to build complex multicellular models of the liver. Currently, hepatocyte-like cells differentiated from stem cells still fall short of recapitulating the full mature hepatocellular phenotype. Therefore, we convened a number of experts from the areas of preclinical and clinical hepatotoxicity and safety assessment, from industry, academia, and regulatory bodies, to specifically explore the application of stem cells in hepatotoxicity safety assessment and to make recommendations for the way forward. In this short review, we particularly discuss the importance of benchmarking stem cell-derived hepatocyte-like cells to their terminally differentiated human counterparts using defined phenotyping, to make sure the cells are relevant and comparable between labs, and outline why this process is essential before the cells are introduced into chemical safety assessment. (Hepatology 2017;65:710-721). © 2016 by the American Association for the Study of Liver Diseases.

Impact of dose size in single fraction spatially fractionated (grid) radiotherapy for melanoma

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

Zhang, Hualin, E-mail: hualin.zhang@northwestern.edu, E-mail: hualinzhang@yahoo.com; Zhong, Hualiang; Barth, Rolf F.

2014-02-15

Purpose: To evaluate the impact of dose size in single fraction, spatially fractionated (grid) radiotherapy for selectively killing infiltrated melanoma cancer cells of different tumor sizes, using different radiobiological models. Methods: A Monte Carlo technique was employed to calculate the 3D dose distribution of a commercially available megavoltage grid collimator in a 6 MV beam. The linear-quadratic (LQ) and modified linear quadratic (MLQ) models were used separately to evaluate the therapeutic outcome of a series of single fraction regimens that employed grid therapy to treat both acute and late responding melanomas of varying sizes. The dose prescription point was atmore » the center of the tumor volume. Dose sizes ranging from 1 to 30 Gy at 100% dose line were modeled. Tumors were either touching the skin surface or having their centers at a depth of 3 cm. The equivalent uniform dose (EUD) to the melanoma cells and the therapeutic ratio (TR) were defined by comparing grid therapy with the traditional open debulking field. The clinical outcomes from recent reports were used to verify the authors’ model. Results: Dose profiles at different depths and 3D dose distributions in a series of 3D melanomas treated with grid therapy were obtained. The EUDs and TRs for all sizes of 3D tumors involved at different doses were derived through the LQ and MLQ models, and a practical equation was derived. The EUD was only one fifth of the prescribed dose. The TR was dependent on the prescribed dose and on the LQ parameters of both the interspersed cancer and normal tissue cells. The results from the LQ model were consistent with those of the MLQ model. At 20 Gy, the EUD and TR by the LQ model were 2.8% higher and 1% lower than by the MLQ, while at 10 Gy, the EUD and TR as defined by the LQ model were only 1.4% higher and 0.8% lower, respectively. The dose volume histograms of grid therapy for a 10 cm tumor showed different dosimetric characteristics from those of conventional radiotherapy. A significant portion of the tumor volume received a very large dose in grid therapy, which ensures significant tumor cell killing in these regions. Conversely, some areas received a relatively small dose, thereby sparing interspersed normal cells and increasing radiation tolerance. The radiobiology modeling results indicated that grid therapy could be useful for treating acutely responding melanomas infiltrating radiosensitive normal tissues. The theoretical model predictions were supported by the clinical outcomes. Conclusions: Grid therapy functions by selectively killing infiltrating tumor cells and concomitantly sparing interspersed normal cells. The TR depends on the radiosensitivity of the cell population, dose, tumor size, and location. Because the volumes of very high dose regions are small, the LQ model can be used safely to predict the clinical outcomes of grid therapy. When treating melanomas with a dose of 15 Gy or higher, single fraction grid therapy is clearly advantageous for sparing interspersed normal cells. The existence of a threshold fraction dose, which was found in the authors’ theoretical simulations, was confirmed by clinical observations.« less

Biofilm growth program and architecture revealed by single-cell live imaging

NASA Astrophysics Data System (ADS)

Yan, Jing; Sabass, Benedikt; Stone, Howard; Wingreen, Ned; Bassler, Bonnie

Biofilms are surface-associated bacterial communities. Little is known about biofilm structure at the level of individual cells. We image living, growing Vibrio cholerae biofilms from founder cells to ten thousand cells at single-cell resolution, and discover the forces underpinning the architectural evolution of the biofilm. Mutagenesis, matrix labeling, and simulations demonstrate that surface-adhesion-mediated compression causes V. cholerae biofilms to transition from a two-dimensional branched morphology to a dense, ordered three-dimensional cluster. We discover that directional proliferation of rod-shaped bacteria plays a dominant role in shaping the biofilm architecture, and this growth pattern is controlled by a single gene. Competition analyses reveal the advantages of the dense growth mode in providing the biofilm with superior mechanical properties. We will further present continuum theory to model the three-dimensional growth of biofilms at the solid-liquid interface as well as solid-air interface.

Do bacterial cell numbers follow a theoretical Poisson distribution? Comparison of experimentally obtained numbers of single cells with random number generation via computer simulation.

PubMed

Koyama, Kento; Hokunan, Hidekazu; Hasegawa, Mayumi; Kawamura, Shuso; Koseki, Shigenobu

2016-12-01

We investigated a bacterial sample preparation procedure for single-cell studies. In the present study, we examined whether single bacterial cells obtained via 10-fold dilution followed a theoretical Poisson distribution. Four serotypes of Salmonella enterica, three serotypes of enterohaemorrhagic Escherichia coli and one serotype of Listeria monocytogenes were used as sample bacteria. An inoculum of each serotype was prepared via a 10-fold dilution series to obtain bacterial cell counts with mean values of one or two. To determine whether the experimentally obtained bacterial cell counts follow a theoretical Poisson distribution, a likelihood ratio test between the experimentally obtained cell counts and Poisson distribution which parameter estimated by maximum likelihood estimation (MLE) was conducted. The bacterial cell counts of each serotype sufficiently followed a Poisson distribution. Furthermore, to examine the validity of the parameters of Poisson distribution from experimentally obtained bacterial cell counts, we compared these with the parameters of a Poisson distribution that were estimated using random number generation via computer simulation. The Poisson distribution parameters experimentally obtained from bacterial cell counts were within the range of the parameters estimated using a computer simulation. These results demonstrate that the bacterial cell counts of each serotype obtained via 10-fold dilution followed a Poisson distribution. The fact that the frequency of bacterial cell counts follows a Poisson distribution at low number would be applied to some single-cell studies with a few bacterial cells. In particular, the procedure presented in this study enables us to develop an inactivation model at the single-cell level that can estimate the variability of survival bacterial numbers during the bacterial death process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Experimentally guided models reveal replication principles that shape the mutation distribution of RNA viruses

PubMed Central

Schulte, Michael B; Draghi, Jeremy A; Plotkin, Joshua B; Andino, Raul

2015-01-01

Life history theory posits that the sequence and timing of events in an organism's lifespan are fine-tuned by evolution to maximize the production of viable offspring. In a virus, a life history strategy is largely manifested in its replication mode. Here, we develop a stochastic mathematical model to infer the replication mode shaping the structure and mutation distribution of a poliovirus population in an intact single infected cell. We measure production of RNA and poliovirus particles through the infection cycle, and use these data to infer the parameters of our model. We find that on average the viral progeny produced from each cell are approximately five generations removed from the infecting virus. Multiple generations within a single cell infection provide opportunities for significant accumulation of mutations per viral genome and for intracellular selection. DOI: http://dx.doi.org/10.7554/eLife.03753.001 PMID:25635405

Learning and disrupting invariance in visual recognition with a temporal association rule

PubMed Central

Isik, Leyla; Leibo, Joel Z.; Poggio, Tomaso

2012-01-01

Learning by temporal association rules such as Foldiak's trace rule is an attractive hypothesis that explains the development of invariance in visual recognition. Consistent with these rules, several recent experiments have shown that invariance can be broken at both the psychophysical and single cell levels. We show (1) that temporal association learning provides appropriate invariance in models of object recognition inspired by the visual cortex, (2) that we can replicate the “invariance disruption” experiments using these models with a temporal association learning rule to develop and maintain invariance, and (3) that despite dramatic single cell effects, a population of cells is very robust to these disruptions. We argue that these models account for the stability of perceptual invariance despite the underlying plasticity of the system, the variability of the visual world and expected noise in the biological mechanisms. PMID:22754523

A linear programming approach to reconstructing subcellular structures from confocal images for automated generation of representative 3D cellular models.

PubMed

Wood, Scott T; Dean, Brian C; Dean, Delphine

2013-04-01

This paper presents a novel computer vision algorithm to analyze 3D stacks of confocal images of fluorescently stained single cells. The goal of the algorithm is to create representative in silico model structures that can be imported into finite element analysis software for mechanical characterization. Segmentation of cell and nucleus boundaries is accomplished via standard thresholding methods. Using novel linear programming methods, a representative actin stress fiber network is generated by computing a linear superposition of fibers having minimum discrepancy compared with an experimental 3D confocal image. Qualitative validation is performed through analysis of seven 3D confocal image stacks of adherent vascular smooth muscle cells (VSMCs) grown in 2D culture. The presented method is able to automatically generate 3D geometries of the cell's boundary, nucleus, and representative F-actin network based on standard cell microscopy data. These geometries can be used for direct importation and implementation in structural finite element models for analysis of the mechanics of a single cell to potentially speed discoveries in the fields of regenerative medicine, mechanobiology, and drug discovery. Copyright © 2012 Elsevier B.V. All rights reserved.

Multimodal autofluorescence detection of cancer: from single cells to living organism

NASA Astrophysics Data System (ADS)

Horilova, J.; Cunderlikova, B.; Cagalinec, M.; Chorvat, D.; Marcek Chorvatova, A.

2018-02-01

Multimodal optical imaging of suspected tissues is showing to be a promising method for distinguishing suspected cancerous tissues from healthy ones. In particular, the combination of steady-state spectroscopic methods with timeresolved fluorescence provides more precise insight into native metabolism when focused on tissue autofluorescence. Cancer is linked to specific metabolic remodelation detectable spectroscopically. In this work, we evaluate possibilities and limitations of multimodal optical cancer detection in single cells, collagen-based 3D cell cultures and in living organisms (whole mice), as a representation of gradually increasing complexity of model systems.

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

PubMed

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

2013-02-01

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

In vivo diagnosis of skin cancer using polarized and multiple scattered light spectroscopy

NASA Astrophysics Data System (ADS)

Bartlett, Matthew Allen

This thesis research presents the development of a non-invasive diagnostic technique for distinguishing between skin cancer, moles, and normal skin using polarized and multiple scattered light spectroscopy. Polarized light incident on the skin is single scattered by the epidermal layer and multiple scattered by the dermal layer. The epidermal light maintains its initial polarization while the light from the dermal layer becomes randomized and multiple scattered. Mie theory was used to model the epidermal light as the scattering from the intercellular organelles. The dermal signal was modeled as the diffusion of light through a localized semi-homogeneous volume. These models were confirmed using skin phantom experiments, studied with in vitro cell cultures, and applied to human skin for in vivo testing. A CCD-based spectroscopy system was developed to perform all these experiments. The probe and the theory were tested on skin phantoms of latex spheres on top of a solid phantom. We next extended our phantom study to include in vitro cells on top of the solid phantom. Optical fluorescent microscope images revealed at least four distinct scatterers including mitochondria, nucleoli, nuclei, and cell membranes. Single scattering measurements on the mammalian cells consistently produced PSD's in the size range of the mitochondria. The clinical portion of the study consisted of in vivo measurements on cancer, mole, and normal skin spots. The clinical study combined the single scattering model from the phantom and in vitro cell studies with the diffusion model for multiple scattered light. When parameters from both layers were combined, we found that a sensitivity of 100% and 77% can be obtained for detecting cancers and moles, respectively, given the number of lesions examined.

Transition of spiral calcium waves between multiple stable patterns can be triggered by a single calcium spark in a fire-diffuse-fire model

PubMed Central

Tang, Ai-Hui; Wang, Shi-Qiang

2009-01-01

Spiral patterns have been found in various nonequilibrium systems. The Ca2+-induced Ca2+ release system in single cardiac cells is unique for highly discrete reaction elements, each giving rise to a Ca2+ spark upon excitation. We imaged the spiral Ca2+ waves in isolated cardiac cells and numerically studied the effect of system excitability on spiral patterns using a two-dimensional fire-diffuse-fire model. We found that under certain conditions, the system was able to display multiple stable patterns of spiral waves, each exhibiting different periods and distinct routines of spiral tips. Transition between these different patterns could be triggered by an internal fluctuation in the form of a single Ca2+ spark. PMID:19792039

Transition of spiral calcium waves between multiple stable patterns can be triggered by a single calcium spark in a fire-diffuse-fire model.

PubMed

Tang, Ai-Hui; Wang, Shi-Qiang

2009-09-01

Spiral patterns have been found in various nonequilibrium systems. The Ca(2+)-induced Ca(2+) release system in single cardiac cells is unique for highly discrete reaction elements, each giving rise to a Ca(2+) spark upon excitation. We imaged the spiral Ca(2+) waves in isolated cardiac cells and numerically studied the effect of system excitability on spiral patterns using a two-dimensional fire-diffuse-fire model. We found that under certain conditions, the system was able to display multiple stable patterns of spiral waves, each exhibiting different periods and distinct routines of spiral tips. Transition between these different patterns could be triggered by an internal fluctuation in the form of a single Ca(2+) spark.

Light scattering microscopy measurements of single nuclei compared with GPU-accelerated FDTD simulations

NASA Astrophysics Data System (ADS)

Stark, Julian; Rothe, Thomas; Kieß, Steffen; Simon, Sven; Kienle, Alwin

2016-04-01

Single cell nuclei were investigated using two-dimensional angularly and spectrally resolved scattering microscopy. We show that even for a qualitative comparison of experimental and theoretical data, the standard Mie model of a homogeneous sphere proves to be insufficient. Hence, an accelerated finite-difference time-domain method using a graphics processor unit and domain decomposition was implemented to analyze the experimental scattering patterns. The measured cell nuclei were modeled as single spheres with randomly distributed spherical inclusions of different size and refractive index representing the nucleoli and clumps of chromatin. Taking into account the nuclear heterogeneity of a large number of inclusions yields a qualitative agreement between experimental and theoretical spectra and illustrates the impact of the nuclear micro- and nanostructure on the scattering patterns.

Light scattering microscopy measurements of single nuclei compared with GPU-accelerated FDTD simulations.

PubMed

Stark, Julian; Rothe, Thomas; Kieß, Steffen; Simon, Sven; Kienle, Alwin

2016-04-07

Single cell nuclei were investigated using two-dimensional angularly and spectrally resolved scattering microscopy. We show that even for a qualitative comparison of experimental and theoretical data, the standard Mie model of a homogeneous sphere proves to be insufficient. Hence, an accelerated finite-difference time-domain method using a graphics processor unit and domain decomposition was implemented to analyze the experimental scattering patterns. The measured cell nuclei were modeled as single spheres with randomly distributed spherical inclusions of different size and refractive index representing the nucleoli and clumps of chromatin. Taking into account the nuclear heterogeneity of a large number of inclusions yields a qualitative agreement between experimental and theoretical spectra and illustrates the impact of the nuclear micro- and nanostructure on the scattering patterns.

Modeling dynamics for oncogenesis encompassing mutations and genetic instability.

PubMed

Fassoni, Artur C; Yang, Hyun M

2018-06-27

Tumorigenesis has been described as a multistep process, where each step is associated with a genetic alteration, in the direction to progressively transform a normal cell and its descendants into a malignant tumour. Into this work, we propose a mathematical model for cancer onset and development, considering three populations: normal, premalignant and cancer cells. The model takes into account three hallmarks of cancer: self-sufficiency on growth signals, insensibility to anti-growth signals and evading apoptosis. By using a nonlinear expression to describe the mutation from premalignant to cancer cells, the model includes genetic instability as an enabling characteristic of tumour progression. Mathematical analysis was performed in detail. Results indicate that apoptosis and tissue repair system are the first barriers against tumour progression. One of these mechanisms must be corrupted for cancer to develop from a single mutant cell. The results also show that the presence of aggressive cancer cells opens way to survival of less adapted premalignant cells. Numerical simulations were performed with parameter values based on experimental data of breast cancer, and the necessary time taken for cancer to reach a detectable size from a single mutant cell was estimated with respect to some parameters. We find that the rates of apoptosis and mutations have a large influence on the pace of tumour progression and on the time it takes to become clinically detectable.

Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor.

PubMed

Loomba, Varun; Huber, Gregor; von Lieres, Eric

2018-01-01

Flat-panel photo-bioreactors (PBRs) are customarily applied for investigating growth of microalgae. Optimal design and operation of such reactors is still a challenge due to complex non-linear combinations of various impact factors, particularly hydrodynamics, light irradiation, and cell metabolism. A detailed analysis of single-cell light reception can lead to novel insights into the complex interactions of light exposure and algae movement in the reactor. The combined impacts of hydrodynamics and light irradiation on algae cultivation in a flat-panel PBR were studied by tracing the light exposure of individual cells over time. Hydrodynamics and turbulent mixing in this air-sparged bioreactor were simulated using the Eulerian approach for the liquid phase and a slip model for the gas phase velocity profiles. The liquid velocity was then used for tracing single cells and their light exposure, using light intensity profiles obtained from solving the radiative transfer equation at different wavelengths. The residence times of algae cells in defined dark and light zones of the PBR were statistically analyzed for different algal concentrations and sparging rates. The results indicate poor mixing caused by the reactor design which can be only partially improved by increased sparging rates. The results provide important information for optimizing algal biomass productivity by improving bioreactor design and operation and can further be utilized for an in-depth analysis of algal growth by using advanced models of cell metabolism.

Action Potential Waveform Variability Limits Multi-Unit Separation in Freely Behaving Rats

PubMed Central

Stratton, Peter; Cheung, Allen; Wiles, Janet; Kiyatkin, Eugene; Sah, Pankaj; Windels, François

2012-01-01

Extracellular multi-unit recording is a widely used technique to study spontaneous and evoked neuronal activity in awake behaving animals. These recordings are done using either single-wire or mulitwire electrodes such as tetrodes. In this study we have tested the ability of single-wire electrodes to discriminate activity from multiple neurons under conditions of varying noise and neuronal cell density. Using extracellular single-unit recording, coupled with iontophoresis to drive cell activity across a wide dynamic range, we studied spike waveform variability, and explored systematic differences in single-unit spike waveform within and between brain regions as well as the influence of signal-to-noise ratio (SNR) on the similarity of spike waveforms. We also modelled spike misclassification for a range of cell densities based on neuronal recordings obtained at different SNRs. Modelling predictions were confirmed by classifying spike waveforms from multiple cells with various SNRs using a leading commercial spike-sorting system. Our results show that for single-wire recordings, multiple units can only be reliably distinguished under conditions of high recording SNR (≥4) and low neuronal density (≈20,000/ mm3). Physiological and behavioural changes, as well as technical limitations typical of awake animal preparations, reduce the accuracy of single-channel spike classification, resulting in serious classification errors. For SNR <4, the probability of misclassifying spikes approaches 100% in many cases. Our results suggest that in studies where the SNR is low or neuronal density is high, separation of distinct units needs to be evaluated with great caution. PMID:22719894

Implementation of a Smeared Crack Band Model in a Micromechanics Framework

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Waas, Anthony M.; Arnold, Steven M.

2012-01-01

The smeared crack band theory is implemented within the generalized method of cells and high-fidelity generalized method of cells micromechanics models to capture progressive failure within the constituents of a composite material while retaining objectivity with respect to the size of the discretization elements used in the model. An repeating unit cell containing 13 randomly arranged fibers is modeled and subjected to a combination of transverse tension/compression and transverse shear loading. The implementation is verified against experimental data (where available), and an equivalent finite element model utilizing the same implementation of the crack band theory. To evaluate the performance of the crack band theory within a repeating unit cell that is more amenable to a multiscale implementation, a single fiber is modeled with generalized method of cells and high-fidelity generalized method of cells using a relatively coarse subcell mesh which is subjected to the same loading scenarios as the multiple fiber repeating unit cell. The generalized method of cells and high-fidelity generalized method of cells models are validated against a very refined finite element model.

Robust model-based analysis of single-particle tracking experiments with Spot-On

PubMed Central

Grimm, Jonathan B; Lavis, Luke D

2018-01-01

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce ‘Spot-On’, an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. PMID:29300163

Robust model-based analysis of single-particle tracking experiments with Spot-On.

PubMed

Hansen, Anders S; Woringer, Maxime; Grimm, Jonathan B; Lavis, Luke D; Tjian, Robert; Darzacq, Xavier

2018-01-04

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. © 2018, Hansen et al.

Mapping nonlinear receptive field structure in primate retina at single cone resolution

PubMed Central

Li, Peter H; Greschner, Martin; Gunning, Deborah E; Mathieson, Keith; Sher, Alexander; Litke, Alan M; Paninski, Liam

2015-01-01

The function of a neural circuit is shaped by the computations performed by its interneurons, which in many cases are not easily accessible to experimental investigation. Here, we elucidate the transformation of visual signals flowing from the input to the output of the primate retina, using a combination of large-scale multi-electrode recordings from an identified ganglion cell type, visual stimulation targeted at individual cone photoreceptors, and a hierarchical computational model. The results reveal nonlinear subunits in the circuity of OFF midget ganglion cells, which subserve high-resolution vision. The model explains light responses to a variety of stimuli more accurately than a linear model, including stimuli targeted to cones within and across subunits. The recovered model components are consistent with known anatomical organization of midget bipolar interneurons. These results reveal the spatial structure of linear and nonlinear encoding, at the resolution of single cells and at the scale of complete circuits. DOI: http://dx.doi.org/10.7554/eLife.05241.001 PMID:26517879

A minimal model for kinetochore-microtubule dynamics

NASA Astrophysics Data System (ADS)

Liu, Andrea

2014-03-01

During mitosis, chromosome pairs align at the center of a bipolar microtubule (MT) spindle and oscillate as MTs attaching them to the cell poles polymerize and depolymerize. The cell fixes misaligned pairs by a tension-sensing mechanism. Pairs later separate as shrinking MTs pull each chromosome toward its respective cell pole. We present a minimal model for these processes based on properties of MT kinetics. We apply the measured tension-dependence of single MT kinetics to a stochastic many MT model, which we solve numerically and with master equations. We find that the force-velocity curve for the single chromosome system is bistable and hysteretic. Above some threshold load, tension fluctuations induce MTs to spontaneously switch from a pulling state into a growing, pushing state. To recover pulling from the pushing state, the load must be reduced far below the threshold. This leads to oscillations in the two-chromosome system. Our minimal model quantitatively captures several aspects of kinetochore dynamics observed experimentally. This work was supported by NSF-DMR-1104637.

Identification of gene regulation models from single-cell data

NASA Astrophysics Data System (ADS)

Weber, Lisa; Raymond, William; Munsky, Brian

2018-09-01

In quantitative analyses of biological processes, one may use many different scales of models (e.g. spatial or non-spatial, deterministic or stochastic, time-varying or at steady-state) or many different approaches to match models to experimental data (e.g. model fitting or parameter uncertainty/sloppiness quantification with different experiment designs). These different analyses can lead to surprisingly different results, even when applied to the same data and the same model. We use a simplified gene regulation model to illustrate many of these concerns, especially for ODE analyses of deterministic processes, chemical master equation and finite state projection analyses of heterogeneous processes, and stochastic simulations. For each analysis, we employ MATLAB and PYTHON software to consider a time-dependent input signal (e.g. a kinase nuclear translocation) and several model hypotheses, along with simulated single-cell data. We illustrate different approaches (e.g. deterministic and stochastic) to identify the mechanisms and parameters of the same model from the same simulated data. For each approach, we explore how uncertainty in parameter space varies with respect to the chosen analysis approach or specific experiment design. We conclude with a discussion of how our simulated results relate to the integration of experimental and computational investigations to explore signal-activated gene expression models in yeast (Neuert et al 2013 Science 339 584–7) and human cells (Senecal et al 2014 Cell Rep. 8 75–83)5.

Progressive Failure of a Unidirectional Fiber-Reinforced Composite Using the Method of Cells: Discretization Objective Computational Results

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Waas, Anthony M.; Arnold, Steven M.

2012-01-01

The smeared crack band theory is implemented within the generalized method of cells and high-fidelity generalized method of cells micromechanics models to capture progressive failure within the constituents of a composite material while retaining objectivity with respect to the size of the discretization elements used in the model. An repeating unit cell containing 13 randomly arranged fibers is modeled and subjected to a combination of transverse tension/compression and transverse shear loading. The implementation is verified against experimental data (where available), and an equivalent finite element model utilizing the same implementation of the crack band theory. To evaluate the performance of the crack band theory within a repeating unit cell that is more amenable to a multiscale implementation, a single fiber is modeled with generalized method of cells and high-fidelity generalized method of cells using a relatively coarse subcell mesh which is subjected to the same loading scenarios as the multiple fiber repeating unit cell. The generalized method of cells and high-fidelity generalized method of cells models are validated against a very refined finite element model.

Characterization of protein marker expression, tumorigenicity, and doxorubicin chemoresistance in two new canine mammary tumor cell lines.

PubMed

Hsiao, Yen-Ling; Hsieh, Tai-Zu; Liou, Chian-Jiun; Cheng, Yeong-Hsiang; Lin, Chung-Tien; Chang, Chi-Yao; Lai, Yu-Shen

2014-09-30

Canine mammary tumors (CMTs) are the most common type of cancer found in female dogs. Establishment and evaluation of tumor cell lines can facilitate investigations of the biological mechanisms of cancer. Different cell models are used to investigate genetic, epigenetic, and cellular pathways, cancer progression, and cancer therapeutics. Establishment of new cell models will greatly facilitate research in this field. In the present study, we established and characterized two new CMT cell lines derived from a single CMT. We established two cell lines from a single malignant CMT specimen: DTK-E and DTK-SME. Morphologically, the DTK-E cells were large, flat, and epithelial-like, whereas DTK-SME cells were round and epithelial-like. Doubling times were 24 h for DTK-E and 18 h for DTK-SME. On western blots, both cell lines expressed cytokeratin AE1, vimentin, cytokeratin 7 (CK7), and heat shock protein 27 (HSP27). Moreover, investigation of chemoresistance revealed that DTK-SME was more resistant to doxorubicin-induced apoptosis than DTK-E was. After xenotransplantation, both DTK-E and DTK-SME tumors appeared within 14 days, but the average size of DTK-SME tumors was greater than that of DTK-E tumors after 56 days. We established two new cell lines from a single CMT, which exhibit significant diversity in cell morphology, protein marker expression, tumorigenicity, and chemoresistance. The results of this study revealed that the DTK-SME cell line was more resistant to doxorubicin-induced apoptosis and exhibited higher tumorigenicity in vivo than the DTK-E cell line. We anticipate that the two novel CMT cell lines established in this study will be useful for investigating the tumorigenesis of mammary carcinomas and for screening anticancer drugs.

Label-free Quantification of Proteins in Single Embryonic Cells with Neural Fate in the Cleavage-Stage Frog (Xenopus laevis) Embryo using Capillary Electrophoresis Electrospray Ionization High-Resolution Mass Spectrometry (CE-ESI-HRMS).

PubMed

Lombard-Banek, Camille; Reddy, Sushma; Moody, Sally A; Nemes, Peter

2016-08-01

Quantification of protein expression in single cells promises to advance a systems-level understanding of normal development. Using a bottom-up proteomic workflow and multiplexing quantification by tandem mass tags, we recently demonstrated relative quantification between single embryonic cells (blastomeres) in the frog (Xenopus laevis) embryo. In this study, we minimize derivatization steps to enhance analytical sensitivity and use label-free quantification (LFQ) for single Xenopus cells. The technology builds on a custom-designed capillary electrophoresis microflow-electrospray ionization high-resolution mass spectrometry platform and LFQ by MaxLFQ (MaxQuant). By judiciously tailoring performance to peptide separation, ionization, and data-dependent acquisition, we demonstrate an ∼75-amol (∼11 nm) lower limit of detection and quantification for proteins in complex cell digests. The platform enabled the identification of 438 nonredundant protein groups by measuring 16 ng of protein digest, or <0.2% of the total protein contained in a blastomere in the 16-cell embryo. LFQ intensity was validated as a quantitative proxy for protein abundance. Correlation analysis was performed to compare protein quantities between the embryo and n = 3 different single D11 blastomeres, which are fated to develop into the nervous system. A total of 335 nonredundant protein groups were quantified in union between the single D11 cells spanning a 4 log-order concentration range. LFQ and correlation analysis detected expected proteomic differences between the whole embryo and blastomeres, and also found translational differences between individual D11 cells. LFQ on single cells raises exciting possibilities to study gene expression in other cells and models to help better understand cell processes on a systems biology level. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Cell identification using Raman spectroscopy in combination with optical trapping and microfluidics

NASA Astrophysics Data System (ADS)

Krafft, Christoph; Dochow, Sebastian; Beleites, Claudia; Popp, Jürgen

2014-03-01

Cell identification by Raman spectroscopy has evolved to be an attractive complement to established optical techniques. Raman activated cell sorting (RACS) offers prospects to complement the widely applied fluorescence activated cell sorting. RACS can be realized by combination with optical traps and microfluidic devices. The progress of RACS is reported for a cellular model system that can be found in peripheral blood of tumor patients. Lymphocytes and erythrocytes were extracted from blood samples. Breast carcinoma derived tumor cells (MCF-7, BT-20) and acute myeloid leukemia cells (OCI-AML3) were grown in cell cultures. First, Raman images were collected from dried cells on calcium fluoride slides. Support vector machines (SVM) classified 99.7% of the spectra to the correct cell type. Second, a 785 nm laser was used for optical trapping of single cells in aqueous buffer and for excitation of the Raman spectrum. SVM distinguished 1210 spectra of tumor and normal cells with a sensitivity of >99.7% and a specificity of >99.5%. Third, a microfluidic glass chip was designed to inject single cells, modify the flow speed, accommodate fibers of an optical trap and sort single cells after Raman based identification with 514 nm for excitation. Forth, the microfluidic chip was fabricated by quartz which improved cell identification results with 785 nm excitation. Here, partial least squares discriminant analysis gave classification rates of 98%. Finally, a Raman-on-chip approach was developed that integrates fibers for trapping, Raman excitation and signal detection in a single compact unit.

Millisecond single-molecule localization microscopy combined with convolution analysis and automated image segmentation to determine protein concentrations in complexly structured, functional cells, one cell at a time.

PubMed

Wollman, Adam J M; Leake, Mark C

2015-01-01

We present a single-molecule tool called the CoPro (concentration of proteins) method that uses millisecond imaging with convolution analysis, automated image segmentation and super-resolution localization microscopy to generate robust estimates for protein concentration in different compartments of single living cells, validated using realistic simulations of complex multiple compartment cell types. We demonstrate its utility experimentally on model Escherichia coli bacteria and Saccharomyces cerevisiae budding yeast cells, and use it to address the biological question of how signals are transduced in cells. Cells in all domains of life dynamically sense their environment through signal transduction mechanisms, many involving gene regulation. The glucose sensing mechanism of S. cerevisiae is a model system for studying gene regulatory signal transduction. It uses the multi-copy expression inhibitor of the GAL gene family, Mig1, to repress unwanted genes in the presence of elevated extracellular glucose concentrations. We fluorescently labelled Mig1 molecules with green fluorescent protein (GFP) via chromosomal integration at physiological expression levels in living S. cerevisiae cells, in addition to the RNA polymerase protein Nrd1 with the fluorescent protein reporter mCherry. Using CoPro we make quantitative estimates of Mig1 and Nrd1 protein concentrations in the cytoplasm and nucleus compartments on a cell-by-cell basis under physiological conditions. These estimates indicate a ∼4-fold shift towards higher values in the concentration of diffusive Mig1 in the nucleus if the external glucose concentration is raised, whereas equivalent levels in the cytoplasm shift to smaller values with a relative change an order of magnitude smaller. This compares with Nrd1 which is not involved directly in glucose sensing, and which is almost exclusively localized in the nucleus under high and low external glucose levels. CoPro facilitates time-resolved quantification of protein concentrations in single functional cells, and enables the distributions of concentrations across a cell population to be measured. This could be useful in investigating several cellular processes that are mediated by proteins, especially where changes in protein concentration in a single cell in response to changes in the extracellular chemical environment are subtle and rapid and may be smaller than the variability across a cell population.

Systems Modeling in Developmental Toxicity

EPA Science Inventory

An individual starts off as a single cell, the progeny of which form complex structures that are themselves integrated into progressively larger systems. Developmental biology is concerned with how this cellular complexity and patterning arises through orchestration of cell divi...

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

PubMed

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

2016-12-01

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

Single-cell tracking of flavivirus RNA uncovers species-specific interactions with the immune system dictating disease outcome

PubMed Central

Douam, Florian; Hrebikova, Gabriela; Albrecht, Yentli E. Soto; Sellau, Julie; Sharon, Yael; Ding, Qiang; Ploss, Alexander

2017-01-01

Positive-sense RNA viruses pose increasing health and economic concerns worldwide. Our limited understanding of how these viruses interact with their host and how these processes lead to virulence and disease seriously hampers the development of anti-viral strategies. Here, we demonstrate the tracking of (+) and (−) sense viral RNA at single-cell resolution within complex subsets of the human and murine immune system in different mouse models. Our results provide insights into how a prototypic flavivirus, yellow fever virus (YFV-17D), differentially interacts with murine and human hematopoietic cells in these mouse models and how these dynamics influence distinct outcomes of infection. We detect (−) YFV-17D RNA in specific secondary lymphoid compartments and cell subsets not previously recognized as permissive for YFV replication, and we highlight potential virus–host interaction events that could be pivotal in regulating flavivirus virulence and attenuation. PMID:28290449

Distribution and evolution of cotton fiber development genes in the fibreless Gossypium raimondii genome

USDA-ARS?s Scientific Manuscript database

Cotton fibers represent the largest single cell in the plant kingdom, and they have been used as a model to study cell function, differentiation, maturation, and cell death. The cotton fiber transcriptome can be clustered into two genomic regions: conserved and recombination hotspots. Genetic link...

Genomic landscape of fiber genes in fibered and non-fibered cottons

USDA-ARS?s Scientific Manuscript database

Cotton fiber is the largest single cell in the plant kingdom. It is the best model to study cell function, differentiation, maturation, and cell death. Cotton fiber transcriptome can be clustered into two types of regions: conservative areas and recombination hotspots. This study was to investig...

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

PubMed Central

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

2002-01-01

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

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

PubMed

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

2017-01-01

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

Modeling the locomotion of the African trypanosome using multi-particle collision dynamics

NASA Astrophysics Data System (ADS)

Babu, Sujin B.; Stark, Holger

2012-08-01

The African trypanosome is a single flagellated micro-organism that causes the deadly sleeping sickness in humans and animals. We study the locomotion of a model trypanosome by modeling the spindle-shaped cell body using an elastic network of vertices with additional bending rigidity. The flagellum firmly attached to the model cell body is either straight or helical. A bending wave propagates along the flagellum and pushes the trypanosome forward in its viscous environment, which we simulate with the method of multi-particle collision dynamics. The relaxation dynamics of the model cell body due to a static bending wave reveals the sperm number from elastohydrodynamics as the relevant parameter. Characteristic cell body conformations for the helically attached flagellum resemble experimental observations. We show that the swimming velocity scales as the root of the angular frequency of the bending wave reminiscent of predictions for an actuated slender rod attached to a large viscous load. The swimming velocity for one geometry collapses on a single master curve when plotted versus the sperm number. The helically attached flagellum leads to a helical swimming path and a rotation of the model trypanosome about its long axis as observed in experiments. The simulated swimming velocity agrees with the experimental value.

Multidimensional Single-Cell Analysis of BCR Signaling Reveals Proximal Activation Defect As a Hallmark of Chronic Lymphocytic Leukemia B Cells

PubMed Central

Palomba, M. Lia; Piersanti, Kelly; Ziegler, Carly G. K.; Decker, Hugo; Cotari, Jesse W.; Bantilan, Kurt; Rijo, Ivelise; Gardner, Jeff R.; Heaney, Mark; Bemis, Debra; Balderas, Robert; Malek, Sami N.; Seymour, Erlene; Zelenetz, Andrew D.

2014-01-01

Purpose Chronic Lymphocytic Leukemia (CLL) is defined by a perturbed B-cell receptor-mediated signaling machinery. We aimed to model differential signaling behavior between B cells from CLL and healthy individuals to pinpoint modes of dysregulation. Experimental Design We developed an experimental methodology combining immunophenotyping, multiplexed phosphospecific flow cytometry, and multifactorial statistical modeling. Utilizing patterns of signaling network covariance, we modeled BCR signaling in 67 CLL patients using Partial Least Squares Regression (PLSR). Results from multidimensional modeling were validated using an independent test cohort of 38 patients. Results We identified a dynamic and variable imbalance between proximal (pSYK, pBTK) and distal (pPLCγ2, pBLNK, ppERK) phosphoresponses. PLSR identified the relationship between upstream tyrosine kinase SYK and its target, PLCγ2, as maximally predictive and sufficient to distinguish CLL from healthy samples, pointing to this juncture in the signaling pathway as a hallmark of CLL B cells. Specific BCR pathway signaling signatures that correlate with the disease and its degree of aggressiveness were identified. Heterogeneity in the PLSR response variable within the B cell population is both a characteristic mark of healthy samples and predictive of disease aggressiveness. Conclusion Single-cell multidimensional analysis of BCR signaling permitted focused analysis of the variability and heterogeneity of signaling behavior from patient-to-patient, and from cell-to-cell. Disruption of the pSYK/pPLCγ2 relationship is uncovered as a robust hallmark of CLL B cell signaling behavior. Together, these observations implicate novel elements of the BCR signal transduction as potential therapeutic targets. PMID:24489640

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.

Suppressive effects of primed eosinophils on single epicutaneous sensitization through regulation of dermal dendritic cells.

PubMed

Lin, Jing-Yi; Ta, Yng-Cun; Liu, I-Lin; Chen, Hsi-Wen; Wang, Li-Fang

2016-07-01

Eosinophils are multifunctional innate immune cells involved in many aspects of innate and adaptive immunity. Epicutaneous sensitization with protein allergen is an important sensitization route for atopic dermatitis. In this study, using a murine single protein-patch model, we show that eosinophils of a primed status accumulate in draining lymph nodes following single epicutaneous sensitization. Further, depletion of eosinophils results in enhancement of the induced Th1/Th2 immune responses, whereas IL-5-induced hypereosinophilia suppresses these responses. Mechanistically, primed eosinophils cause a reduction in the numbers and activation status of dermal dendritic cells in draining lymph nodes. Collectively, these results demonstrate that primed eosinophils exert suppressive effects on single epicutaneous sensitization through regulation of dermal dendritic cells. Thus, these findings highlight the critical roles of eosinophils in the pathogenesis of atopic dermatitis with important clinical implications for the prevention of allergen sensitization. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Single-cell topological RNA-Seq analysis reveals insights into cellular differentiation and development

PubMed Central

Rizvi, Abbas H.; Camara, Pablo G.; Kandror, Elena K.; Roberts, Thomas J.; Schieren, Ira; Maniatis, Tom; Rabadan, Raul

2017-01-01

Transcriptional programs control cellular lineage commitment and differentiation during development. Understanding cell fate has been advanced by studying single-cell RNA-seq, but is limited by the assumptions of current analytic methods regarding the structure of data. We present single-cell topological data analysis (scTDA), an algorithm for topology-based computational analyses to study temporal, unbiased transcriptional regulation. Compared to other methods, scTDA is a non-linear, model-independent, unsupervised statistical framework that can characterize transient cellular states. We applied scTDA to the analysis of murine embryonic stem cell (mESC) differentiation in vitro in response to inducers of motor neuron differentiation. scTDA resolved asynchrony and continuity in cellular identity over time, and identified four transient states (pluripotent, precursor, progenitor, and fully differentiated cells) based on changes in stage-dependent combinations of transcription factors, RNA-binding proteins and long non-coding RNAs. scTDA can be applied to study asynchronous cellular responses to either developmental cues or environmental perturbations. PMID:28459448

Imparting magnetic dipole heterogeneity to internalized iron oxide nanoparticles for microorganism swarm control

NASA Astrophysics Data System (ADS)

Kim, Paul Seung Soo; Becker, Aaron; Ou, Yan; Julius, Anak Agung; Kim, Min Jun

2015-03-01

Tetrahymena pyriformis is a single cell eukaryote that can be modified to respond to magnetic fields, a response called magnetotaxis. Naturally, this microorganism cannot respond to magnetic fields, but after modification using iron oxide nanoparticles, cells are magnetized and exhibit a constant magnetic dipole strength. In experiments, a rotating field is applied to cells using a two-dimensional approximate Helmholtz coil system. Using rotating magnetic fields, we characterize discrete cells' swarm swimming which is affected by several factors. The behavior of the cells under these fields is explained in detail. After the field is removed, relatively straight swimming is observed. We also generate increased heterogeneity within a population of cells to improve controllability of a swarm, which is explored in a cell model. By exploiting this straight swimming behavior, we propose a method to control discrete cells utilizing a single global magnetic input. Successful implementation of this swarm control method would enable teams of microrobots to perform a variety of in vitro microscale tasks impossible for single microrobots, such as pushing objects or simultaneous micromanipulation of discrete entities.

Extracting cancer cell line electrochemical parameters at the single cell level using a microfabricated device.

PubMed

Alqabandi, Jassim A; Abdel-Motal, Ussama M; Youcef-Toumi, Kamal

2009-02-01

Cancer cells have distinctive electrochemical properties. This work sheds light on the system design aspects and key challenges that should be considered when experimentally analyzing and extracting the electrical characteristics of a tumor cell line. In this study, we developed a cellularbased functional microfabricated device using lithography technology. This device was used to investigate the electrochemical parameters of cultured cancer cells at the single-cell level. Using impedance spectroscopy analyses, we determined the average specific capacitance and resistance of the membrane of the cancer cell line B16-F10 to be 1.154 +/- 0.29 microF/cm(2), and 3.9 +/- 1.15 KOmega.cm(2) (mean +/- SEM, n =14 cells), respectively. The consistency of our findings via different trails manifests the legitimacy of our experimental procedure. Furthermore, the data were compared with a proposed constructed analytical-circuit model. The results of this work may greatly assist researchers in defining an optimal procedure while extracting electrical properties of cancer cells. Detecting electrical signals at the single cell level could lead to the development of novel approaches for analysis of malignant cells in human tissues and biopsies.

Coding of auditory temporal and pitch information by hippocampal individual cells and cell assemblies in the rat.

PubMed

Sakurai, Y

2002-01-01

This study reports how hippocampal individual cells and cell assemblies cooperate for neural coding of pitch and temporal information in memory processes for auditory stimuli. Each rat performed two tasks, one requiring discrimination of auditory pitch (high or low) and the other requiring discrimination of their duration (long or short). Some CA1 and CA3 complex-spike neurons showed task-related differential activity between the high and low tones in only the pitch-discrimination task. However, without exception, neurons which showed task-related differential activity between the long and short tones in the duration-discrimination task were always task-related neurons in the pitch-discrimination task. These results suggest that temporal information (long or short), in contrast to pitch information (high or low), cannot be coded independently by specific neurons. The results also indicate that the two different behavioral tasks cannot be fully differentiated by the task-related single neurons alone and suggest a model of cell-assembly coding of the tasks. Cross-correlation analysis among activities of simultaneously recorded multiple neurons supported the suggested cell-assembly model.Considering those results, this study concludes that dual coding by hippocampal single neurons and cell assemblies is working in memory processing of pitch and temporal information of auditory stimuli. The single neurons encode both auditory pitches and their temporal lengths and the cell assemblies encode types of tasks (contexts or situations) in which the pitch and the temporal information are processed.

Magnetic fields applied to collagen-coated ferric oxide beads induce stretch-activated Ca2+ flux in fibroblasts.

PubMed

Glogauer, M; Ferrier, J; McCulloch, C A

1995-11-01

The ability to apply controlled forces to the cell membrane may enable elucidation of the mechanisms and pathways involved in signal transduction in response to applied physical stimuli. We have developed a magnetic particle-electromagnet model that allows the application of controlled forces to the plasma membrane of substrate-attached fibroblasts. The system allows applied forces to be controlled by the magnitude of the magnetic field and by the surface area of cell membrane covered with collagen-coated ferric beads. Analysis by single-cell ratio fluorimetry of fura 2-loaded cells demonstrated large calcium transients (50-300 nM) in response to the magnetic force applications. Experiments using either the stretch-activated channel blocker gadolinium chloride or ethylene glycol-bis(beta-aminoethyl ether)-N,N,N',N'-tetraacetic acid to eliminate external calcium ions, or addition of extracellular manganese ions, indicated that there was a calcium influx through putative stretch-activated channels. The probability of a calcium influx in single cells was increased by higher surface bead loading and the degree of cell spreading. Depolymerization of actin filaments by cytochalasin D increased the amplitude of calcium response twofold. The regulation of calcium flux by filamentous actin content and by cell spreading indicates a possible modulatory role for the cytoskeleton in channel sensitivity. Magnetic force application to beads on single cells provides a controlled model to study mechanisms and heterogeneity in physical force stimulation of cation-permeable channels.

Single Cell Analysis Linking Ribosomal (r)DNA and rRNA Copy Numbers to Cell Size and Growth Rate Provides Insights into Molecular Protistan Ecology.

PubMed

Fu, Rao; Gong, Jun

2017-11-01

Ribosomal (r)RNA and rDNA have been golden molecular markers in microbial ecology. However, it remains poorly understood how ribotype copy number (CN)-based characteristics are linked with diversity, abundance, and activity of protist populations and communities observed at organismal levels. Here, we applied a single-cell approach to quantify ribotype CNs in two ciliate species reared at different temperatures. We found that in actively growing cells, the per-cell rDNA and rRNA CNs scaled with cell volume (CV) to 0.44 and 0.58 powers, respectively. The modeled rDNA and rRNA concentrations thus appear to be much higher in smaller than in larger cells. The observed rRNA:rDNA ratio scaled with CV 0.14 . The maximum growth rate could be well predicted by a combination of per-cell ribotype CN and temperature. Our empirical data and modeling on single-cell ribotype scaling are in agreement with both the metabolic theory of ecology and the growth rate hypothesis, providing a quantitative framework for linking cellular rDNA and rRNA CNs with body size, growth (activity), and biomass stoichiometry. This study also demonstrates that the expression rate of rRNA genes is constrained by cell size, and favors biomass rather than abundance-based interpretation of quantitative ribotype data in population and community ecology of protists. © 2017 The Authors. Journal of Eukaryotic Microbiology published by Wiley Periodicals, Inc. on behalf of International Society of Protistologists.

Flocking Transition in Confluent Tissues

NASA Astrophysics Data System (ADS)

Paoluzzi, Matteo; Giavazzi, Fabio; Macchi, Marta; Scita, Giorgio; Cerbino, Roberto; Manning, Lisa; Marchetti, Cristina

The emerging of collective migration in biological tissues plays a pivotal role in embryonic morphogenesis, wound healing and cancer invasion. While many aspects of single cell movements are well established, the mechanisms leading to coherent displacements of cohesive cell groups are still poorly understood. Some of us recently proposed a Self-Propelled Voronoi (SPV) model of dense tissues that combines self-propelled particle models and vertex models of confluent cell layers and exhibits a liquid-solid transition as a function of cell shape and cell motility. We now examine the role of cell polarization on collective cell dynamics by introducing an orientation mechanism that aligns cell polarization with local cell motility. The model predicts a density-independent flocking transition tuned by the strength of the aligning interaction, with both solid and liquid flocking states existing in different regions of parameter space. MP and MCM were supported by the Simons Foundation Targeted Grant in the Mathematical Modeling of Living Systems Number: 342354 and by the Syracuse Soft Matter Program.

SU-E-T-667: Radiosensitization Due to Gold Nanoparticles: A Monte Carlo Cellular Dosimetry Investigation of An Expansive Parameter Space

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

Martinov, M; Thomson, R

2015-06-15

Purpose: To investigate dose enhancement to cellular compartments following gold nanoparticle (GNP) uptake in tissue, varying cell and tissue morphology, intra and extracellular GNP distribution, and source energy using Monte Carlo (MC) simulations. Methods: Models of single and multiple cells are developed for normal and cancerous tissues; cells (outer radii 5–10 µm) are modeled as concentric spheres comprising the nucleus (radii 2.5–7.5 µm) and cytoplasm. GNP distributions modeled include homogeneous distributions throughout the cytoplasm, variable numbers of GNP-containing endosomes within the cytoplasm, or distributed in a spherical shell about the nucleus. Gold concentrations range from 1 to 30 mg/g. Dosemore » to nucleus and to cytoplasm for simulations including GNPs are compared to simulations without GNPs to compute Nuclear and Cytoplasm Dose Enhancement Factors (NDEF, CDEF). Photon source energies are between 20 keV and 1.25 MeV. Results: DEFs are highly sensitive to GNP intracellular distribution; for a 2.5 µm radius nucleus irradiated by a 30 keV source, NDEF varies from 1.2 for a single endosome containing all GNPs to 8.2 for GNPs distributed about the nucleus (7 mg/g). DEFs vary with cell dimensions and source energy: NDEFs vary from 2.5 (90 keV) to 8.2 (30 keV) for a 2.5 µm radius nucleus and from 1.1 (90 keV) to 1.3 (30 keV) for a 7.5 µm radius nucleus, both with GNPs in a spherical shell about the nucleus (7 mg/g). NDEF and CDEF are generally different within a single cell. For multicell models, the presence of gold within intervening tissues between source and target perturbs the fluence reaching cellular targets, resulting in DEF inhomogeneities within a population of irradiated cells. Conclusion: DEFs vary by an order of magnitude for different cell models, GNP distributions, and source energies, demonstrating the importance of detailed modelling for advancing GNP development for radiotherapy. Funding provided by the Natural Sciences and Engineering Council of Canada (NSERC), and the Canada Research Chairs Program (CRC)« less

Modeling the formation of cell-matrix adhesions on a single 3D matrix fiber.

PubMed

Escribano, J; Sánchez, M T; García-Aznar, J M

2015-11-07

Cell-matrix adhesions are crucial in different biological processes like tissue morphogenesis, cell motility, and extracellular matrix remodeling. These interactions that link cell cytoskeleton and matrix fibers are built through protein clutches, generally known as adhesion complexes. The adhesion formation process has been deeply studied in two-dimensional (2D) cases; however, the knowledge is limited for three-dimensional (3D) cases. In this work, we simulate different local extracellular matrix properties in order to unravel the fundamental mechanisms that regulate the formation of cell-matrix adhesions in 3D. We aim to study the mechanical interaction of these biological structures through a three dimensional discrete approach, reproducing the transmission pattern force between the cytoskeleton and a single extracellular matrix fiber. This numerical model provides a discrete analysis of the proteins involved including spatial distribution, interaction between them, and study of the different phenomena, such as protein clutches unbinding or protein unfolding. Copyright © 2015 Elsevier Ltd. All rights reserved.

Measurement of In Vitro Single Cell Temperature by Novel Thermocouple Nanoprobe in Acute Lung Injury Models.

PubMed

Wang, Xing; Chen, Qiuhua; Tian, Wenjuan; Wang, Jianqing; Cheng, Lu; Lu, Jun; Chen, Mingqi; Pei, Yinhao; Li, Can; Chen, Gong; Gu, Ning

2017-01-01

Energy metabolism may alter pattern differences in acute lung injury (ALI) as one of the causes but the detailed features at single-cellular level remain unclear. Changes in intercellular temperature and adenosine triphosphate (ATP) concentration within the single cell may help to understand the role of energy metabolism in causing ALI. ALI in vitro models were established by treating mice lung epithelial (MLE-12) cells with lipopolysaccharide (LPS), hydrogen peroxide (H2O2), hydrochloric acid (HCl) and cobalt chloride (CoCl2, respectively. 100 nm micro thermocouple probe (TMP) was inserted into the cytosol by micromanipulation system and thermoelectric readings were recorded to calculate the intracellular temperature based on standard curve. The total ATP contents for the MLE-12 cells were evaluated at different time intervals after treatments. A significant increase of intracellular temperature was observed after 10 or 20 μg/L LPS and HCl treatments. The HCl increased the temperature in a dose-dependent manner. On the contrary, H2O2 induced a significant decline of intracellular temperature after treatment. No significant difference in intracellular temperature was observed after CoCl2 exposure. The intracellular ATP levels decreased in a time-dependent manner after treatment with H2O2 and HCl, while the LPS and CoCl2 had no significant effect on ATP levels. The intracellular temperature responses varied in different ALI models. The concentration of ATP in the MLE-12 cells played part in the intracellular temperature changes. No direct correlation was observed between the intracellular temperature and concentration of ATP in the MLE-12 cells.

Proteolytic and non-proteolytic regulation of collective cell invasion: tuning by ECM density and organization

PubMed Central

Kumar, Sandeep; Kapoor, Aastha; Desai, Sejal; Inamdar, Mandar M.; Sen, Shamik

2016-01-01

Cancer cells manoeuvre through extracellular matrices (ECMs) using different invasion modes, including single cell and collective cell invasion. These modes rely on MMP-driven ECM proteolysis to make space for cells to move. How cancer-associated alterations in ECM influence the mode of invasion remains unclear. Further, the sensitivity of the two invasion modes to MMP dynamics remains unexplored. In this paper, we address these open questions using a multiscale hybrid computational model combining ECM density-dependent MMP secretion, MMP diffusion, ECM degradation by MMP and active cell motility. Our results demonstrate that in randomly aligned matrices, collective cell invasion is more efficient than single cell invasion. Although increase in MMP secretion rate enhances invasiveness independent of cell–cell adhesion, sustenance of collective invasion in dense matrices requires high MMP secretion rates. However, matrix alignment can sustain both single cell and collective cell invasion even without ECM proteolysis. Similar to our in-silico observations, increase in ECM density and MMP inhibition reduced migration of MCF-7 cells embedded in sandwich gels. Together, our results indicate that apart from cell intrinsic factors (i.e., high cell–cell adhesion and MMP secretion rates), ECM density and organization represent two important extrinsic parameters that govern collective cell invasion and invasion plasticity. PMID:26832069

Coarse-Grained Models for Protein-Cell Membrane Interactions

PubMed Central

Bradley, Ryan; Radhakrishnan, Ravi

2015-01-01

The physiological properties of biological soft matter are the product of collective interactions, which span many time and length scales. Recent computational modeling efforts have helped illuminate experiments that characterize the ways in which proteins modulate membrane physics. Linking these models across time and length scales in a multiscale model explains how atomistic information propagates to larger scales. This paper reviews continuum modeling and coarse-grained molecular dynamics methods, which connect atomistic simulations and single-molecule experiments with the observed microscopic or mesoscale properties of soft-matter systems essential to our understanding of cells, particularly those involved in sculpting and remodeling cell membranes. PMID:26613047

Mechanism of vaso-occlusion in sickle cell anemia

NASA Astrophysics Data System (ADS)

Lei, Huan; Karniadakis, George

2012-11-01

Vaso-occlusion crisis is one of the key hallmark of sickle cell anemia. While early studies suggested that the crisis is caused by blockage of a single elongated cell, recent experimental investigations indicate that vaso-occlusion is a complex process triggered by adhesive interactions among different cell groups in multiple stages. Based on dissipative particle dynamics, a multi-scale model for the sickle red blood cells (SS-RBCs), accounting for diversity in both shapes and cell rigidities, is developed to investigate the mechanism of vaso-occlusion crisis. Using this model, the adhesive dynamics of single SS-RBC was investigated in arterioles. Simulation results indicate that the different cell groups (deformable SS2 RBCs, rigid SS4 RBCs, leukocytes, etc.) exhibit heterogeneous adhesive behavior due to the different cell morphologies and membrane rigidities. We further simulate the tube flow of SS-RBC suspensions with different cell fractions. The more adhesive SS2 cells interact with the vascular endothelium and further trap rigid SS4 cells, resulting in vaso-occlusion in vessels less than 15 μm . Under inflammation, adherent leukocytes may also trap SS4 cells, resulting in vaso-occlusion in even larger vessels. This work was supported by the NSF grant CBET-0852948 and the NIH grant R01HL094270.

Combined BTK and PI3Kδ Inhibition with Acalabrutinib and ACP-319 Improves Survival and Tumor Control in CLL Mouse Model.

PubMed

Niemann, Carsten U; Mora-Jensen, Helena I; Dadashian, Eman L; Krantz, Fanny; Covey, Todd; Chen, Shih-Shih; Chiorazzi, Nicholas; Izumi, Raquel; Ulrich, Roger; Lannutti, Brian J; Wiestner, Adrian; Herman, Sarah E M

2017-10-01

Purpose: Targeting the B-cell receptor (BCR) pathway with inhibitors of Bruton tyrosine kinase (BTK) and PI3Kδ is highly effective for the treatment of chronic lymphocytic leukemia (CLL). However, deep remissions are uncommon, and drug resistance with single-agent therapy can occur. In vitro studies support the effectiveness of combing PI3Kδ and BTK inhibitors. Experimental Design: As CLL proliferation and survival depends on the microenvironment, we used murine models to assess the efficacy of the BTK inhibitor acalabrutinib combined with the PI3Kδ inhibitor ACP-319 in vivo We compared single-agent with combination therapy in TCL1-192 cell-injected mice, a model of aggressive CLL. Results: We found significantly larger reductions in tumor burden in the peripheral blood and spleen of combination-treated mice. Although single-agent therapy improved survival compared with control mice by a few days, combination therapy extended survival by over 2 weeks compared with either single agent. The combination reduced tumor proliferation, NF-κB signaling, and expression of BCL-xL and MCL-1 more potently than single-agent therapy. Conclusions: The combination of acalabrutinib and ACP-319 was superior to single-agent treatment in a murine CLL model, warranting further investigation of this combination in clinical studies. Clin Cancer Res; 23(19); 5814-23. ©2017 AACR . ©2017 American Association for Cancer Research.

Stimulus-dependent Maximum Entropy Models of Neural Population Codes

PubMed Central

Segev, Ronen; Schneidman, Elad

2013-01-01

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

A new model of strabismic amblyopia: Loss of spatial acuity due to increased temporal dispersion of geniculate X-cell afferents on to cortical neurons.

PubMed

Crewther, D P; Crewther, S G

2015-09-01

Although the neural locus of strabismic amblyopia has been shown to lie at the first site of binocular integration, first in cat and then in primate, an adequate mechanism is still lacking. Here we hypothesise that increased temporal dispersion of LGN X-cell afferents driven by the deviating eye onto single cortical neurons may provide a neural mechanism for strabismic amblyopia. This idea was investigated via single cell extracellular recordings of 93 X and 50 Y type LGN neurons from strabismic and normal cats. Both X and Y neurons driven by the non-deviating eye showed shorter latencies than those driven by either the strabismic or normal eyes. Also the mean latency difference between X and Y neurons was much greater for the strabismic cells compared with the other two groups. The incidence of lagged X-cells driven by the deviating eye of the strabismic cats was higher than that of LGN X-cells from normal animals. Remarkably, none of the cells recorded from the laminae driven by the non-deviating eye were of the lagged class. A simple computational model was constructed in which a mixture of lagged and non-lagged afferents converge on to single cortical neurons. Model cut-off spatial frequencies to a moving grating stimulus were sensitive to the temporal dispersion of the geniculate afferents. Thus strabismic amblyopia could be viewed as a lack of developmental tuning of geniculate lags for neurons driven by the amblyopic eye. Monocular control of fixation by the non-deviating eye is associated with reduced incidence of lagged neurons, suggesting that in normal vision, lagged neurons might play a role in maintaining binocular connections for cortical neurons. Copyright © 2014 Elsevier Ltd. All rights reserved.

Pinched-flow hydrodynamic stretching of single-cells.

PubMed

Dudani, Jaideep S; Gossett, Daniel R; Tse, Henry T K; Di Carlo, Dino

2013-09-21

Reorganization of cytoskeletal networks, condensation and decondensation of chromatin, and other whole cell structural changes often accompany changes in cell state and can reflect underlying disease processes. As such, the observable mechanical properties, or mechanophenotype, which is closely linked to intracellular architecture, can be a useful label-free biomarker of disease. In order to make use of this biomarker, a tool to measure cell mechanical properties should accurately characterize clinical specimens that consist of heterogeneous cell populations or contain small diseased subpopulations. Because of the heterogeneity and potential for rare populations in clinical samples, single-cell, high-throughput assays are ideally suited. Hydrodynamic stretching has recently emerged as a powerful method for carrying out mechanical phenotyping. Importantly, this method operates independently of molecular probes, reducing cost and sample preparation time, and yields information-rich signatures of cell populations through significant image analysis automation, promoting more widespread adoption. In this work, we present an alternative mode of hydrodynamic stretching where inertially-focused cells are squeezed in flow by perpendicular high-speed pinch flows that are extracted from the single inputted cell suspension. The pinched-flow stretching method reveals expected differences in cell deformability in two model systems. Furthermore, hydraulic circuit design is used to tune stretching forces and carry out multiple stretching modes (pinched-flow and extensional) in the same microfluidic channel with a single fluid input. The ability to create a self-sheathing flow from a single input solution should have general utility for other cytometry systems and the pinched-flow design enables an order of magnitude higher throughput (65,000 cells s(-1)) compared to our previously reported deformability cytometry method, which will be especially useful for identification of rare cell populations in clinical body fluids in the future.

The measurement of ultrasound scattering from individual micron-sized objects and its application in single cell scattering.

PubMed

Falou, Omar; Rui, Min; El Kaffas, Ahmed; Kumaradas, J Carl; Kolios, Michael C

2010-08-01

The measurement of the ultrasound backscatter from individual micron-sized objects such as cells is required for various applications such as tissue characterization. However, performing such a measurement remains a challenge. For example, the presence of air bubbles in a suspension of cells during the measurements may lead to the incorrect interpretation of the acoustic signals. This work introduces a technique for measuring the ultrasound backscatter from individual micron-sized objects by combining a microinjection system with a co-registered optical microscope and an ultrasound imaging device. This allowed the measurement of the ultrasound backscatter response from a single object under optical microscope guidance. The optical and ultrasonic data were used to determine the size of the object and to deduce its backscatter responses, respectively. In order to calibrate the system, the backscatter frequency responses from polystyrene microspheres were measured and compared to theoretical predictions. A very good agreement was found between the measured backscatter responses of individual microspheres and theoretical predictions of an elastic sphere. The backscatter responses from single OCI-AML-5 cells were also investigated. It was found that the backscatter responses from AML cells are best modeled using the fluid sphere model. The advantages, limitations, and future applications of the developed technique are discussed.

Single-cell RNA-seq of human induced pluripotent stem cells reveals cellular heterogeneity and cell state transitions between subpopulations.

PubMed

Nguyen, Quan; Lukowski, Samuel; Chiu, Han; Senabouth, Anne; Bruxner, Timothy; Christ, Angelika; Palpant, Nathan; Powell, Joseph

2018-05-11

Heterogeneity of cell states represented in pluripotent cultures have not been described at the transcriptional level. Since gene expression is highly heterogeneous between cells, single-cell RNA sequencing can be used to identify how individual pluripotent cells function. Here, we present results from the analysis of single-cell RNA sequencing data from 18,787 individual WTC CRISPRi human induced pluripotent stem cells. We developed an unsupervised clustering method, and through this identified four subpopulations distinguishable on the basis of their pluripotent state including: a core pluripotent population (48.3%), proliferative (47.8%), early-primed for differentiation (2.8%) and late-primed for differentiation (1.1%). For each subpopulation we were able to identify the genes and pathways that define differences in pluripotent cell states. Our method identified four discrete predictor gene sets comprised of 165 unique genes that denote the specific pluripotency states; and using these sets, we developed a multigenic machine learning prediction method to accurately classify single cells into each of the subpopulations. Compared against a set of established pluripotency markers, our method increases prediction accuracy by 10%, specificity by 20%, and explains a substantially larger proportion of deviance (up to 3-fold) from the prediction model. Finally, we developed an innovative method to predict cells transitioning between subpopulations, and support our conclusions with results from two orthogonal pseudotime trajectory methods. Published by Cold Spring Harbor Laboratory Press.

A study on parameter variation effects on battery packs for electric vehicles

NASA Astrophysics Data System (ADS)

Zhou, Long; Zheng, Yuejiu; Ouyang, Minggao; Lu, Languang

2017-10-01

As one single cell cannot meet power and driving range requirement in an electric vehicle, the battery packs with hundreds of single cells connected in parallel and series should be constructed. The most significant difference between a single cell and a battery pack is cell variation. Not only does cell variation affect pack energy density and power density, but also it causes early degradation of battery and potential safety issues. The cell variation effects on battery packs are studied, which are of great significant to battery pack screening and management scheme. In this study, the description for the consistency characteristics of battery packs was first proposed and a pack model with 96 cells connected in series was established. A set of parameters are introduced to study the cell variation and their impacts on battery packs are analyzed through the battery pack capacity loss simulation and experiments. Meanwhile, the capacity loss composition of the battery pack is obtained and verified by the temperature variation experiment. The results from this research can demonstrate that the temperature, self-discharge rate and coulombic efficiency are the major affecting parameters of cell variation and indicate the dissipative cell equalization is sufficient for the battery pack.

Assessment of Cell Line Models of Primary Human Cells by Raman Spectral Phenotyping

PubMed Central

Swain, Robin J.; Kemp, Sarah J.; Goldstraw, Peter; Tetley, Teresa D.; Stevens, Molly M.

2010-01-01

Abstract Researchers have previously questioned the suitability of cell lines as models for primary cells. In this study, we used Raman microspectroscopy to characterize live A549 cells from a unique molecular biochemical perspective to shed light on their suitability as a model for primary human pulmonary alveolar type II (ATII) cells. We also investigated a recently developed transduced type I (TT1) cell line as a model for alveolar type I (ATI) cells. Single-cell Raman spectra provide unique biomolecular fingerprints that can be used to characterize cellular phenotypes. A multivariate statistical analysis of Raman spectra indicated that the spectra of A549 and TT1 cells are characterized by significantly lower phospholipid content compared to ATII and ATI spectra because their cytoplasm contains fewer surfactant lamellar bodies. Furthermore, we found that A549 spectra are statistically more similar to ATI spectra than to ATII spectra. The spectral variation permitted phenotypic classification of cells based on Raman spectral signatures with >99% accuracy. These results suggest that A549 cells are not a good model for ATII cells, but TT1 cells do provide a reasonable model for ATI cells. The findings have far-reaching implications for the assessment of cell lines as suitable primary cellular models in live cultures. PMID:20409492

Impact of a compound droplet on a flat surface: A model for single cell epitaxy.

PubMed

Tasoglu, Savas; Kaynak, Gozde; Szeri, Andrew J; Demirci, Utkan; Muradoglu, Metin

2010-08-01

The impact and spreading of a compound viscous droplet on a flat surface are studied computationally using a front-tracking method as a model for the single cell epitaxy. This is a technology developed to create two-dimensional and three-dimensional tissue constructs cell by cell by printing cell-encapsulating droplets precisely on a substrate using an existing ink-jet printing method. The success of cell printing mainly depends on the cell viability during the printing process, which requires a deeper understanding of the impact dynamics of encapsulated cells onto a solid surface. The present study is a first step in developing a model for deposition of cell-encapsulating droplets. The inner droplet representing the cell, the encapsulating droplet, and the ambient fluid are all assumed to be Newtonian. Simulations are performed for a range of dimensionless parameters to probe the deformation and rate of deformation of the encapsulated cell, which are both hypothesized to be related to cell damage. The deformation of the inner droplet consistently increases: as the Reynolds number increases; as the diameter ratio of the encapsulating droplet to the cell decreases; as the ratio of surface tensions of the air-solution interface to the solution-cell interface increases; as the viscosity ratio of the cell to encapsulating droplet decreases; or as the equilibrium contact angle decreases. It is observed that maximum deformation for a range of Weber numbers has (at least) one local minimum at We=2. Thereafter, the effects of cell deformation on viability are estimated by employing a correlation based on the experimental data of compression of cells between parallel plates. These results provide insight into achieving optimal parameter ranges for maximal cell viability during cell printing.

Real-time Molecular Study of Bystander Effects of Low dose Low LET radiation Using Living Cell Imaging and Nanoparticale Optics

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

Natarajan, Mohan; Xu, Nancy R; Mohan, Sumathy

2013-06-03

In this study two novel approaches are proposed to investigate precisely the low dose low LET radiation damage and its effect on bystander cells in real time. First, a flow shear model system, which would provide us a near in vivo situation where endothelial cells in the presence of extra cellular matrix experiencing continuous flow shear stress, will be used. Endothelial cells on matri-gel (simulated extra cellular matrix) will be subjected to physiological flow shear (that occurs in normal blood vessels). Second, a unique tool (Single nano particle/single live cell/single molecule microscopy and spectroscopy; Figure A) will be used tomore » track the molecular trafficking by single live cell imaging. Single molecule chemical microscopy allows one to single out and study rare events that otherwise might be lost in assembled average measurement, and monitor many target single molecules simultaneously in real-time. Multi color single novel metal nanoparticle probes allow one to prepare multicolor probes (Figure B) to monitor many single components (events) simultaneously and perform multi-complex analysis in real-time. These nano-particles resist to photo bleaching and hence serve as probes for unlimited timeframe of analysis. Single live cell microscopy allows one to image many single cells simultaneously in real-time. With the combination of these unique tools, we will be able to study under near-physiological conditions the cellular and sub-cellular responses (even subtle changes at one molecule level) to low and very low doses of low LET radiation in real time (milli-second or nano-second) at sub-10 nanometer spatial resolution. This would allow us to precisely identify, at least in part, the molecular mediators that are responsible of radiation damage in the irradiated cells and the mediators that are responsible for initiating the signaling in the neighboring cells. Endothelial cells subjected to flow shear (2 dynes/cm2 or 16 dynes/cm2) and exposed to 0.1, 1 and 10 cGy on coverslips will be examined for (a) low LET radiation-induced alterations of cellular function and its physiological relevance in real time; and (b) radiation damage triggered bystander effect on the neighboring unirradiated cells. First, to determine the low LET radiation induced alteration of cellular function we will examine: (i) the real time transformation of single membrane transporters in single living cells; (ii) the pump efficiency of membrane efflux pump of live cells in real time at the molecular level; (iii) the kinetics of single-ligand receptor interaction on single live cell surface (Figure C); and (iv) alteration in chromosome replication in living cell. Second, to study the radiation triggered bystander responses, we will examine one of the key signaling pathway i.e. TNF- alpha/NF-kappa B mediated signaling. TNF-alpha specific nano particle sensors (green) will be developed to detect the releasing dynamics, transport mechanisms and ligand-receptor binding on live cell surface in real time. A second sensor (blue) will be developed to simultaneously monitor the track of NF-kB inside the cell. The proposed nano-particle optics approach would complement our DOE funded study on biochemical mechanisms of TNF-alpha- NF-kappa B-mediated bystander effect.« less

Order-of-magnitude estimates of latency (time to appearance) and refill time of a cancer from a single cancer 'stem' cell compared by an exponential and a logistic equation.

PubMed

Anderson, Ken M; Rubenstein, Marvin; Guinan, Patrick; Patel, Minu

2012-01-01

The time required before a mass of cancer cells considered to have originated from a single malignantly transformed cancer 'stem' cell reaches a certain number has not been studied. Applications might include determination of the time the cell mass reaches a size that can be detected by X-rays or physical examination or modeling growth rates in vitro in order to compare with other models or established data. We employed a simple logarithmic equation and a common logistic equation incorporating 'feedback' for unknown variables of cell birth, growth, division, and death that can be used to model cell proliferation. It can be used in association with free or commercial statistical software. Results with these two equations, varying the proliferation rate, nominally reduced by generational cell loss, are presented in two tables. The resulting equation, instructions, examples, and necessary mathematical software are available in the online appendix, where several parameters of interest can be modified by the reader www.uic.edu/nursing/publicationsupplements/tobillion_Anderson_Rubenstein_Guinan_Patel1.pdf. Reducing the proliferation rate by whatever alterations employed, markedly increases the time to reach 10(9) cells originating from an initial progenitor. In thinking about multistep oncogenesis, it is useful to consider the profound effect that variations in the effective proliferation rate may have during cancer development. This can be approached with the proposed equation, which is easy to use and available to further peer fine-tuning to be used in future modeling of cell growth.

A Monte Carlo study of macroscopic and microscopic dose descriptors for kilovoltage cellular dosimetry

NASA Astrophysics Data System (ADS)

Oliver, P. A. K.; Thomson, Rowan M.

2017-02-01

This work investigates how doses to cellular targets depend on cell morphology, as well as relations between cellular doses and doses to bulk tissues and water. Multicellular models of five healthy and cancerous soft tissues are developed based on typical values of cell compartment sizes, elemental compositions and number densities found in the literature. Cells are modelled as two concentric spheres with nucleus and cytoplasm compartments. Monte Carlo simulations are used to calculate the absorbed dose to the nucleus and cytoplasm for incident photon energies of 20-370 keV, relevant for brachytherapy, diagnostic radiology, and out-of-field radiation in higher-energy external beam radiotherapy. Simulations involving cell clusters, single cells and single nuclear cavities are carried out for cell radii between 5 and 10~μ m, and nuclear radii between 2 and 9~μ m. Seven nucleus and cytoplasm elemental compositions representative of animal cells are considered. The presence of a cytoplasm, extracellular matrix and surrounding cells can affect the nuclear dose by up to 13 % . Differences in cell and nucleus size can affect dose to the nucleus (cytoplasm) of the central cell in a cluster of 13 cells by up to 13 % (8 % ). Furthermore, the results of this study demonstrate that neither water nor bulk tissue are reliable substitutes for subcellular targets for incident photon energies  <50 keV: nuclear (cytoplasm) doses differ from dose-to-medium by up to 32 % (18 % ), and from dose-to-water by up to 21 % (8 % ). The largest differences between dose descriptors are seen for the lowest incident photon energies; differences are less than 3 % for energies ≥slant 90 keV. The sensitivity of results with regard to the parameters of the microscopic tissue structure model and cell model geometry, and the importance of the nucleus and cytoplasm as targets for radiation-induced cell death emphasize the importance of accurate models for cellular dosimetry studies.

The C. elegans Intestine As a Model for Intercellular Lumen Morphogenesis and In Vivo Polarized Membrane Biogenesis at the Single-cell Level: Labeling by Antibody Staining, RNAi Loss-of-function Analysis and Imaging.

PubMed

Zhang, Nan; Khan, Liakot A; Membreno, Edward; Jafari, Gholamali; Yan, Siyang; Zhang, Hongjie; Gobel, Verena

2017-10-03

Multicellular tubes, fundamental units of all internal organs, are composed of polarized epithelial or endothelial cells, with apical membranes lining the lumen and basolateral membranes contacting each other and/or the extracellular matrix. How this distinctive membrane asymmetry is established and maintained during organ morphogenesis is still an unresolved question of cell biology. This protocol describes the C. elegans intestine as a model for the analysis of polarized membrane biogenesis during tube morphogenesis, with emphasis on apical membrane and lumen biogenesis. The C. elegans twenty-cell single-layered intestinal epithelium is arranged into a simple bilaterally symmetrical tube, permitting analysis on a single-cell level. Membrane polarization occurs concomitantly with polarized cell division and migration during early embryogenesis, but de novo polarized membrane biogenesis continues throughout larval growth, when cells no longer proliferate and move. The latter setting allows one to separate subcellular changes that simultaneously mediate these different polarizing processes, difficult to distinguish in most polarity models. Apical-, basolateral membrane-, junctional-, cytoskeletal- and endomembrane components can be labeled and tracked throughout development by GFP fusion proteins, or assessed by in situ antibody staining. Together with the organism's genetic versatility, the C. elegans intestine thus provides a unique in vivo model for the visual, developmental, and molecular genetic analysis of polarized membrane and tube biogenesis. The specific methods (all standard) described here include how to: label intestinal subcellular components by antibody staining; analyze genes involved in polarized membrane biogenesis by loss-of-function studies adapted to the typically essential tubulogenesis genes; assess polarity defects during different developmental stages; interpret phenotypes by epifluorescence, differential interference contrast (DIC) and confocal microscopy; quantify visual defects. This protocol can be adapted to analyze any of the often highly conserved molecules involved in epithelial polarity, membrane biogenesis, tube and lumen morphogenesis.

A Study of Early Afterdepolarizations in a Model for Human Ventricular Tissue

PubMed Central

Vandersickel, Nele; Kazbanov, Ivan V.; Nuitermans, Anita; Weise, Louis D.; Pandit, Rahul; Panfilov, Alexander V.

2014-01-01

Sudden cardiac death is often caused by cardiac arrhythmias. Recently, special attention has been given to a certain arrhythmogenic condition, the long-QT syndrome, which occurs as a result of genetic mutations or drug toxicity. The underlying mechanisms of arrhythmias, caused by the long-QT syndrome, are not fully understood. However, arrhythmias are often connected to special excitations of cardiac cells, called early afterdepolarizations (EADs), which are depolarizations during the repolarizing phase of the action potential. So far, EADs have been studied mainly in isolated cardiac cells. However, the question on how EADs at the single-cell level can result in fibrillation at the tissue level, especially in human cell models, has not been widely studied yet. In this paper, we study wave patterns that result from single-cell EAD dynamics in a mathematical model for human ventricular cardiac tissue. We induce EADs by modeling experimental conditions which have been shown to evoke EADs at a single-cell level: by an increase of L-type Ca currents and a decrease of the delayed rectifier potassium currents. We show that, at the tissue level and depending on these parameters, three types of abnormal wave patterns emerge. We classify them into two types of spiral fibrillation and one type of oscillatory dynamics. Moreover, we find that the emergent wave patterns can be driven by calcium or sodium currents and we find phase waves in the oscillatory excitation regime. From our simulations we predict that arrhythmias caused by EADs can occur during normal wave propagation and do not require tissue heterogeneities. Experimental verification of our results is possible for experiments at the cell-culture level, where EADs can be induced by an increase of the L-type calcium conductance and by the application of I blockers, and the properties of the emergent patterns can be studied by optical mapping of the voltage and calcium. PMID:24427289

Collective gradient sensing and chemotaxis: modeling and recent developments

NASA Astrophysics Data System (ADS)

Camley, Brian A.

2018-06-01

Cells measure a vast variety of signals, from their environment’s stiffness to chemical concentrations and gradients; physical principles strongly limit how accurately they can do this. However, when many cells work together, they can cooperate to exceed the accuracy of any single cell. In this topical review, I will discuss the experimental evidence showing that cells collectively sense gradients of many signal types, and the models and physical principles involved. I also propose new routes by which experiments and theory can expand our understanding of these problems.

Documentation for the MODFLOW 6 Groundwater Flow Model

USGS Publications Warehouse

Langevin, Christian D.; Hughes, Joseph D.; Banta, Edward R.; Niswonger, Richard G.; Panday, Sorab; Provost, Alden M.

2017-08-10

This report documents the Groundwater Flow (GWF) Model for a new version of MODFLOW called MODFLOW 6. The GWF Model for MODFLOW 6 is based on a generalized control-volume finite-difference approach in which a cell can be hydraulically connected to any number of surrounding cells. Users can define the model grid using one of three discretization packages, including (1) a structured discretization package for defining regular MODFLOW grids consisting of layers, rows, and columns, (2) a discretization by ver­tices package for defining layered unstructured grids consisting of layers and cells, and (3) a general unstruc­tured discretization package for defining flexible grids comprised of cells and their connection properties. For layered grids, a new capability is available for removing thin cells and vertically connecting cells overlying and underlying the thin cells. For complex problems involving water-table conditions, an optional Newton-Raphson formulation, based on the formulations in MODFLOW-NWT and MODFLOW-USG, can be acti­vated. Use of the Newton-Raphson formulation will often improve model convergence and allow solutions to be obtained for difficult problems that cannot be solved using the traditional wetting and drying approach. The GWF Model is divided into “packages,” as was done in previous MODFLOW versions. A package is the part of the model that deals with a single aspect of simulation. Packages included with the GWF Model include those related to internal calculations of groundwater flow (discretization, initial conditions, hydraulic conduc­tance, and storage), stress packages (constant heads, wells, recharge, rivers, general head boundaries, drains, and evapotranspiration), and advanced stress packages (streamflow routing, lakes, multi-aquifer wells, and unsaturated zone flow). An additional package is also available for moving water available in one package into the individual features of the advanced stress packages. The GWF Model also has packages for obtaining and controlling output from the model. This report includes detailed explanations of physical and mathematical concepts on which the GWF Model and its packages are based.Like its predecessors, MODFLOW 6 is based on a highly modular structure; however, this structure has been extended into an object-oriented framework. The framework includes a robust and generalized numeri­cal solution object, which can be used to solve many different types of models. The numerical solution object has several different matrix preconditioning options as well as several methods for solving the linear system of equations. In this new framework, the GWF Model itself is an object as are each of the GWF Model packages. A benefit of the object-oriented structure is that multiple objects of the same type can be used in a single sim­ulation. Thus, a single forward run with MODFLOW 6 may contain multiple GWF Models. GWF Models can be hydraulically connected using GWF-GWF Exchange objects. Connecting GWF models in different ways permits the user to utilize a local grid refinement strategy consisting of parent and child models or to couple adjacent GWF Models. An advantage of the approach implemented in MODFLOW 6 is that multiple models and their exchanges can be incorporated into a single numerical solution object. With this design, models can be tightly coupled at the matrix level.

Quantitative assessment of protein activity in orphan tissues and single cells using the metaVIPER algorithm. | Office of Cancer Genomics

Cancer.gov

We and others have shown that transition and maintenance of biological states is controlled by master regulator proteins, which can be inferred by interrogating tissue-specific regulatory models (interactomes) with transcriptional signatures, using the VIPER algorithm. Yet, some tissues may lack molecular profiles necessary for interactome inference (orphan tissues), or, as for single cells isolated from heterogeneous samples, their tissue context may be undetermined.

Distinctive features of single nucleotide alterations in induced pluripotent stem cells with different types of DNA repair deficiency disorders

PubMed Central

Okamura, Kohji; Sakaguchi, Hironari; Sakamoto-Abutani, Rie; Nakanishi, Mahito; Nishimura, Ken; Yamazaki-Inoue, Mayu; Ohtaka, Manami; Periasamy, Vaiyapuri Subbarayan; Alshatwi, Ali Abdullah; Higuchi, Akon; Hanaoka, Kazunori; Nakabayashi, Kazuhiko; Takada, Shuji; Hata, Kenichiro; Toyoda, Masashi; Umezawa, Akihiro

2016-01-01

Disease-specific induced pluripotent stem cells (iPSCs) have been used as a model to analyze pathogenesis of disease. In this study, we generated iPSCs derived from a fibroblastic cell line of xeroderma pigmentosum (XP) group A (XPA-iPSCs), a rare autosomal recessive hereditary disease in which patients develop skin cancer in the areas of skin exposed to sunlight. XPA-iPSCs exhibited hypersensitivity to ultraviolet exposure and accumulation of single-nucleotide substitutions when compared with ataxia telangiectasia-derived iPSCs that were established in a previous study. However, XPA-iPSCs did not show any chromosomal instability in vitro, i.e. intact chromosomes were maintained. The results were mutually compensating for examining two major sources of mutations, nucleotide excision repair deficiency and double-strand break repair deficiency. Like XP patients, XPA-iPSCs accumulated single-nucleotide substitutions that are associated with malignant melanoma, a manifestation of XP. These results indicate that XPA-iPSCs may serve a monitoring tool (analogous to the Ames test but using mammalian cells) to measure single-nucleotide alterations, and may be a good model to clarify pathogenesis of XP. In addition, XPA-iPSCs may allow us to facilitate development of drugs that delay genetic alteration and decrease hypersensitivity to ultraviolet for therapeutic applications. PMID:27197874

Peptide immunotherapy in allergic asthma generates IL-10–dependent immunological tolerance associated with linked epitope suppression

PubMed Central

Campbell, John D.; Buckland, Karen F.; McMillan, Sarah J.; Kearley, Jennifer; Oldfield, William L.G.; Stern, Lawrence J.; Grönlund, Hans; van Hage, Marianne; Reynolds, Catherine J.; Boyton, Rosemary J.; Cobbold, Stephen P.; Kay, A. Barry; Altmann, Daniel M.; Larché, Mark

2009-01-01

Treatment of patients with allergic asthma using low doses of peptides containing T cell epitopes from Fel d 1, the major cat allergen, reduces allergic sensitization and improves surrogate markers of disease. Here, we demonstrate a key immunological mechanism, linked epitope suppression, associated with this therapeutic effect. Treatment with selected epitopes from a single allergen resulted in suppression of responses to other (“linked”) epitopes within the same molecule. This phenomenon was induced after peptide immunotherapy in human asthmatic subjects and in a novel HLA-DR1 transgenic mouse model of asthma. Tracking of allergen-specific T cells using DR1 tetramers determined that suppression was associated with the induction of interleukin (IL)-10+ T cells that were more abundant than T cells specific for the single-treatment peptide and was reversed by anti–IL-10 receptor administration. Resolution of airway pathophysiology in this model was associated with reduced recruitment, proliferation, and effector function of allergen-specific Th2 cells. Our results provide, for the first time, in vivo evidence of linked epitope suppression and IL-10 induction in both human allergic disease and a mouse model designed to closely mimic peptide therapy in humans. PMID:19528258

Unimpaired terminal erythroid differentiation and preserved enucleation capacity in myelodysplastic 5q(del) clones: a single cell study

PubMed Central

Garderet, Laurent; Kobari, Ladan; Mazurier, Christelle; De Witte, Caroline; Giarratana, Marie-Catherine; Pérot, Christine; Gorin, Norbert Claude; Lapillonne, Hélène; Douay, Luc

2010-01-01

Background Anemia is a characteristic of myelodysplastic syndromes, such as the rare 5q- syndrome, but its mechanism remains unclear. In particular, data are lacking on the terminal phase of differentiation of erythroid cells (enucleation) in myelodysplastic syndromes. Design and Methods We used a previously published culture model to generate mature red blood cells in vitro from human hematopoietic progenitor cells in order to study the pathophysiology of the 5q- syndrome. Our model enables analysis of cell proliferation and differentiation at a single cell level and determination of the enucleation capacity of erythroid precursors. Results The erythroid commitment of 5q(del) clones was not altered and their terminal differentiation capacity was preserved since they achieved final erythroid maturation (enucleation stage). The drop in red blood cell production was secondary to the decrease in the erythroid progenitor cell pool and to impaired proliferative capacity. RPS14 gene haploinsufficiency was related to defective erythroid proliferation but not to differentiation capacity. Conclusions The 5q- syndrome should be considered a quantitative rather than qualitative bone marrow defect. This observation might open the way to new therapeutic concepts. PMID:19815832

Multiple scale model for cell migration in monolayers: Elastic mismatch between cells enhances motility

NASA Astrophysics Data System (ADS)

Palmieri, Benoit; Bresler, Yony; Wirtz, Denis; Grant, Martin

2015-07-01

We propose a multiscale model for monolayer of motile cells that comprise normal and cancer cells. In the model, the two types of cells have identical properties except for their elasticity; cancer cells are softer and normal cells are stiffer. The goal is to isolate the role of elasticity mismatch on the migration potential of cancer cells in the absence of other contributions that are present in real cells. The methodology is based on a phase-field description where each cell is modeled as a highly-deformable self-propelled droplet. We simulated two types of nearly confluent monolayers. One contains a single cancer cell in a layer of normal cells and the other contains normal cells only. The simulation results demonstrate that elasticity mismatch alone is sufficient to increase the motility of the cancer cell significantly. Further, the trajectory of the cancer cell is decorated by several speed “bursts” where the cancer cell quickly relaxes from a largely deformed shape and consequently increases its translational motion. The increased motility and the amplitude and frequency of the bursts are in qualitative agreement with recent experiments.

Iso-acoustic focusing of cells for size-insensitive acousto-mechanical phenotyping

PubMed Central

Augustsson, Per; Karlsen, Jonas T.; Su, Hao-Wei; Bruus, Henrik; Voldman, Joel

2016-01-01

Mechanical phenotyping of single cells is an emerging tool for cell classification, enabling assessment of effective parameters relating to cells' interior molecular content and structure. Here, we present iso-acoustic focusing, an equilibrium method to analyze the effective acoustic impedance of single cells in continuous flow. While flowing through a microchannel, cells migrate sideways, influenced by an acoustic field, into streams of increasing acoustic impedance, until reaching their cell-type specific point of zero acoustic contrast. We establish an experimental procedure and provide theoretical justifications and models for iso-acoustic focusing. We describe a method for providing a suitable acoustic contrast gradient in a cell-friendly medium, and use acoustic forces to maintain that gradient in the presence of destabilizing forces. Applying this method we demonstrate iso-acoustic focusing of cell lines and leukocytes, showing that acoustic properties provide phenotypic information independent of size. PMID:27180912

Iso-acoustic focusing of cells for size-insensitive acousto-mechanical phenotyping.

PubMed

Augustsson, Per; Karlsen, Jonas T; Su, Hao-Wei; Bruus, Henrik; Voldman, Joel

2016-05-16

Mechanical phenotyping of single cells is an emerging tool for cell classification, enabling assessment of effective parameters relating to cells' interior molecular content and structure. Here, we present iso-acoustic focusing, an equilibrium method to analyze the effective acoustic impedance of single cells in continuous flow. While flowing through a microchannel, cells migrate sideways, influenced by an acoustic field, into streams of increasing acoustic impedance, until reaching their cell-type specific point of zero acoustic contrast. We establish an experimental procedure and provide theoretical justifications and models for iso-acoustic focusing. We describe a method for providing a suitable acoustic contrast gradient in a cell-friendly medium, and use acoustic forces to maintain that gradient in the presence of destabilizing forces. Applying this method we demonstrate iso-acoustic focusing of cell lines and leukocytes, showing that acoustic properties provide phenotypic information independent of size.

Synchronization of glycolytic oscillations in a yeast cell population.

PubMed

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

2001-01-01

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

Toxicity of an α-Pore-forming Toxin Depends on the Assembly Mechanism on the Target Membrane as Revealed by Single Molecule Imaging*

PubMed Central

Subburaj, Yamunadevi; Ros, Uris; Hermann, Eduard; Tong, Rudi; García-Sáez, Ana J.

2015-01-01

α-Pore-forming toxins (α-PFTs) are ubiquitous defense tools that kill cells by opening pores in the target cell membrane. Despite their relevance in host/pathogen interactions, very little is known about the pore stoichiometry and assembly pathway leading to membrane permeabilization. Equinatoxin II (EqtII) is a model α-PFT from sea anemone that oligomerizes and forms pores in sphingomyelin-containing membranes. Here, we determined the spatiotemporal organization of EqtII in living cells by single molecule imaging. Surprisingly, we found that on the cell surface EqtII did not organize into a unique oligomeric form. Instead, it existed as a mixture of oligomeric species mostly including monomers, dimers, tetramers, and hexamers. Mathematical modeling based on our data supported a new model in which toxin clustering happened in seconds and proceeded via condensation of EqtII dimer units formed upon monomer association. Furthermore, altering the pathway of EqtII assembly strongly affected its toxic activity, which highlights the relevance of the assembly mechanism on toxicity. PMID:25525270

Phase locking and multiple oscillating attractors for the coupled mammalian clock and cell cycle

PubMed Central

Feillet, Céline; Krusche, Peter; Tamanini, Filippo; Janssens, Roel C.; Downey, Mike J.; Martin, Patrick; Teboul, Michèle; Saito, Shoko; Lévi, Francis A.; Bretschneider, Till; van der Horst, Gijsbertus T. J.; Delaunay, Franck; Rand, David A.

2014-01-01

Daily synchronous rhythms of cell division at the tissue or organism level are observed in many species and suggest that the circadian clock and cell cycle oscillators are coupled. For mammals, despite known mechanistic interactions, the effect of such coupling on clock and cell cycle progression, and hence its biological relevance, is not understood. In particular, we do not know how the temporal organization of cell division at the single-cell level produces this daily rhythm at the tissue level. Here we use multispectral imaging of single live cells, computational methods, and mathematical modeling to address this question in proliferating mouse fibroblasts. We show that in unsynchronized cells the cell cycle and circadian clock robustly phase lock each other in a 1:1 fashion so that in an expanding cell population the two oscillators oscillate in a synchronized way with a common frequency. Dexamethasone-induced synchronization reveals additional clock states. As well as the low-period phase-locked state there are distinct coexisting states with a significantly higher period clock. Cells transition to these states after dexamethasone synchronization. The temporal coordination of cell division by phase locking to the clock at a single-cell level has significant implications because disordered circadian function is increasingly being linked to the pathogenesis of many diseases, including cancer. PMID:24958884

Phase locking and multiple oscillating attractors for the coupled mammalian clock and cell cycle.

PubMed

Feillet, Céline; Krusche, Peter; Tamanini, Filippo; Janssens, Roel C; Downey, Mike J; Martin, Patrick; Teboul, Michèle; Saito, Shoko; Lévi, Francis A; Bretschneider, Till; van der Horst, Gijsbertus T J; Delaunay, Franck; Rand, David A

2014-07-08

Daily synchronous rhythms of cell division at the tissue or organism level are observed in many species and suggest that the circadian clock and cell cycle oscillators are coupled. For mammals, despite known mechanistic interactions, the effect of such coupling on clock and cell cycle progression, and hence its biological relevance, is not understood. In particular, we do not know how the temporal organization of cell division at the single-cell level produces this daily rhythm at the tissue level. Here we use multispectral imaging of single live cells, computational methods, and mathematical modeling to address this question in proliferating mouse fibroblasts. We show that in unsynchronized cells the cell cycle and circadian clock robustly phase lock each other in a 1:1 fashion so that in an expanding cell population the two oscillators oscillate in a synchronized way with a common frequency. Dexamethasone-induced synchronization reveals additional clock states. As well as the low-period phase-locked state there are distinct coexisting states with a significantly higher period clock. Cells transition to these states after dexamethasone synchronization. The temporal coordination of cell division by phase locking to the clock at a single-cell level has significant implications because disordered circadian function is increasingly being linked to the pathogenesis of many diseases, including cancer.

Developmental switching in Physarum polycephalum: Petri net analysis of single cell trajectories of gene expression indicates responsiveness and genetic plasticity of the Waddington quasipotential landscape

NASA Astrophysics Data System (ADS)

Werthmann, Britta; Marwan, Wolfgang

2017-11-01

The developmental switch to sporulation in Physarum polycephalum is a phytochrome-mediated far-red light-induced cell fate decision that synchronously encompasses the entire multinucleate plasmodial cell and is associated with extensive reprogramming of the transcriptome. By repeatedly taking samples of single cells after delivery of a light stimulus pulse, we analysed differential gene expression in two mutant strains and in a heterokaryon of the two strains all of which display a different propensity for making the cell fate decision. Multidimensional scaling of the gene expression data revealed individually different single cell trajectories eventually leading to sporulation. Characterization of the trajectories as walks through states of gene expression discretized by hierarchical clustering allowed the reconstruction of Petri nets that model and predict the observed behavior. Structural analyses of the Petri nets indicated stimulus- and genotype-dependence of both, single cell trajectories and of the quasipotential landscape through which these trajectories are taken. The Petri net-based approach to the analysis and decomposition of complex cellular responses and of complex mutant phenotypes may provide a scaffold for the data-driven reconstruction of causal molecular mechanisms that shape the topology of the quasipotential landscape.

Divergent cytosine DNA methylation patterns in single-cell, soybean root hairs.

PubMed

Hossain, Md Shakhawat; Kawakatsu, Taiji; Kim, Kyung Do; Zhang, Ning; Nguyen, Cuong T; Khan, Saad M; Batek, Josef M; Joshi, Trupti; Schmutz, Jeremy; Grimwood, Jane; Schmitz, Robert J; Xu, Dong; Jackson, Scott A; Ecker, Joseph R; Stacey, Gary

2017-04-01

Chromatin modifications, such as cytosine methylation of DNA, play a significant role in mediating gene expression in plants, which affects growth, development, and cell differentiation. As root hairs are single-cell extensions of the root epidermis and the primary organs for water uptake and nutrients, we sought to use root hairs as a single-cell model system to measure the impact of environmental stress. We measured changes in cytosine DNA methylation in single-cell root hairs as compared with multicellular stripped roots, as well as in response to heat stress. Differentially methylated regions (DMRs) in each methylation context showed very distinct methylation patterns between cell types and in response to heat stress. Intriguingly, at normal temperature, root hairs were more hypermethylated than were stripped roots. However, in response to heat stress, both root hairs and stripped roots showed hypomethylation in each context, especially in the CHH context. Moreover, expression analysis of mRNA from similar tissues and treatments identified some associations between DMRs, genes and transposons. Taken together, the data indicate that changes in DNA methylation are directly or indirectly associated with expression of genes and transposons within the context of either specific tissues/cells or stress (heat). © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Live Imaging of Cellular Internalization of Single Colloidal Particle by Combined Label-Free and Fluorescence Total Internal Reflection Microscopy.

PubMed

Byrne, Gerard D; Vllasaliu, Driton; Falcone, Franco H; Somekh, Michael G; Stolnik, Snjezana

2015-11-02

In this work we utilize the combination of label-free total internal reflection microscopy and total internal reflectance fluorescence (TIRM/TIRF) microscopy to achieve a simultaneous, live imaging of single, label-free colloidal particle endocytosis by individual cells. The TIRM arm of the microscope enables label free imaging of the colloid and cell membrane features, while the TIRF arm images the dynamics of fluorescent-labeled clathrin (protein involved in endocytosis via clathrin pathway), expressed in transfected 3T3 fibroblasts cells. Using a model polymeric colloid and cells with a fluorescently tagged clathrin endocytosis pathway, we demonstrate that wide field TIRM/TIRF coimaging enables live visualization of the process of colloidal particle interaction with the labeled cell structure, which is valuable for discerning the membrane events and route of colloid internalization by the cell. We further show that 500 nm in diameter model polystyrene colloid associates with clathrin, prior to and during its cellular internalization. This association is not apparent with larger, 1 μm in diameter colloids, indicating an upper particle size limit for clathrin-mediated endocytosis.

Multicellular detachment generates metastatic spheroids during intra-abdominal dissemination in epithelial ovarian cancer.

PubMed

Al Habyan, Sara; Kalos, Christina; Szymborski, Joseph; McCaffrey, Luke

2018-05-23

Ovarian cancer is the most lethal gynecological cancer, where survival rates have had modest improvement over the last 30 years. Metastasis of cancer cells is a major clinical problem, and patient mortality occurs when ovarian cancer cells spread beyond the confinement of ovaries. Disseminated ovarian cancer cells typically spread within the abdomen, where ascites accumulation aids in their transit. Metastatic ascites contain multicellular spheroids, which promote chemo-resistance and recurrence. However, little is known about the origin and mechanisms through which spheroids arise. Using live-imaging of 3D culture models and animal models, we report that epithelial ovarian cancer (EOC) cells, the most common type of ovarian cancer, can spontaneously detach as either single cells or clusters. We report that clusters are more resistant to anoikis and have a potent survival advantage over single cells. Using in vivo lineage tracing, we found that multicellular spheroids arise preferentially from collective detachment, rather than aggregation in the abdomen. Finally, we report that multicellular spheroids from collective detachment are capable of seeding intra-abdominal metastases that retain intra-tumoral heterogeneity from the primary tumor.

Ciliary heterogeneity within a single cell: the Paramecium model.

PubMed

Aubusson-Fleury, Anne; Cohen, Jean; Lemullois, Michel

2015-01-01

Paramecium is a single cell able to divide in its morphologically differentiated stage that has many cilia anchored at its cell surface. Many thousands of cilia are thus assembled in a short period of time during division to duplicate the cell pattern while the cell continues swimming. Most, but not all, of these sensory cilia are motile and involved in two main functions: prey capture and cell locomotion. These cilia display heterogeneity, both in their length and their biochemical properties. Thanks to these properties, as well as to the availability of many postgenomic tools and the possibility to follow the regrowth of cilia after deciliation, Paramecium offers a nice opportunity to study the assembly of the cilia, as well as the genesis of their diversity within a single cell. In this paper, after a brief survey of Paramecium morphology and cilia properties, we describe the tools and the protocols currently used for immunofluorescence, transmission electron microscopy, and ultrastructural immunocytochemistry to analyze cilia, with special recommendations to overcome the problem raised by cilium diversity. Copyright © 2015. Published by Elsevier Inc.

The comparison between gallium arsenide and indium gallium arsenide as materials for solar cell performance using Silvaco application

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

Zahari, Suhaila Mohd; Norizan, Mohd Natashah; Mohamad, Ili Salwani

2015-05-15

The work presented in this paper is about the development of single and multilayer solar cells using GaAs and InGaAs in AM1.5 condition. The study includes the modeling structure and simulation of the device using Silvaco applications. The performance in term of efficiency of Indium Gallium Arsenide (InGaAs) and GaAs material was studied by modification of the doping concentration and thickness of material in solar cells. The efficiency of the GaAs solar cell was higher than InGaAs solar cell for single layer solar cell. Single layer GaAs achieved an efficiency about 25% compared to InGaAs which is only 2.65% ofmore » efficiency. For multilayer which includes both GaAs and InGaAs, the output power, P{sub max} was 8.91nW/cm² with the efficiency only 8.51%. GaAs is one of the best materials to be used in solar cell as a based compared to InGaAs.« less

Single-molecule microscopy reveals membrane microdomain organization of cells in a living vertebrate.

PubMed

Schaaf, Marcel J M; Koopmans, Wiepke J A; Meckel, Tobias; van Noort, John; Snaar-Jagalska, B Ewa; Schmidt, Thomas S; Spaink, Herman P

2009-08-19

It has been possible for several years to study the dynamics of fluorescently labeled proteins by single-molecule microscopy, but until now this technology has been applied only to individual cells in culture. In this study, it was extended to stem cells and living vertebrate organisms. As a molecule of interest we used yellow fluorescent protein fused to the human H-Ras membrane anchor, which has been shown to serve as a model for proteins anchored in the plasma membrane. We used a wide-field fluorescence microscopy setup to visualize individual molecules in a zebrafish cell line (ZF4) and in primary embryonic stem cells. A total-internal-reflection microscopy setup was used for imaging in living organisms, in particular in epidermal cells in the skin of 2-day-old zebrafish embryos. Our results demonstrate the occurrence of membrane microdomains in which the diffusion of membrane proteins in a living organism is confined. This membrane organization differed significantly from that observed in cultured cells, illustrating the relevance of performing single-molecule microscopy in living organisms.

Visualizing interactions between Sindbis virus and cells by single particle tracking

NASA Astrophysics Data System (ADS)

Williard, Mary

2005-03-01

Sindbis virus infects both mammalian and insect cells. Though not pathogenic in humans, Sindbis is a model for many mosquito- borne viruses that cause human disease, such as West Nile virus. We have used real-time single particle fluorescence microscopy to observe individual Sindbis virus particles as they infect living cells. Fluorescent labels were incorporated into both the viral coat proteins and the lipid envelope of the virus. Kinetics characteristic of free diffusion in solution, slower diffusion inside cells, attachment to spots on the cell surface, and motor protein transport inside cells have been observed. Dequenching of the membrane label is used to report membrane fusion events during the infection process. Tracking individual viral particles allows multiple pathways to be determined without the requirement of synchronicity.

A medaka model of cancer allowing direct observation of transplanted tumor cells in vivo at a cellular-level resolution.

PubMed

Hasegawa, Sumitaka; Maruyama, Kouichi; Takenaka, Hikaru; Furukawa, Takako; Saga, Tsuneo

2009-08-18

The recent success with small fish as an animal model of cancer with the aid of fluorescence technique has attracted cancer modelers' attention because it would be possible to directly visualize tumor cells in vivo in real time. Here, we report a medaka model capable of allowing the observation of various cell behaviors of transplanted tumor cells, such as cell proliferation and metastasis, which were visualized easily in vivo. We established medaka melanoma (MM) cells stably expressing GFP and transplanted them into nonirradiated and irradiated medaka. The tumor cells were grown at the injection sites in medaka, and the spatiotemporal changes were visualized under a fluorescence stereoscopic microscope at a cellular-level resolution, and even at a single-cell level. Tumor dormancy and metastasis were also observed. Interestingly, in irradiated medaka, accelerated tumor growth and metastasis of the transplanted tumor cells were directly visualized. Our medaka model provides an opportunity to visualize in vivo tumor cells "as seen in a culture dish" and would be useful for in vivo tumor cell biology.

Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes

PubMed Central

Manning, Cerys; Rattray, Magnus

2017-01-01

Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5’ LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package. PMID:28493880

Bacteria as living patchy colloids: Phenotypic heterogeneity in surface adhesion

PubMed Central

Hermes, Michiel; Schwarz-Linek, Jana; Poon, Wilson C. K.

2018-01-01

Understanding and controlling the surface adhesion of pathogenic bacteria is of urgent biomedical importance. However, many aspects of this process remain unclear (for example, microscopic details of the initial adhesion and possible variations between individual cells). Using a new high-throughput method, we identify and follow many single cells within a clonal population of Escherichia coli near a glass surface. We find strong phenotypic heterogeneities: A fraction of the cells remain in the free (planktonic) state, whereas others adhere with an adhesion strength that itself exhibits phenotypic heterogeneity. We explain our observations using a patchy colloid model; cells bind with localized, adhesive patches, and the strength of adhesion is determined by the number of patches: Nonadherers have no patches, weak adherers bind with a single patch only, and strong adherers bind via a single or multiple patches. We discuss possible implications of our results for controlling bacterial adhesion in biomedical and other applications. PMID:29719861

Differential tumor biology effects of double-initiation in a mouse skin chemical carcinogenesis model comparing wild type versus protein kinase Cepsilon overexpression mice.

PubMed

Li, Yafan; Wheeler, Deric L; Ananthaswamy, Honnavara N; Verma, Ajit K; Oberley, Terry D

2007-12-01

Our previous studies showed that protein kinase Cepsilon (PKCepsilon) verexpression in mouse skin resulted in metastatic squamous cell carcinoma (SCC) elicited by single 7,12-dimethylbenz(a)anthracene (DMBA)-initiation and 12-O-tetradecanoylphorbol-13-acetate (TPA)-promotion in the absence of preceding papilloma formation as is typically observed in wild type mice. The present study demonstrates that double-DMBA initiation modulates tumor incidence, multiplicity, and latency period in both wild type and PKCepsilon overexpression transgenic (PKCepsilon-Tg) mice. After 17 weeks (wks) of tumor promotion, a reduction in papilloma multiplicity was observed in double- versus single-DMBA initiated wild type mice. Papilloma multiplicity was inversely correlated with cell death indices of interfollicular keratinocytes, indicating decreased papilloma formation was caused by increased cell death and suggesting the origin of papillomas is in interfollicular epidermis. Double-initiated PKCepsilon-Tg mice had accelerated carcinoma formation and cancer incidence in comparison to single-initiated PKCepsilon-Tg mice. Morphologic analysis of mouse skin following double initiation and tumor promotion showed a similar if not identical series of events to those previously observed following single initiation and tumor promotion: putative preneoplastic cells were observed arising from hyperplastic hair follicles (HFs) with subsequent cancer cell infiltration into the dermis. Single-initiated PKCepsilon-Tg mice exhibited increased mitosis in epidermal cells of HFs during tumor promotion.

Preclinical Evaluation of MET Inhibitor INC-280 With or Without the Epidermal Growth Factor Receptor Inhibitor Erlotinib in Non–Small-Cell Lung Cancer

PubMed Central

Lara, Matthew S.; Holland, William S.; Chinn, Danielle; Burich, Rebekah A.; Lara, Primo N.; Gandara, David R.; Kelly, Karen; Mack, Philip C.

2018-01-01

The MET inhibitor INC-280 restored sensitivity to erlotinib and promoted apoptosis in non–small-cell lung cancer models rendered resistant to erlotinib by hepatocyte growth factor. Background Although the epidermal growth factor receptor (EGFR) inhibitor erlotinib is initially effective in non–small-cell lung cancer (NSCLC) patients with tumors harboring activating mutations of EGFR, most subsequently develop acquired resistance. One recognized resistance mechanism occurs through activation of bypass signaling via the hepatocyte growth factor (HGF)-MET pathway. INC-280 is a small molecule kinase inhibitor of MET. We sought to demonstrate the activity of INC-280 on select NSCLC cell lines both as a single agent and in combination with erlotinib using exogenous HGF to simulate MET up-regulation. Methods Four NSCLC cell lines (HCC827, PC9, H1666, and H358) were treated with either single-agent INC-280 or in combination with erlotinib with or without HGF. The activity of the drug treatments was measured by cell viability assays. Immunoblotting was used to monitor expression of EGFR/pEGFR, MET/pMET, GAB1/pGAB1, AKT/pAKT, and ERK/pERK as well as markers of apoptosis (PARP and capase-3 cleavage) in H1666, HCC827, and PC9. Results As a single agent, INC-280 showed minimal cytotoxicity despite potent inhibition of MET kinase activity at concentrations as low as 10 nM. Addition of HGF prevented erlotinib-induced cell death. The addition of INC280 to HGF-mediated erlotinib-resistant models restored erlotinib sensitivity for all cell lines tested, associated with cleavage of both PARP and caspase-3. In these models, INC-280 treatment was sufficient to restore erlotinib-induced inhibition of MET, GAB1, AKT, and ERK in the presence of HGF. Conclusion Although the MET inhibitor INC-280 alone had no discernible effect on cell growth, it was able to restore sensitivity to erlotinib and promote apoptosis in NSCLC models rendered erlotinib resistant by HGF. These data provide a preclinical rationale for an ongoing phase 1 clinical trial of erlotinib plus INC-280 in EGFR-mutated NSCLC. PMID:28038979

Recent Advances in Microbial Single Cell Genomics Technology and Applications

NASA Astrophysics Data System (ADS)

Stepanauskas, R.

2016-02-01

Single cell genomics is increasingly utilized as a powerful tool to decipher the metabolic potential, evolutionary histories and in situ interactions of environmental microorganisms. This transformative technology recovers extensive information from cultivation-unbiased samples of individual, unicellular organisms. Thus, it does not require data binning into arbitrary phylogenetic or functional groups and therefore is highly compatible with agent-based modeling approaches. I will present several technological advances in this field, which significantly improve genomic data recovery from individual cells and provide direct linkages between cell's genomic and phenotypic properties. I will also demonstrate how these new technical capabilities help understanding the metabolic potential and viral infections of the "microbial dark matter" inhabiting aquatic and subsurface environments.

B7-H1 shapes T-cell-mediated brain endothelial cell dysfunction and regional encephalitogenicity in spontaneous CNS autoimmunity.

PubMed

Klotz, Luisa; Kuzmanov, Ivan; Hucke, Stephanie; Gross, Catharina C; Posevitz, Vilmos; Dreykluft, Angela; Schulte-Mecklenbeck, Andreas; Janoschka, Claudia; Lindner, Maren; Herold, Martin; Schwab, Nicholas; Ludwig-Portugall, Isis; Kurts, Christian; Meuth, Sven G; Kuhlmann, Tanja; Wiendl, Heinz

2016-10-11

Molecular mechanisms that determine lesion localization or phenotype variation in multiple sclerosis are mostly unidentified. Although transmigration of activated encephalitogenic T cells across the blood-brain barrier (BBB) is a crucial step in the disease pathogenesis of CNS autoimmunity, the consequences on brain endothelial barrier integrity upon interaction with such T cells and subsequent lesion formation and distribution are largely unknown. We made use of a transgenic spontaneous mouse model of CNS autoimmunity characterized by inflammatory demyelinating lesions confined to optic nerves and spinal cord (OSE mice). Genetic ablation of a single immune-regulatory molecule in this model [i.e., B7-homolog 1 (B7-H1, PD-L1)] not only significantly increased incidence of spontaneous CNS autoimmunity and aggravated disease course, especially in the later stages of disease, but also importantly resulted in encephalitogenic T-cell infiltration and lesion formation in normally unaffected brain regions, such as the cerebrum and cerebellum. Interestingly, B7-H1 ablation on myelin oligodendrocyte glycoprotein-specific CD4 + T cells, but not on antigen-presenting cells, amplified T-cell effector functions, such as IFN-γ and granzyme B production. Therefore, these T cells were rendered more capable of eliciting cell contact-dependent brain endothelial cell dysfunction and increased barrier permeability in an in vitro model of the BBB. Our findings suggest that a single immune-regulatory molecule on T cells can be ultimately responsible for localized BBB breakdown, and thus substantial changes in lesion topography in the context of CNS autoimmunity.

One-Cell Doubling Evaluation by Living Arrays of Yeast, ODELAY!

DOE PAGES

Herricks, Thurston; Dilworth, David J.; Mast, Fred D.; ...

2016-11-16

Cell growth is a complex phenotype widely used in systems biology to gauge the impact of genetic and environmental perturbations. Due to the magnitude of genome-wide studies, resolution is often sacrificed in favor of throughput, creating a demand for scalable, time-resolved, quantitative methods of growth assessment. We present ODELAY (One-cell Doubling Evaluation by Living Arrays of Yeast), an automated and scalable growth analysis platform. High measurement density and single-cell resolution provide a powerful tool for large-scale multiparameter growth analysis based on the modeling of microcolony expansion on solid media. Pioneered in yeast but applicable to other colony forming organisms, ODELAYmore » extracts the three key growth parameters (lag time, doubling time, and carrying capacity) that define microcolony expansion from single cells, simultaneously permitting the assessment of population heterogeneity. The utility of ODELAY is illustrated using yeast mutants, revealing a spectrum of phenotypes arising from single and combinatorial growth parameter perturbations.« less

One-Cell Doubling Evaluation by Living Arrays of Yeast, ODELAY!

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

Herricks, Thurston; Dilworth, David J.; Mast, Fred D.

Cell growth is a complex phenotype widely used in systems biology to gauge the impact of genetic and environmental perturbations. Due to the magnitude of genome-wide studies, resolution is often sacrificed in favor of throughput, creating a demand for scalable, time-resolved, quantitative methods of growth assessment. We present ODELAY (One-cell Doubling Evaluation by Living Arrays of Yeast), an automated and scalable growth analysis platform. High measurement density and single-cell resolution provide a powerful tool for large-scale multiparameter growth analysis based on the modeling of microcolony expansion on solid media. Pioneered in yeast but applicable to other colony forming organisms, ODELAYmore » extracts the three key growth parameters (lag time, doubling time, and carrying capacity) that define microcolony expansion from single cells, simultaneously permitting the assessment of population heterogeneity. The utility of ODELAY is illustrated using yeast mutants, revealing a spectrum of phenotypes arising from single and combinatorial growth parameter perturbations.« less

Accurate analytic solution of chemical master equations for gene regulation networks in a single cell

NASA Astrophysics Data System (ADS)

Huang, Guan-Rong; Saakian, David B.; Hu, Chin-Kun

2018-01-01

Studying gene regulation networks in a single cell is an important, interesting, and hot research topic of molecular biology. Such process can be described by chemical master equations (CMEs). We propose a Hamilton-Jacobi equation method with finite-size corrections to solve such CMEs accurately at the intermediate region of switching, where switching rate is comparable to fast protein production rate. We applied this approach to a model of self-regulating proteins [H. Ge et al., Phys. Rev. Lett. 114, 078101 (2015), 10.1103/PhysRevLett.114.078101] and found that as a parameter related to inducer concentration increases the probability of protein production changes from unimodal to bimodal, then to unimodal, consistent with phenotype switching observed in a single cell.

Theoretical model for optical oximetry at the capillary level: exploring hemoglobin oxygen saturation through backscattering of single red blood cells

NASA Astrophysics Data System (ADS)

Liu, Rongrong; Spicer, Graham; Chen, Siyu; Zhang, Hao F.; Yi, Ji; Backman, Vadim

2017-02-01

Oxygen saturation (sO2) of red blood cells (RBCs) in capillaries can indirectly assess local tissue oxygenation and metabolic function. For example, the altered retinal oxygenation in diabetic retinopathy and local hypoxia during tumor development in cancer are reflected by abnormal sO2 of local capillary networks. However, it is far from clear whether accurate label-free optical oximetry (i.e., measuring hemoglobin sO2) is feasible from dispersed RBCs at the single capillary level. The sO2-dependent hemoglobin absorption contrast present in optical scattering signal is complicated by geometry-dependent scattering from RBCs. We present a numerical study of backscattering spectra from single RBCs based on the first-order Born approximation, considering practical factors: RBC orientations, size variation, and deformations. We show that the oscillatory spectral behavior of RBC geometries is smoothed by variations in cell size and orientation, resulting in clear sO2-dependent spectral contrast. In addition, this spectral contrast persists with different mean cellular hemoglobin content and different deformations of RBCs. This study shows for the first time the feasibility of, and provides a theoretical model for, label-free optical oximetry at the single capillary level using backscattering-based imaging modalities, challenging the popular view that such measurements are impossible at the single capillary level.

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

PubMed

Kurhekar, Manish; Deshpande, Umesh

2016-01-01

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

Mathematical modelling of radiotherapy strategies for early breast cancer.

PubMed

Enderling, Heiko; Anderson, Alexander R A; Chaplain, Mark A J; Munro, Alastair J; Vaidya, Jayant S

2006-07-07

Targeted intraoperative radiotherapy (Targit) is a new concept of partial breast irradiation where single fraction radiotherapy is delivered directly to the tumour bed. Apart from logistic advantages, this strategy minimizes the risk of missing the tumour bed and avoids delay between surgery and radiotherapy. It is presently being compared with the standard fractionated external beam radiotherapy (EBRT) in randomized trials. In this paper we present a mathematical model for the growth and invasion of a solid tumour into a domain of tissue (in this case breast tissue), and then a model for surgery and radiation treatment of this tumour. We use the established linear-quadratic (LQ) model to compute the survival probabilities for both tumour cells and irradiated breast tissue and then simulate the effects of conventional EBRT and Targit. True local recurrence of the tumour could arise either from stray tumour cells, or the tumour bed that harbours morphologically normal cells having a predisposition to genetic changes, such as a loss of heterozygosity (LOH) in genes that are crucial for tumourigenesis, e.g. tumour suppressor genes (TSGs). Our mathematical model predicts that the single high dose of radiotherapy delivered by Targit would result in eliminating all these sources of recurrence, whereas the fractionated EBRT would eliminate stray tumour cells, but allow (by virtue of its very schedule) the cells with LOH in TSGs or cell-cycle checkpoint genes to pass on low-dose radiation-induced DNA damage and consequently mutations that may favour the development of a new tumour. The mathematical model presented here is an initial attempt to model a biologically complex phenomenon that has until now received little attention in the literature and provides a 'proof of principle' that it is possible to produce clinically testable hypotheses on the effects of different approaches of radiotherapy for breast cancer.

Implementing parallel spreadsheet models for health policy decisions: The impact of unintentional errors on model projections

PubMed Central

Bailey, Stephanie L.; Bono, Rose S.; Nash, Denis; Kimmel, April D.

2018-01-01

Background Spreadsheet software is increasingly used to implement systems science models informing health policy decisions, both in academia and in practice where technical capacity may be limited. However, spreadsheet models are prone to unintentional errors that may not always be identified using standard error-checking techniques. Our objective was to illustrate, through a methodologic case study analysis, the impact of unintentional errors on model projections by implementing parallel model versions. Methods We leveraged a real-world need to revise an existing spreadsheet model designed to inform HIV policy. We developed three parallel versions of a previously validated spreadsheet-based model; versions differed by the spreadsheet cell-referencing approach (named single cells; column/row references; named matrices). For each version, we implemented three model revisions (re-entry into care; guideline-concordant treatment initiation; immediate treatment initiation). After standard error-checking, we identified unintentional errors by comparing model output across the three versions. Concordant model output across all versions was considered error-free. We calculated the impact of unintentional errors as the percentage difference in model projections between model versions with and without unintentional errors, using +/-5% difference to define a material error. Results We identified 58 original and 4,331 propagated unintentional errors across all model versions and revisions. Over 40% (24/58) of original unintentional errors occurred in the column/row reference model version; most (23/24) were due to incorrect cell references. Overall, >20% of model spreadsheet cells had material unintentional errors. When examining error impact along the HIV care continuum, the percentage difference between versions with and without unintentional errors ranged from +3% to +16% (named single cells), +26% to +76% (column/row reference), and 0% (named matrices). Conclusions Standard error-checking techniques may not identify all errors in spreadsheet-based models. Comparing parallel model versions can aid in identifying unintentional errors and promoting reliable model projections, particularly when resources are limited. PMID:29570737

Implementing parallel spreadsheet models for health policy decisions: The impact of unintentional errors on model projections.

PubMed

Bailey, Stephanie L; Bono, Rose S; Nash, Denis; Kimmel, April D

2018-01-01

Spreadsheet software is increasingly used to implement systems science models informing health policy decisions, both in academia and in practice where technical capacity may be limited. However, spreadsheet models are prone to unintentional errors that may not always be identified using standard error-checking techniques. Our objective was to illustrate, through a methodologic case study analysis, the impact of unintentional errors on model projections by implementing parallel model versions. We leveraged a real-world need to revise an existing spreadsheet model designed to inform HIV policy. We developed three parallel versions of a previously validated spreadsheet-based model; versions differed by the spreadsheet cell-referencing approach (named single cells; column/row references; named matrices). For each version, we implemented three model revisions (re-entry into care; guideline-concordant treatment initiation; immediate treatment initiation). After standard error-checking, we identified unintentional errors by comparing model output across the three versions. Concordant model output across all versions was considered error-free. We calculated the impact of unintentional errors as the percentage difference in model projections between model versions with and without unintentional errors, using +/-5% difference to define a material error. We identified 58 original and 4,331 propagated unintentional errors across all model versions and revisions. Over 40% (24/58) of original unintentional errors occurred in the column/row reference model version; most (23/24) were due to incorrect cell references. Overall, >20% of model spreadsheet cells had material unintentional errors. When examining error impact along the HIV care continuum, the percentage difference between versions with and without unintentional errors ranged from +3% to +16% (named single cells), +26% to +76% (column/row reference), and 0% (named matrices). Standard error-checking techniques may not identify all errors in spreadsheet-based models. Comparing parallel model versions can aid in identifying unintentional errors and promoting reliable model projections, particularly when resources are limited.

Cell-matrix adhesion characterization using multiple shear stress zones in single stepwise microchannel

NASA Astrophysics Data System (ADS)

Kim, Min-Ji; Doh, Il; Bae, Gab-Yong; Cha, Hyuk-Jin; Cho, Young-Ho

2014-08-01

This paper presents a cell chip capable to characterize cell-matrix adhesion by monitoring cell detachment rate. The proposed cell chip can supply multiple levels of shear stress in single stepwise microchannel. As epithelial-mesenchymal transition (EMT), one of hallmarks of cancer metastasis is closely associated to the interaction with extracelluar matrix (ECM), we took advantage of two lung cancer cell models with different adhesion properties to ECM depending their epithelial or mesenchymal properties, including the pair of lung cancer cells with (A549sh) or without E-cadherin expression (A549sh-Ecad), which would be optimal model to examine the alteration of adhesion properties after EMT induction. The cell-matrix adhesion resisting to shear stress appeared to be remarkably differed between lung cancer cells. The detachment rate of epithelial-like H358 and mesenchymal-like H460 cells was 53%-80% and 25%-66% in the shear stress range of 34-60 dyn/cm2, respectively. A549sh-Ecad cells exhibits lower detachment rate (5%-9%) compared to A549sh cells (14%-40%). By direct comparison of adhesion between A549sh and A549sh-Ecad, we demonstrated that A549shE-cad to mimic EMT were more favorable to the ECM attachment under the various levels of shear stress. The present method can be applied to quantitative analysis of tumor cell-ECM adhesion.

Quantitative assessment of viable cells of Lactobacillus plantarum strains in single, dual and multi-strain biofilms.

PubMed

Fernández Ramírez, Mónica D; Kostopoulos, Ioannis; Smid, Eddy J; Nierop Groot, Masja N; Abee, Tjakko

2017-03-06

Biofilms of Lactobacillus plantarum are a potential source for contamination and recontamination of food products. Although biofilms have been mostly studied using single species or even single strains, it is conceivable that in a range of environmental settings including food processing areas, biofilms are composed of multiple species with each species represented by multiple strains. In this study six spoilage related L. plantarum strains FBR1-FBR6 and the model strain L. plantarum WCFS1 were characterised in single, dual and multiple strain competition models. A quantitative PCR approach was used with added propidium monoazide (PMA) enabling quantification of intact cells in the biofilm, representing the viable cell fraction that determines the food spoilage risk. Our results show that the performance of individual strains in multi-strain cultures generally correlates with their performance in pure culture, and relative strain abundance in multi-strain biofilms positively correlated with the relative strain abundance in suspended (planktonic) cultures. Performance of individual strains in dual-strain biofilms was highly influenced by the presence of the secondary strain, and in most cases no correlation between the relative contributions of viable planktonic cells and viable cells in the biofilm was noted. The total biofilm quantified by CV staining of the dual and multi-strain biofilms formed was mainly correlated to CV values of the dominant strain obtained in single strain studies. However, the combination of strain FBR5 and strain WCFS1 showed significantly higher CV values compared to the individual performances of both strains indicating that total biofilm formation was higher in this specific condition. Notably, L. plantarum FBR5 was able to outgrow all other strains and showed the highest relative abundance in dual and multi-strain biofilms. All the dual and multi-strain biofilms contained a considerable number of viable cells, representing a potential source of contamination. Copyright © 2016 Elsevier B.V. All rights reserved.

Organizing the Cellular and Molecular Heterogeneity in High-Grade Serous Ovarian Cancer by Mass Cytometry

DTIC Science & Technology

2013-10-01

5b. GRANT NUMBER W81XWH-12-1-0591 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Garry P. Nolan, Ph.D. 5d. PROJECT NUMBER Wendy J . Fantl...viable HG-SOC single cells prepared from clinically anno - tated samples where the parameters measured at the single-cell level will provide critical...models by comparison of genomic profiles. Nat Commun, 2013. 4: p. 2126. 2. Coticchia, C.M., J . Yang, and M.A. Moses, Ovarian cancer biomarkers: current

A generalized reaction diffusion model for spatial structure formed by motile cells.

PubMed

Ochoa, F L

1984-01-01

A non-linear stability analysis using a multi-scale perturbation procedure is carried out on a model of a generalized reaction diffusion mechanism which involves only a single equation but which nevertheless exhibits bifurcation to non-uniform states. The patterns generated by this model by variation in a parameter related to the scalar dimensions of domain of definition, indicate its capacity to represent certain key morphogenetic features of multicellular systems formed by motile cells.

Effects of early afterdepolarizations on excitation patterns in an accurate model of the human ventricles

PubMed Central

Seemann, Gunnar; Panfilov, Alexander V.; Vandersickel, Nele

2017-01-01

Early Afterdepolarizations, EADs, are defined as the reversal of the action potential before completion of the repolarization phase, which can result in ectopic beats. However, the series of mechanisms of EADs leading to these ectopic beats and related cardiac arrhythmias are not well understood. Therefore, we aimed to investigate the influence of this single cell behavior on the whole heart level. For this study we used a modified version of the Ten Tusscher-Panfilov model of human ventricular cells (TP06) which we implemented in a 3D ventricle model including realistic fiber orientations. To increase the likelihood of EAD formation at the single cell level, we reduced the repolarization reserve (RR) by reducing the rapid delayed rectifier Potassium current and raising the L-type Calcium current. Varying these parameters defined a 2D parametric space where different excitation patterns could be classified. Depending on the initial conditions, by either exciting the ventricles with a spiral formation or burst pacing protocol, we found multiple different spatio-temporal excitation patterns. The spiral formation protocol resulted in the categorization of a stable spiral (S), a meandering spiral (MS), a spiral break-up regime (SB), spiral fibrillation type B (B), spiral fibrillation type A (A) and an oscillatory excitation type (O). The last three patterns are a 3D generalization of previously found patterns in 2D. First, the spiral fibrillation type B showed waves determined by a chaotic bi-excitable regime, i.e. mediated by both Sodium and Calcium waves at the same time and in same tissue settings. In the parameter region governed by the B pattern, single cells were able to repolarize completely and different (spiral) waves chaotically burst into each other without finishing a 360 degree rotation. Second, spiral fibrillation type A patterns consisted of multiple small rotating spirals. Single cells failed to repolarize to the resting membrane potential hence prohibiting the Sodium channel gates to recover. Accordingly, we found that Calcium waves mediated these patterns. Third, a further reduction of the RR resulted in a more exotic parameter regime whereby the individual cells behaved independently as oscillators. The patterns arose due to a phase-shift of different oscillators as disconnection of the cells resulted in continuation of the patterns. For all patterns, we computed realistic 9 lead ECGs by including a torso model. The B and A type pattern exposed the behavior of Ventricular Tachycardia (VT). We conclude that EADs at the single cell level can result in different types of cardiac fibrillation at the tissue and 3D ventricle level. PMID:29216239

Dynamic Modeling, Model-Based Control, and Optimization of Solid Oxide Fuel Cells

NASA Astrophysics Data System (ADS)

Spivey, Benjamin James

2011-07-01

Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.

Effect of the microtubule-associated protein tau on dynamics of single-headed motor proteins KIF1A

NASA Astrophysics Data System (ADS)

Sparacino, J.; Farías, M. G.; Lamberti, P. W.

2014-02-01

Intracellular transport based on molecular motors and its regulation are crucial to the functioning of cells. Filamentary tracks of the cells are abundantly decorated with nonmotile microtubule-associated proteins, such as tau. Motivated by experiments on kinesin-tau interactions [Dixit et al., Science 319, 1086 (2008), 10.1126/science.1152993] we developed a stochastic model of interacting single-headed motor proteins KIF1A that also takes into account the interactions between motor proteins and tau molecules. Our model reproduces experimental observations and predicts significant effects of tau on bound time and run length which suggest an important role of tau in regulation of kinesin-based transport.

Problems in mechanistic theoretical models for cell transformation by ionizing radiation

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

Chatterjee, A.; Holley, W.R.

1991-10-01

A mechanistic model based on yields of double strand breaks has been developed to determine the dose response curves for cell transformation frequencies. At its present stage the model is applicable to immortal cell lines and to various qualities (X-rays, Neon and Iron) of ionizing radiation. Presently, we have considered four types of processes which can lead to activation phenomena: (1) point mutation events on a regulatory segment of selected oncogenes, (2) inactivation of suppressor genes, through point mutation, (3) deletion of a suppressor gene by a single track, and (4) deletion of a suppressor gene by two tracks.

Enhanced antitumor effect of YM872 and AG1296 combination treatment on human glioblastoma xenograft models.

PubMed

Watanabe, Takashi; Ohtani, Toshiyuki; Aihara, Masanori; Ishiuchi, Shogo

2013-04-01

Blockade of Ca(++)-permeable α-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptor (AMPAR) inhibits the proliferation of human glioblastoma by inhibiting Akt phosphorylation, which is independent of the phosphatidylinositol 3-kinase pathway. Inhibiting platelet-derived growth factor receptor (PDGFR)-mediated phosphorylation causes growth inhibition in glioblastoma cells. The authors of this study investigated the effects of YM872 and AG1296, singly and in combination and targeting different pathways upstream of Akt, on Akt-mediated tumor growth in glioblastoma cells in vivo and in vitro. The expression of AMPAR, PDGFR, and c-kit in glioblastoma cells was analyzed via immunofluorescence. Glioblastoma cells, both in culture and in xenografts grown in mice, were treated with YM872 and AG1296, singly or in combination. Inhibition of tumor growth was observed after treatment in the xenograft model. Cell proliferation assays were performed using anti-Ki 67 antibody in vivo and in vitro. The CD34-positive tumor vessel counts within the vascular hot spots of tumor specimens were evaluated. Phosphorylation of Akt was studied using Western blot analysis. Combined administration of YM872 and AG1296 had a significant enhanced effect on the inhibition of cell proliferation and reduction of tumor vascularity in the xenograft model. These agents singly and in combination demonstrated a significant reduction of Akt phosphorylation at Ser473 and inhibition of tumor proliferation in vitro, although combined administration had no enhanced antitumor effects. The strongly enhanced antitumor effect of this combination therapy in vivo rather than in vitro may be attributable to disruption of the aberrant vascular niche. This combination therapy might provide substantial benefits to patients with glioblastoma.

Probing cooperative force generation in collective cancer invasion

NASA Astrophysics Data System (ADS)

Alobaidi, Amani A.; Xu, Yaopengxiao; Chen, Shaohua; Jiao, Yang; Sun, Bo

2017-08-01

Collective cellular dynamics in the three-dimensional extracellular matrix (ECM) plays a crucial role in many physiological processes such as cancer invasion. Both chemical and mechanical signaling support cell-cell communications on a variety of length scales, leading to collective migratory behaviors. Here we conduct experiments using 3D in vitro tumor models and develop a phenomenological model in order to probe the cooperativity of force generation in the collective invasion of breast cancer cells. In our model, cell-cell communication is characterized by a single parameter that quantifies the correlation length of cellular migration cycles. We devise a stochastic reconstruction method to generate realizations of cell colonies with specific contraction phase correlation functions and correlation length a. We find that as a increases, the characteristic size of regions containing cells with similar contraction phases grows. For small a values, the large fluctuations in individual cell contraction phases smooth out the temporal fluctuations in the time-dependent deformation field in the ECM. For large a values, the periodicity of an individual cell contraction cycle is clearly manifested in the temporal variation of the overall deformation field in the ECM. Through quantitative comparisons of the simulated and experimentally measured deformation fields, we find that the correlation length for collective force generation in the breast cancer diskoid in geometrically micropatterned ECM (DIGME) system is a≈ 25~μ \\text{m} , which is roughly twice the linear size of a single cell. One possible mechanism for this intermediate cell correlation length is the fiber-mediated stress propagation in the 3D ECM network in the DIGME system.

Live cell and immuno-labeling techniques to study gravitational effects on single plant cells.

PubMed

Chebli, Youssef; Geitmann, Anja

2015-01-01

The constant force of gravity plays a primordial role in the ontogeny of all living organisms. Plants, for example, develop their roots and shoots in accordance with the direction of the gravitational vector. Any change in the magnitude and/or the direction of gravity has an important impact on the development of tissues and cells. In order to understand how the gravitational force affects plant cell growth and differentiation, we established two complementary experimental procedures with which the effect of hyper-gravity on single plant cell development can be assessed. The single model cell system we used is the pollen tube or male gametophyte which, because of its rapid growth behavior, is known for its instant response to external stresses. The physiological response of the pollen tube can be assessed in a quantitative manner based on changes in the composition and spatial distribution of its cell wall components and in the precisely defined pattern of its very dynamic cytoplasmic streaming. Here, we provide a detailed description of the steps required for the immuno-localization of various cell wall components using microwave-assisted techniques and we explain how live imaging of the intracellular traffic can be achieved under hyper-gravity conditions.

Evaluation of concentrated space solar arrays using computer modeling. [for spacecraft propulsion and power supplies

NASA Technical Reports Server (NTRS)

Rockey, D. E.

1979-01-01

A general approach is developed for predicting the power output of a concentrator enhanced photovoltaic space array. A ray trace routine determines the concentrator intensity arriving at each solar cell. An iterative calculation determines the cell's operating temperature since cell temperature and cell efficiency are functions of one another. The end result of the iterative calculation is that the individual cell's power output is determined as a function of temperature and intensity. Circuit output is predicted by combining the individual cell outputs using the single diode model of a solar cell. Concentrated array characteristics such as uniformity of intensity and operating temperature at various points across the array are examined using computer modeling techniques. An illustrative example is given showing how the output of an array can be enhanced using solar concentration techniques.

Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution.

PubMed

Ling, Shaoping; Hu, Zheng; Yang, Zuyu; Yang, Fang; Li, Yawei; Lin, Pei; Chen, Ke; Dong, Lili; Cao, Lihua; Tao, Yong; Hao, Lingtong; Chen, Qingjian; Gong, Qiang; Wu, Dafei; Li, Wenjie; Zhao, Wenming; Tian, Xiuyun; Hao, Chunyi; Hungate, Eric A; Catenacci, Daniel V T; Hudson, Richard R; Li, Wen-Hsiung; Lu, Xuemei; Wu, Chung-I

2015-11-24

The prevailing view that the evolution of cells in a tumor is driven by Darwinian selection has never been rigorously tested. Because selection greatly affects the level of intratumor genetic diversity, it is important to assess whether intratumor evolution follows the Darwinian or the non-Darwinian mode of evolution. To provide the statistical power, many regions in a single tumor need to be sampled and analyzed much more extensively than has been attempted in previous intratumor studies. Here, from a hepatocellular carcinoma (HCC) tumor, we evaluated multiregional samples from the tumor, using either whole-exome sequencing (WES) (n = 23 samples) or genotyping (n = 286) under both the infinite-site and infinite-allele models of population genetics. In addition to the many single-nucleotide variations (SNVs) present in all samples, there were 35 "polymorphic" SNVs among samples. High genetic diversity was evident as the 23 WES samples defined 20 unique cell clones. With all 286 samples genotyped, clonal diversity agreed well with the non-Darwinian model with no evidence of positive Darwinian selection. Under the non-Darwinian model, MALL (the number of coding region mutations in the entire tumor) was estimated to be greater than 100 million in this tumor. DNA sequences reveal local diversities in small patches of cells and validate the estimation. In contrast, the genetic diversity under a Darwinian model would generally be orders of magnitude smaller. Because the level of genetic diversity will have implications on therapeutic resistance, non-Darwinian evolution should be heeded in cancer treatments even for microscopic tumors.

Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution

PubMed Central

Ling, Shaoping; Hu, Zheng; Yang, Zuyu; Yang, Fang; Li, Yawei; Lin, Pei; Chen, Ke; Dong, Lili; Cao, Lihua; Tao, Yong; Hao, Lingtong; Chen, Qingjian; Gong, Qiang; Wu, Dafei; Li, Wenjie; Zhao, Wenming; Tian, Xiuyun; Hao, Chunyi; Hungate, Eric A.; Catenacci, Daniel V. T.; Hudson, Richard R.; Li, Wen-Hsiung; Lu, Xuemei; Wu, Chung-I

2015-01-01

The prevailing view that the evolution of cells in a tumor is driven by Darwinian selection has never been rigorously tested. Because selection greatly affects the level of intratumor genetic diversity, it is important to assess whether intratumor evolution follows the Darwinian or the non-Darwinian mode of evolution. To provide the statistical power, many regions in a single tumor need to be sampled and analyzed much more extensively than has been attempted in previous intratumor studies. Here, from a hepatocellular carcinoma (HCC) tumor, we evaluated multiregional samples from the tumor, using either whole-exome sequencing (WES) (n = 23 samples) or genotyping (n = 286) under both the infinite-site and infinite-allele models of population genetics. In addition to the many single-nucleotide variations (SNVs) present in all samples, there were 35 “polymorphic” SNVs among samples. High genetic diversity was evident as the 23 WES samples defined 20 unique cell clones. With all 286 samples genotyped, clonal diversity agreed well with the non-Darwinian model with no evidence of positive Darwinian selection. Under the non-Darwinian model, MALL (the number of coding region mutations in the entire tumor) was estimated to be greater than 100 million in this tumor. DNA sequences reveal local diversities in small patches of cells and validate the estimation. In contrast, the genetic diversity under a Darwinian model would generally be orders of magnitude smaller. Because the level of genetic diversity will have implications on therapeutic resistance, non-Darwinian evolution should be heeded in cancer treatments even for microscopic tumors. PMID:26561581

Development of a chicken ileal explant culture model for measurement of gut inflammation induced by lipopolysaccharide

USDA-ARS?s Scientific Manuscript database

Gut mucosa holds a single layer of epithelial cells and the largest mass of lymphoid tissue in the body. While epithelial cell culture is widely used to assess intestinal barrier functions, it has limitations for studying cellular interactions with other cells, in particular those of the immune syst...

Novel T lymphocyte proliferation assessment using whole mouse cryo-imaging

NASA Astrophysics Data System (ADS)

Wuttisarnwattana, Patiwet; Raza, Syed A.; Eid, Saada; Cooke, Kenneth R.; Wilson, David L.

2014-03-01

New imaging technologies enable one to assess T-cell proliferation, an important feature of the immunological response. However, none of the traditional imaging modalities allow one to examine quantiatively T-cell function with microscopic resolution and single cell sensitivity over an entire mouse. To address this need, we established T-cells proliferation assays using 3D microscopic cryo-imaging. Assays include: (1) biodistribution of T-cells, (2) secondary lymphoid organ (SLO) volume measurement, (3) carboxyfluorescein succinimidyl ester (CFSE) dilution per cell as cells divide. To demonstrate the application, a graft-versus-host-disease (GVHD) model was used. 3D visualization show that T-cells specifically homed to the SLOs (spleen and lymph nodes) as well as GVHD target organs (such as GI-tract, liver, skin and thymus).The spleen was chosen as representative of the SLOs. For spleen size analysis, volumes of red and white pulp were measured. Spleen volumes of the allogeneic mice (with GVHD) were significantly larger than those of the syngeneic mice (without GVHD) at 72 to 120 hours post-transplant. For CFSE dilution approach, we employed color-coded volume rendering and probability density function (PDF) of single cell intensity to assess T-cell proliferation in the spleen. As compared to syngeneic T-cells, the allogeneic T-cells quickly aggregated in the spleen as indicated by increasing of CFSE signal over the first 48 hours. Then they rapidly proliferated as evidenced by reduced CFSE intensity (at 48-96 hours). Results suggest that assays can be used to study GVHD treatments using T-cell proliferation and biodistibution as assays. In summary, this is the first time that we are able to track and visualize T-cells in whole mouse with single cell sensitivity. We believe that our technique can be an alternative choice to traditional in vitro immunological proliferation assays by providing assessment of proliferation in an in vivo model.

Mathematical modeling of a continuous alcoholic fermentation process in a two-stage tower reactor cascade with flocculating yeast recycle.

PubMed

de Oliveira, Samuel Conceição; de Castro, Heizir Ferreira; Visconti, Alexandre Eliseu Stourdze; Giudici, Reinaldo

2015-03-01

Experiments of continuous alcoholic fermentation of sugarcane juice with flocculating yeast recycle were conducted in a system of two 0.22-L tower bioreactors in series, operated at a range of dilution rates (D 1 = D 2 = 0.27-0.95 h(-1)), constant recycle ratio (α = F R /F = 4.0) and a sugar concentration in the feed stream (S 0) around 150 g/L. The data obtained in these experimental conditions were used to adjust the parameters of a mathematical model previously developed for the single-stage process. This model considers each of the tower bioreactors as a perfectly mixed continuous reactor and the kinetics of cell growth and product formation takes into account the limitation by substrate and the inhibition by ethanol and biomass, as well as the substrate consumption for cellular maintenance. The model predictions agreed satisfactorily with the measurements taken in both stages of the cascade. The major differences with respect to the kinetic parameters previously estimated for a single-stage system were observed for the maximum specific growth rate, for the inhibition constants of cell growth and for the specific rate of substrate consumption for cell maintenance. Mathematical models were validated and used to simulate alternative operating conditions as well as to analyze the performance of the two-stage process against that of the single-stage process.

A single-platform approach using flow cytometry and microbeads to evaluate immune reconstitution in mice after bone marrow transplantation.

PubMed

Perruche, Sylvain; Kleinclauss, François; Lienard, Agnès; Robinet, Eric; Tiberghien, Pierre; Saas, Philippe

2004-11-01

The monitoring of immune reconstitution in murine models of HC transplantation, using accurate and automated methods, is necessary in view of the recent developments of hematopoietic cell (HC) transplantation (including reduced intensity conditioning regimens) as well as emerging immunological concepts (such as the involvement of dendritic cells or regulatory T cells). Here, we describe the use of a single-platform approach based on flow cytometry and tubes that contain a defined number of microbeads to evaluate absolute blood cell counts in mice. This method, previously used in humans to quantify CD34+ stem cells or CD4+ T cells in HIV infected patients, was adapted for mouse blood samples. A CD45 gating strategy in this "lyse no wash" protocol makes it possible to discriminate erythroblasts or red blood cell debris from CD45+ leukocytes, thus avoiding cell loss. Tubes contain a lyophilized brightly fluorescent microbead pellet permitting the acquisition of absolute counts of leukocytes after flow cytometric analysis. We compared this method to determine absolute counts of circulating cells with another method combining Unopette reservoir diluted blood samples, hemocytometer, microscopic examination and flow cytometry. The sensitivity of this single-platform approach was evaluated in different situations encountered in allogeneic HC transplantation, including immune cell depletion after different conditioning regimens, activation status of circulating cells after transplantation, evaluation of in vivo cell depletion and hematopoietic progenitor mobilization in the periphery. This single-platform flow cytometric assay can also be proposed to standardize murine (or other mammalian species) leukocyte count determination for physiological, pharmacological/toxicological and diagnostic applications in veterinary practice.

Nonclassical Kinetics of Clonal yet Heterogeneous Enzymes.

PubMed

Park, Seong Jun; Song, Sanggeun; Jeong, In-Chun; Koh, Hye Ran; Kim, Ji-Hyun; Sung, Jaeyoung

2017-07-06

Enzyme-to-enzyme variation in the catalytic rate is ubiquitous among single enzymes created from the same genetic information, which persists over the lifetimes of living cells. Despite advances in single-enzyme technologies, the lack of an enzyme reaction model accounting for the heterogeneous activity of single enzymes has hindered a quantitative understanding of the nonclassical stochastic outcome of single enzyme systems. Here we present a new statistical kinetics and exactly solvable models for clonal yet heterogeneous enzymes with possibly nonergodic state dynamics and state-dependent reactivity, which enable a quantitative understanding of modern single-enzyme experimental results for the mean and fluctuation in the number of product molecules created by single enzymes. We also propose a new experimental measure of the heterogeneity and nonergodicity for a system of enzymes.

In vitro 3D regeneration-like growth of human patient brain tissue.

PubMed

Tang-Schomer, M D; Wu, W B; Kaplan, D L; Bookland, M J

2018-05-01

In vitro culture of primary neurons is widely adapted with embryonic but not mature brain tissue. Here, we extended a previously developed bioengineered three-dimensional (3D) embryonic brain tissue model to resected normal patient brain tissue in an attempt to regenerate human neurons in vitro. Single cells and small sized (diameter < 100 μm) spheroids from dissociated brain tissue were seeded into 3D silk fibroin-based scaffolds, with or without collagen or Matrigel, and compared with two-dimensional cultures and scaffold-free suspension cultures. Changes of cell phenotypes (neuronal, astroglial, neural progenitor, and neuroepithelial) were quantified with flow cytometry and analyzed with a new method of statistical analysis specifically designed for percentage comparison. Compared with a complete lack of viable cells in conventional neuronal cell culture condition, supplements of vascular endothelial growth factor-containing pro-endothelial cell condition led to regenerative growth of neurons and astroglial cells from "normal" human brain tissue of epilepsy surgical patients. This process involved delayed expansion of Nestin+ neural progenitor cells, emergence of TUJ1+ immature neurons, and Vimentin+ neuroepithelium-like cell sheet formation in prolonged cultures (14 weeks). Micro-tissue spheroids, but not single cells, supported the brain tissue growth, suggesting importance of preserving native cell-cell interactions. The presence of 3D scaffold, but not hydrogel, allowed for Vimentin+ cell expansion, indicating a different growth mechanism than pluripotent cell-based brain organoid formation. The slow and delayed process implied an origin of quiescent neural precursors in the neocortex tissue. Further optimization of the 3D tissue model with primary human brain cells could provide personalized brain disease models. Copyright © 2018 John Wiley & Sons, Ltd.

Micropatterns of Matrigel for three-dimensional epithelial cultures.

PubMed

Sodunke, Temitope R; Turner, Keneshia K; Caldwell, Sarah A; McBride, Kevin W; Reginato, Mauricio J; Noh, Hongseok Moses

2007-09-01

Three-dimensional (3D) epithelial culture models are widely used to promote a physiologically relevant microenvironment for the study of normal and aberrant epithelial organization. Despite the increased use of these models, their potential as a cell-based screening tool for therapeutics has been hindered by the lack of existing platforms for large-scale 3D cellular studies. Current 3D standard culture does not allow for single spheroid or 'acinus' analysis required for high-throughput systems. Here, we present general strategies for creating bulk micropatterns of Matrigel that can be used as a platform for 3D epithelial culture and cell-based assays at the single acinus level. Both buried and free-standing micropatterns of Matrigel were created using modified soft lithography techniques such as microtransfer molding (microTM) and dry lift-off technique. Surface modification of poly(dimethylsiloxane) (PDMS) with oxygen plasma followed by treatment with poly(2-hydroxy-ethylmethacrylate) (poly-HEMA) was sufficient to promote deformation-free release of Matrigel patterns. In addition, a novel dual-layer dry lift-off technique was developed to simultaneously generate patterns of Matrigel and poly-HEMA on a single substrate. We also demonstrate that the micropatterned Matrigel can support 3D culture originating from a single normal human mammary epithelial (MCF-10A) cell or a human breast cancer cell (MDA-MB-231) with comparable phenotypes to standard 3D culture techniques. Culture of normal MCF-10A cells on micropatterned Matrigel resulted in formation of structures with the characteristic apoptosis of centrally located cells and formation of hollow lumens. Moreover, the carcinoma cell line showed their characteristic formation of disorganized invasive cellular clusters, lacking the normal epithelial architecture on micropatterned Matrigel. Hence, micropatterned Matrigel can be used as a 3D epithelial cell-based platform for a wide variety of applications in epithelial and cancer biology, tissue engineering, as well as gene/drug screening technology.

Visualization of tandem repeat mutagenesis in Bacillus subtilis.

PubMed

Dormeyer, Miriam; Lentes, Sabine; Ballin, Patrick; Wilkens, Markus; Klumpp, Stefan; Kohlheyer, Dietrich; Stannek, Lorena; Grünberger, Alexander; Commichau, Fabian M

2018-03-01

Mutations are crucial for the emergence and evolution of proteins with novel functions, and thus for the diversity of life. Tandem repeats (TRs) are mutational hot spots that are present in the genomes of all organisms. Understanding the molecular mechanism underlying TR mutagenesis at the level of single cells requires the development of mutation reporter systems. Here, we present a mutation reporter system that is suitable to visualize mutagenesis of TRs occurring in single cells of the Gram-positive model bacterium Bacillus subtilis using microfluidic single-cell cultivation. The system allows measuring the elimination of TR units due to growth rate recovery. The cultivation of bacteria carrying the mutation reporter system in microfluidic chambers allowed us for the first time to visualize the emergence of a specific mutation at the level of single cells. The application of the mutation reporter system in combination with microfluidics might be helpful to elucidate the molecular mechanism underlying TR (in)stability in bacteria. Moreover, the mutation reporter system might be useful to assess whether mutations occur in response to nutrient starvation. Copyright © 2018 Elsevier B.V. All rights reserved.

Development of Novel PEM Membrane and Multiphase CD Modeling of PEM Fuel Cell

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

K. J. Berry; Susanta Das

2009-12-30

To understand heat and water management phenomena better within an operational proton exchange membrane fuel cell's (PEMFC) conditions, a three-dimensional, two-phase computational fluid dynamic (CFD) flow model has been developed and simulated for a complete PEMFC. Both liquid and gas phases are considered in the model by taking into account the gas flow, diffusion, charge transfer, change of phase, electro-osmosis, and electrochemical reactions to understand the overall dynamic behaviors of species within an operating PEMFC. The CFD model is solved numerically under different parametric conditions in terms of water management issues in order to improve cell performance. The results obtainedmore » from the CFD two-phase flow model simulations show improvement in cell performance as well as water management under PEMFCs operational conditions as compared to the results of a single phase flow model available in the literature. The quantitative information obtained from the two-phase model simulation results helped to develop a CFD control algorithm for low temperature PEM fuel cell stacks which opens up a route in designing improvement of PEMFC for better operational efficiency and performance. To understand heat and water management phenomena better within an operational proton exchange membrane fuel cell's (PEMFC) conditions, a three-dimensional, two-phase computational fluid dynamic (CFD) flow model has been developed and simulated for a complete PEMFC. Both liquid and gas phases are considered in the model by taking into account the gas flow, diffusion, charge transfer, change of phase, electro-osmosis, and electrochemical reactions to understand the overall dynamic behaviors of species within an operating PEMFC. The CFD model is solved numerically under different parametric conditions in terms of water management issues in order to improve cell performance. The results obtained from the CFD two-phase flow model simulations show improvement in cell performance as well as water management under PEMFCs operational conditions as compared to the results of a single phase flow model available in the literature. The quantitative information obtained from the two-phase model simulation results helped to develop a CFD control algorithm for low temperature PEM fuel cell stacks which opens up a route in designing improvement of PEMFC for better operational efficiency and performance.« less

Modelling the growth kinetics of Kocuria marina DAGII as a function of single and binary substrate during batch production of β-Cryptoxanthin.

PubMed

Mitra, Ruchira; Chaudhuri, Surabhi; Dutta, Debjani

2017-01-01

In the present investigation, growth kinetics of Kocuria marina DAGII during batch production of β-Cryptoxanthin (β-CRX) was studied by considering the effect of glucose and maltose as a single and binary substrate. The importance of mixed substrate over single substrate has been emphasised in the present study. Different mathematical models namely, the Logistic model for cell growth, the Logistic mass balance equation for substrate consumption and the Luedeking-Piret model for β-CRX production were successfully implemented. Model-based analyses for the single substrate experiments suggested that the concentrations of glucose and maltose higher than 7.5 and 10.0 g/L, respectively, inhibited the growth and β-CRX production by K. marina DAGII. The Han and Levenspiel model and the Luong product inhibition model accurately described the cell growth in glucose and maltose substrate systems with a R 2 value of 0.9989 and 0.9998, respectively. The effect of glucose and maltose as binary substrate was further investigated. The binary substrate kinetics was well described using the sum-kinetics with interaction parameters model. The results of production kinetics revealed that the presence of binary substrate in the cultivation medium increased the biomass and β-CRX yield significantly. This study is a first time detailed investigation on kinetic behaviours of K. marina DAGII during β-CRX production. The parameters obtained in the study might be helpful for developing strategies for commercial production of β-CRX by K. marina DAGII.

Cell size control and homeostasis in bacteria

NASA Astrophysics Data System (ADS)

Bradde, Serena; Taheri, Sattar; Sauls, John; Hill, Nobert; Levine, Petra; Paulsson, Johan; Vergassola, Massimo; Jun, Suckjoon

2015-03-01

How cells control their size is a fundamental question in biology. The mechanisms for sensing size, time, or a combination of the two are not supported by experimental evidence. By analysing distributions of size at division at birth and generation time of hundreds of thousands of Gram-negative E. coli and Gram-positive B. subtilis cells under a wide range of tightly controlled steady-state growth conditions, we are now in the position to validate different theoretical models. In this talk I will present all possible models in details and present a general mechanism that quantitatively explains all measurable aspects of growth and cell division at both population and single-cell levels.

Modeling Bacteria Surface Acid-Base Properties: The Overprint Of Biology

NASA Astrophysics Data System (ADS)

Amores, D. R.; Smith, S.; Warren, L. A.

2009-05-01

Bacteria are ubiquitous in the environment and are important repositories for metals as well as nucleation templates for a myriad of secondary minerals due to an abundance of reactive surface binding sites. Model elucidation of whole cell surface reactivity simplifies bacteria as viable but static, i.e., no metabolic activity, to enable fits of microbial data sets from models derived from mineral surfaces. Here we investigate the surface proton charging behavior of live and dead whole cell cyanobacteria (Synechococcus sp.) harvested from a single parent culture by acid-base titration using a Fully Optimized ContinUouS (FOCUS) pKa spectrum method. Viability of live cells was verified by successful recultivation post experimentation, whereas dead cells were consistently non-recultivable. Surface site identities derived from binding constants determined for both the live and dead cells are consistent with molecular analogs for organic functional groups known to occur on microbial surfaces: carboxylic (pKa = 2.87-3.11), phosphoryl (pKa = 6.01-6.92) and amine/hydroxyl groups (pKa = 9.56-9.99). However, variability in total ligand concentration among the live cells is greater than those between the live and dead. The total ligand concentrations (LT, mol- mg-1 dry solid) derived from the live cell titrations (n=12) clustered into two sub-populations: high (LT = 24.4) and low (LT = 5.8), compared to the single concentration for the dead cell titrations (LT = 18.8; n=5). We infer from these results that metabolic activity can substantively impact surface reactivity of morphologically identical cells. These results and their modeling implications for bacteria surface reactivities will be discussed.

BH3-mimetic small molecule inhibits the growth and recurrence of adenoid cystic carcinoma

PubMed Central

Acasigua, Gerson A.; Warner, Kristy A.; Nör, Felipe; Helman, Joseph; Pearson, Alexander T.; Fossati, Anna C.; Wang, Shaomeng; Nör, Jacques E.

2015-01-01

Objectives To evaluate the anti-tumor effect of BM-1197, a new potent and highly specific small molecule inhibitor of Bcl-2/Bcl-xL, in preclinical models of human adenoid cystic carcinoma (ACC). Methods Low passage primary human adenoid cystic carcinoma cells (UM-HACC-2A,-2B,-5,-6) and patient-derived xenograft (PDX) models (UM-PDX-HACC) were developed from surgical specimens obtained from 4 patients. The effect of BM-1197 on cell viability and cell cycle were evaluated in vitro using this panel of low passage ACC cells. The effect of BM-1197 on tumor growth, recurrence and tumor cell apoptosis in vivo was evaluated with the PDX model of ACC (UM-PDX-HACC-5). Results Exposure of low passage primary human ACC cells to BM-1197 mediated an IC50 of 0.92-2.82 μM. This correlated with an increase in the fraction of apoptotic cells (p<0.0001) and an increase in caspase-3 activity (p<0.0001), but no noticeable differences in cell cycle (p>0.05). In vivo, BM-1197 inhibited tumor growth (p=0.0256) and induced tumor cell apoptosis (p=0.0165) without causing significant systemic toxicities, as determined by mouse weight over time. Surprisingly, weekly BM-1197 decreased the incidence of tumor recurrence (p=0.0297), as determined by Kaplan-Meier analysis. Conclusion These data demonstrated that single agent BM-1197 induces apoptosis and inhibits tumor growth in preclinical models of adenoid cystic carcinoma. Notably, single agent BM-1197 inhibited tumor recurrence, which is considered a major clinical challenge in the clinical management of adenoid cystic carcinoma. Collectively, these results suggest that patients with adenoid cystic carcinoma might benefit from therapy with a BH3-mimetic small molecule. PMID:26121939

Electrical excitability: a spectrum of properties in the progeny of a single embryonic neuroblast.

PubMed Central

Goodman, C S; Pearson, K G; Spitzer, N C

1980-01-01

We have examined the range of some properties of the progeny of a single embryonic precursor cell in the grasshopper. The approximately 100 progeny of this single neuroblast share certain features such as their transmitter and some aspects of their morphology; at the same time, however, they demonstrate a broad spectrum of electrical properties, from spiking to non-spiking neurons. The first-born progeny are spiking neurons with peripheral axons. Many of the progeny, including all of the last-born, do not generate action potentials. The nonspiking progeny are local intraganglionic neurons and appear to compose a major proportion of the progeny of this neuroblast. All of the nonspiking neurons have calcium inward current channels and can make action potentials when outward current channels are blocked. We propose a model for grasshopper neurogenesis based on cell lineage such that (i) certain features (e.g., transmitter) are shared by the progeny of all cell divisions from a single neuroblast, and (ii) other features (e.g., electrical properties) are shared by the progeny of a given birth position (e.g., first versus last born) from all of the neuroblasts. According to this model, the first-born progeny from all neuroblasts are spiking neurons, whereas the last-born are nonspiking. Images PMID:6246499

Multiscale Modeling of Angiogenesis and Predictive Capacity

NASA Astrophysics Data System (ADS)

Pillay, Samara; Byrne, Helen; Maini, Philip

Tumors induce the growth of new blood vessels from existing vasculature through angiogenesis. Using an agent-based approach, we model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death-like processes. We use the transition probabilities associated with the discrete model and a discrete conservation equation for cell occupancy to determine collective cell behavior, in terms of partial differential equations (PDEs). We derive three PDE models incorporating single, multi-species and no volume exclusion. By fitting the parameters in our PDE models and other well-established continuum models to agent-based simulations during a specific time period, and then comparing the outputs from the PDE models and agent-based model at later times, we aim to determine how well the PDE models predict the future behavior of the agent-based model. We also determine whether predictions differ across PDE models and the significance of those differences. This may impact drug development strategies based on PDE models.

Polycistronic lentiviral vector for "hit and run" reprogramming of adult skin fibroblasts to induced pluripotent stem cells.

PubMed

Chang, Chia-Wei; Lai, Yi-Shin; Pawlik, Kevin M; Liu, Kaimao; Sun, Chiao-Wang; Li, Chao; Schoeb, Trenton R; Townes, Tim M

2009-05-01

We report the derivation of induced pluripotent stem (iPS) cells from adult skin fibroblasts using a single, polycistronic lentiviral vector encoding the reprogramming factors Oct4, Sox2, and Klf4. Porcine teschovirus-1 2A sequences that trigger ribosome skipping were inserted between human cDNAs for these factors, and the polycistron was subcloned downstream of the elongation factor 1 alpha promoter in a self-inactivating (SIN) lentiviral vector containing a loxP site in the truncated 3' long terminal repeat (LTR). Adult skin fibroblasts from a humanized mouse model of sickle cell disease were transduced with this single lentiviral vector, and iPS cell colonies were picked within 30 days. These cells expressed endogenous Oct4, Sox2, Nanog, alkaline phosphatase, stage-specific embryonic antigen-1, and other markers of pluripotency. The iPS cells produced teratomas containing tissue derived from all three germ layers after injection into immunocompromised mice and formed high-level chimeras after injection into murine blastocysts. iPS cell lines with as few as three lentiviral insertions were obtained. Expression of Cre recombinase in these iPS cells resulted in deletion of the lentiviral vector, and sequencing of insertion sites demonstrated that remnant 291-bp SIN LTRs containing a single loxP site did not interrupt coding sequences, promoters, or known regulatory elements. These results suggest that a single, polycistronic "hit and run" vector can safely and effectively reprogram adult dermal fibroblasts into iPS cells.

Quantifying Hydrostatic Pressure in Plant Cells by Using Indentation with an Atomic Force Microscope

PubMed Central

Beauzamy, Léna; Derr, Julien; Boudaoud, Arezki

2015-01-01

Plant cell growth depends on a delicate balance between an inner drive—the hydrostatic pressure known as turgor—and an outer restraint—the polymeric wall that surrounds a cell. The classical technique to measure turgor in a single cell, the pressure probe, is intrusive and cannot be applied to small cells. In order to overcome these limitations, we developed a method that combines quantification of topography, nanoindentation force measurements, and an interpretation using a published mechanical model for the pointlike loading of thin elastic shells. We used atomic force microscopy to estimate the elastic properties of the cell wall and turgor pressure from a single force-depth curve. We applied this method to onion epidermal peels and quantified the response to changes in osmolality of the bathing solution. Overall our approach is accessible and enables a straightforward estimation of the hydrostatic pressure inside a walled cell. PMID:25992723

Anesthetic action of volatile anesthetics by using Paramecium as a model.

PubMed

Zhou, Miaomiao; Xia, Huimin; Xu, Younian; Xin, Naixing; Liu, Jiao; Zhang, Shihai

2012-06-01

Although empirically well understood in their clinical administration, volatile anesthetics are not yet well comprehended in their mechanism studies. A major conundrum emerging from these studies is that there is no validated model to assess the presumed candidate sites of the anesthetics. We undertook this study to test the hypothesis that the single-celled Paramecium could be anesthetized and served as a model organism in the study of anesthetics. We assessed the motion of Paramecium cells with Expert Vision system and the chemoresponse of Paramecium cells with T-maze assays in the presence of four different volatile anesthetics, including isoflurane, sevoflurane, enflurane and ether. Each of those volatiles was dissolved in buffers to give drug concentrations equal to 0.8, 1.0, and 1.2 EC50, respectively, in clinical practice. We could see that after application of volatile anesthetics, the swimming of the Paramecium cells was accelerated and then suppressed, or even stopped eventually, and the index of the chemoresponse of the Paramecium cells (denoted as I ( che )) was decreased. All of the above impacts were found in a concentration-dependent fashion. The biphasic effects of the clinical concentrations of volatile anesthetics on Paramecium simulated the situation of high species in anesthesia, and the inhibition of the chemoresponse also indicated anesthetized. In conclusion, the findings in our studies suggested that the single-celled Paramecium could be anesthetized with clinical concentrations of volatile anesthetics and therefore be utilized as a model organism to study the mechanisms of volatile anesthetics.

RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and Three Dimensions.

PubMed

Fu, Jiaqi; Fernandez, Daniel; Ferrer, Marc; Titus, Steven A; Buehler, Eugen; Lal-Nag, Madhu A

2017-06-01

The widespread use of two-dimensional (2D) monolayer cultures for high-throughput screening (HTS) to identify targets in drug discovery has led to attrition in the number of drug targets being validated. Solid tumors are complex, aberrantly growing microenvironments that harness structural components from stroma, nutrients fed through vasculature, and immunosuppressive factors. Increasing evidence of stromally-derived signaling broadens the complexity of our understanding of the tumor microenvironment while stressing the importance of developing better models that reflect these interactions. Three-dimensional (3D) models may be more sensitive to certain gene-silencing events than 2D models because of their components of hypoxia, nutrient gradients, and increased dependence on cell-cell interactions and therefore are more representative of in vivo interactions. Colorectal cancer (CRC) and breast cancer (BC) models composed of epithelial cells only, deemed single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS), containing fibroblasts were developed for RNAi HTS in 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening. We describe the development of a high-throughput assay platform that can assess physiologically relevant phenotypic differences between screening 2D versus 3D SCTS, 3D SCTS, and MCTS in the context of different cancer subtypes. This assay platform represents a paradigm shift in how we approach drug discovery that can reduce the attrition rate of drugs that enter the clinic.

Determination of EGFR mutations in single cells microdissected from enriched lung tumor cells in peripheral blood.

PubMed

Ran, Ran; Li, Longyun; Wang, Mengzhao; Wang, Shulan; Zheng, Zhi; Lin, Peter Ping

2013-09-01

A minimally invasive and repeatable approach for real-time epidermal growth factor receptor (EGFR) mutation surveillance would be highly beneficial for individualized therapy of late stage lung cancer patients whose surgical specimens are often not available. We aim to develop a viable method to detect EGFR mutations in single circulating tumor cells (CTCs). Using a model CTC system of spiked tumor cells in whole blood, we evaluated EGFR mutation determination in single tumor cells enriched from blood. We used magnetic beads labeled with antibody against leukocyte surface antigens to deplete leukocytes and enrich native CTCs independent of epithelial marker expression level. We then used laser cell microdissection (LCM) to isolate individual CTCs, followed by whole-genome amplification of the DNA for exon 19 microdeletion, L858R and T790M mutation detection by PCR sequencing. EGFR mutations were successfully measured in individual spiked tumor cells enriched from 7.5 ml whole blood. Whole-genome amplification provided sufficient DNA for mutation determination at multiple sites. Ninety-five percent of the single CTCs microdissected by LCM (19/20) yielded PCR amplicons for at least one of the three mutation sites. The amplification success rates were 55 % (11/20) for exon 19 deletion, 45 % (9/20) for T790M, and 85 % (17/20) for L858R. Sequencing of the amplicons showed allele dropout in the amplification reactions, but mutations were correctly identified in 80 % of the amplicons. EGFR mutation determination from single captured tumor cells from blood is feasible with the approach described here. However, to overcome allele dropout and to obtain reliable information about the tumor's EGFR status, multiple individual tumor cells should be assayed.

Heavy ion action on single cells: Cellular inactivation capability of single accelerated heavy ions

NASA Technical Reports Server (NTRS)

Kost, M.; Pross, H.-D.; Russmann, C.; Schneider, E.; Kiefer, J.; Kraft, G.; Lenz, G.; Becher, W.

1994-01-01

Heavy ions (HZE-particles) constitute an important part of radiation in space. Although their number is small the high amount of energy transferred by individual particles may cause severe biological effects. Their investigation requires special techniques which were tested by experiments performed at the UNILAC at the GSI (Darmstadt). Diploid yeast was used which is a suitable eucaryotic test system because of its resistance to extreme conditions like dryness and vacuum. Cells were placed on nuclear track detector foils and exposed to ions of different atomic number and energy. To assess the action of one single ion on an individual cell, track parameters and the respective colony forming abilities (CFA) were determined with the help of computer aided image analysis. There is mounting evidence that not only the amount of energy deposited along the particle path, commonly given by the LET, is of importance but also the spatial problem of energy deposition at a submicroscopical scale. It is virtually impossible to investigate track structure effects in detail with whole cell populations and (globally applied) high particle fluences. It is, therefore, necessary to detect the action of simple ions in individual cells. The results show that the biological action depends on atomic number and specific energy of the impinging ions, which can be compared with model calculations of recent track structure models.

Stochasticity in the signalling network of a model microbe

NASA Astrophysics Data System (ADS)

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

2007-03-01

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

Single Cell Assay for Analyzing Single Cell Exosome and Endocrine Secretion and Cancer Markers

NASA Astrophysics Data System (ADS)

Chiu, Yu-Jui

To understand the inhomogeneity of cells in biological systems, there is a growing demand for the capability to characterize the properties of individual single cells. Since single cell studies require continuous monitoring of the cell behaviors instead of a snapshot test at a single time point, an effective single-cell assay that can support time lapsed studies in a high throughput manner is desired. Most currently available single-cell technologies cannot provide proper environments to sustain cell growth and cannot provide, for appropriate cell types, proliferation of single cells and convenient, non-invasive tests of single cell behaviors from molecular markers. In this dissertation, I present a highly versatile single-cell assay that can accommodate different cellular types, enable easy and efficient single cell loading and culturing, and be suitable for the study of effects of in-vitro environmental factors in combination with drug screening. The salient features of the assay are the non-invasive collection and surveying of single cell secretions at different time points and massively parallel translocation of single cells by user defined criteria, producing very high compatibility to the downstream process such as single cell qPCR and sequencing. Above all, the acquired information is quantitative -- for example, one of the studies is measured by the number of exosomes each single cell secretes for a given time period. Therefore, our single-cell assay provides a convenient, low-cost, and enabling tool for quantitative, time lapsed studies of single cell properties.

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

Just-in-time vaccines: Biomineralized calcium phosphate core-immunogen shell nanoparticles induce long-lasting CD8(+) T cell responses in mice.

PubMed

Zhou, Weibin; Moguche, Albanus O; Chiu, David; Murali-Krishna, Kaja; Baneyx, François

2014-04-01

Distributed and on-demand vaccine production could be game-changing for infectious disease treatment in the developing world by providing new therapeutic opportunities and breaking the refrigeration "cold chain". Here, we show that a fusion protein between a calcium phosphate binding domain and the model antigen ovalbumin can mineralize a biocompatible adjuvant in a single step. The resulting 50 nm calcium phosphate core-immunogen shell particles are comparable to soluble protein in inducing ovalbumin-specific antibody response and class switch recombination in mice. However, single dose vaccination with nanoparticles leads to higher expansion of ovalbumin-specific CD8(+) T cells upon challenge with an influenza virus bearing the ovalbumin-derived SIINFEKL peptide, and these cells produce high levels of IFN-γ. Furthermore, mice exhibit a robust antigen-specific CD8(+) T cell recall response when challenged with virus 8 months post-immunization. These results underscore the promise of immunogen-controlled adjuvant mineralization for just-in-time manufacturing of effective T cell vaccines. This paper reports that a fusion protein between a calcium phosphate binding domain and the model antigen ovalbumin can mineralize into a biocompatible adjuvant in a single step, enabling distributed and on-demand vaccine production and eliminating the need for refrigeration of vaccines. The findings highlight the possibility of immunogen-controlled adjuvant mineralization for just-in-time manufacturing of effective T cell vaccines. Copyright © 2014 Elsevier Inc. All rights reserved.

A three-dimensional human neural cell culture model of Alzheimer's disease.

PubMed

Choi, Se Hoon; Kim, Young Hye; Hebisch, Matthias; Sliwinski, Christopher; Lee, Seungkyu; D'Avanzo, Carla; Chen, Hechao; Hooli, Basavaraj; Asselin, Caroline; Muffat, Julien; Klee, Justin B; Zhang, Can; Wainger, Brian J; Peitz, Michael; Kovacs, Dora M; Woolf, Clifford J; Wagner, Steven L; Tanzi, Rudolph E; Kim, Doo Yeon

2014-11-13

Alzheimer's disease is the most common form of dementia, characterized by two pathological hallmarks: amyloid-β plaques and neurofibrillary tangles. The amyloid hypothesis of Alzheimer's disease posits that the excessive accumulation of amyloid-β peptide leads to neurofibrillary tangles composed of aggregated hyperphosphorylated tau. However, to date, no single disease model has serially linked these two pathological events using human neuronal cells. Mouse models with familial Alzheimer's disease (FAD) mutations exhibit amyloid-β-induced synaptic and memory deficits but they do not fully recapitulate other key pathological events of Alzheimer's disease, including distinct neurofibrillary tangle pathology. Human neurons derived from Alzheimer's disease patients have shown elevated levels of toxic amyloid-β species and phosphorylated tau but did not demonstrate amyloid-β plaques or neurofibrillary tangles. Here we report that FAD mutations in β-amyloid precursor protein and presenilin 1 are able to induce robust extracellular deposition of amyloid-β, including amyloid-β plaques, in a human neural stem-cell-derived three-dimensional (3D) culture system. More importantly, the 3D-differentiated neuronal cells expressing FAD mutations exhibited high levels of detergent-resistant, silver-positive aggregates of phosphorylated tau in the soma and neurites, as well as filamentous tau, as detected by immunoelectron microscopy. Inhibition of amyloid-β generation with β- or γ-secretase inhibitors not only decreased amyloid-β pathology, but also attenuated tauopathy. We also found that glycogen synthase kinase 3 (GSK3) regulated amyloid-β-mediated tau phosphorylation. We have successfully recapitulated amyloid-β and tau pathology in a single 3D human neural cell culture system. Our unique strategy for recapitulating Alzheimer's disease pathology in a 3D neural cell culture model should also serve to facilitate the development of more precise human neural cell models of other neurodegenerative disorders.

Quantitative analysis reveals crosstalk mechanisms of heat shock-induced attenuation of NF-κB signaling at the single cell level.

PubMed

Kardyńska, Małgorzata; Paszek, Anna; Śmieja, Jarosław; Spiller, David; Widłak, Wiesława; White, Michael R H; Paszek, Pawel; Kimmel, Marek

2018-04-01

Elevated temperature induces the heat shock (HS) response, which modulates cell proliferation, apoptosis, the immune and inflammatory responses. However, specific mechanisms linking the HS response pathways to major cellular signaling systems are not fully understood. Here we used integrated computational and experimental approaches to quantitatively analyze the crosstalk mechanisms between the HS-response and a master regulator of inflammation, cell proliferation, and apoptosis the Nuclear Factor κB (NF-κB) system. We found that populations of human osteosarcoma cells, exposed to a clinically relevant 43°C HS had an attenuated NF-κB p65 response to Tumor Necrosis Factor α (TNFα) treatment. The degree of inhibition of the NF-κB response depended on the HS exposure time. Mathematical modeling of single cells indicated that individual crosstalk mechanisms differentially encode HS-mediated NF-κB responses while being consistent with the observed population-level responses. In particular "all-or-nothing" encoding mechanisms were involved in the HS-dependent regulation of the IKK activity and IκBα phosphorylation, while others involving transport were "analogue". In order to discriminate between these mechanisms, we used live-cell imaging of nuclear translocations of the NF-κB p65 subunit. The single cell responses exhibited "all-or-nothing" encoding. While most cells did not respond to TNFα stimulation after a 60 min HS, 27% showed responses similar to those not receiving HS. We further demonstrated experimentally and theoretically that the predicted inhibition of IKK activity was consistent with the observed HS-dependent depletion of the IKKα and IKKβ subunits in whole cell lysates. However, a combination of "all-or-nothing" crosstalk mechanisms was required to completely recapitulate the single cell data. We postulate therefore that the heterogeneity of the single cell responses might be explained by the cell-intrinsic variability of HS-modulated IKK signaling. In summary, we show that high temperature modulates NF-κB responses in single cells in a complex and unintuitive manner, which needs to be considered in hyperthermia-based treatment strategies.

Imaging Transcriptional Regulation of Eukaryotic mRNA Genes: Advances and Outlook.

PubMed

Yao, Jie

2017-01-06

Regulation of eukaryotic transcription in vivo occurs at distinct stages. Previous research has identified many active or repressive transcription factors (TFs) and core transcription components and studied their functions in vitro and in vivo. Nonetheless, how individual TFs act in concert to regulate mRNA gene expression in a single cell remains poorly understood. Direct observation of TF assembly and disassembly and various biochemical reactions during transcription of a single-copy gene in vivo is the ideal approach to study this problem. Research in this area requires developing novel techniques for single-cell transcription imaging and integrating imaging studies into understanding the molecular biology of transcription. In the past decade, advanced cell imaging has enabled unprecedented capabilities to visualize individual TF molecules, to track single transcription sites, and to detect individual mRNA in fixed and living cells. These studies have raised several novel insights on transcriptional regulation such as the "hit-and-run" model and transcription bursting that could not be obtained by in vitro biochemistry analysis. At this point, the key question is how to achieve deeper understandings or discover novel mechanisms of eukaryotic transcriptional regulation by imaging transcription in single cells. Meanwhile, further technical advancements are likely required for visualizing distinct kinetic steps of transcription on a single-copy gene in vivo. This review article summarizes recent progress in the field and describes the challenges and opportunities ahead. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Effective Targeting of Multiple B-Cell Maturation Antigen-Expressing Hematological Malignances by Anti-B-Cell Maturation Antigen Chimeric Antigen Receptor T Cells.

PubMed

Friedman, Kevin M; Garrett, Tracy E; Evans, John W; Horton, Holly M; Latimer, Howard J; Seidel, Stacie L; Horvath, Christopher J; Morgan, Richard A

2018-05-01

B-cell maturation antigen (BCMA) expression has been proposed as a marker for the identification of malignant plasma cells in patients with multiple myeloma (MM). Nearly all MM tumor cells express BCMA, while normal tissue expression is restricted to plasma cells and a subset of mature B cells. Consistent BCMA expression was confirmed on MM biopsies (29/29 BCMA+), and it was further demonstrated that BCMA is expressed in a substantial number of lymphoma samples, as well as primary chronic lymphocytic leukemia B cells. To target BCMA using redirected autologous T cells, lentiviral vectors (LVV) encoding chimeric antigen receptors (CARs) were constructed with four unique anti-BCMA single-chain variable fragments, fused to the CD137 (4-1BB) co-stimulatory and CD3ζ signaling domains. One LVV, BB2121, was studied in detail, and BB2121 CAR-transduced T cells (bb2121) exhibited a high frequency of CAR + T cells and robust in vitro activity against MM cell lines, lymphoma cell lines, and primary chronic lymphocytic leukemia peripheral blood. Based on receptor quantification, bb2121 recognized tumor cells expressing as little as 222 BCMA molecules per cell. The in vivo pharmacology of anti-BCMA CAR T cells was studied in NSG mouse models of human MM, Burkitt lymphoma, and mantle cell lymphoma, where mice received a single intravenous administration of vehicle, control vector-transduced T cells, or anti-BCMA CAR-transduced T cells. In all models, the vehicle and control CAR T cells failed to inhibit tumor growth. In contrast, treatment with bb2121 resulted in rapid and sustained elimination of the tumors and 100% survival in all treatment models. Together, these data support the further development of anti-BCMA CAR T cells as a potential treatment for not only MM but also some lymphomas.

Multiscale modelling of Flow-Induced Blood Cell Damage

NASA Astrophysics Data System (ADS)

Liu, Yaling; Sohrabi, Salman

2017-11-01

We study red blood cell (RBC) damage and hemolysis at cellular level. Under high shear rates, pores form on RBC membranes through which hemoglobin (Hb) leaks out and increases free Hb content of plasma leading to hemolysis. By coupling lattice Boltzmann and spring connected network models through immersed boundary method, we estimate hemolysis of a single RBC under various shear rates. The developed cellular damage model can be used as a predictive tool for hydrodynamic and hematologic design optimization of blood-wetting medical devices.

Multi-level characterization of balanced inhibitory-excitatory cortical neuron network derived from human pluripotent stem cells.

PubMed

Nadadhur, Aishwarya G; Emperador Melero, Javier; Meijer, Marieke; Schut, Desiree; Jacobs, Gerbren; Li, Ka Wan; Hjorth, J J Johannes; Meredith, Rhiannon M; Toonen, Ruud F; Van Kesteren, Ronald E; Smit, August B; Verhage, Matthijs; Heine, Vivi M

2017-01-01

Generation of neuronal cultures from induced pluripotent stem cells (hiPSCs) serve the studies of human brain disorders. However we lack neuronal networks with balanced excitatory-inhibitory activities, which are suitable for single cell analysis. We generated low-density networks of hPSC-derived GABAergic and glutamatergic cortical neurons. We used two different co-culture models with astrocytes. We show that these cultures have balanced excitatory-inhibitory synaptic identities using confocal microscopy, electrophysiological recordings, calcium imaging and mRNA analysis. These simple and robust protocols offer the opportunity for single-cell to multi-level analysis of patient hiPSC-derived cortical excitatory-inhibitory networks; thereby creating advanced tools to study disease mechanisms underlying neurodevelopmental disorders.

TLM-Tracker: software for cell segmentation, tracking and lineage analysis in time-lapse microscopy movies.

PubMed

Klein, Johannes; Leupold, Stefan; Biegler, Ilona; Biedendieck, Rebekka; Münch, Richard; Jahn, Dieter

2012-09-01

Time-lapse imaging in combination with fluorescence microscopy techniques enable the investigation of gene regulatory circuits and uncovered phenomena like culture heterogeneity. In this context, computational image processing for the analysis of single cell behaviour plays an increasing role in systems biology and mathematical modelling approaches. Consequently, we developed a software package with graphical user interface for the analysis of single bacterial cell behaviour. A new software called TLM-Tracker allows for the flexible and user-friendly interpretation for the segmentation, tracking and lineage analysis of microbial cells in time-lapse movies. The software package, including manual, tutorial video and examples, is available as Matlab code or executable binaries at http://www.tlmtracker.tu-bs.de.

Emergence of tissue mechanics from cellular processes: shaping a fly wing

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Etournay, Raphael; Popovic, Marko; Nandi, Amitabha; Brandl, Holger; Salbreux, Guillaume; Eaton, Suzanne; Jülicher, Frank

Nowadays, biologistsare able to image biological tissueswith up to 10,000 cells in vivowhere the behavior of each individual cell can be followed in detail.However, how precisely large-scale tissue deformation and stresses emerge from cellular behavior remains elusive. Here, we study this question in the developing wing of the fruit fly. To this end, we first establish a geometrical framework that exactly decomposes tissue deformation into contributions by different kinds of cellular processes. These processes comprise cell shape changes, cell neighbor exchanges, cell divisions, and cell extrusions. As the key idea, we introduce a tiling of the cellular network into triangles. This approach also reveals that tissue deformation can also be created by correlated cellular motion. Based on quantifications using these concepts, we developed a novel continuum mechanical model for the fly wing. In particular, our model includes active anisotropic stresses and a delay in the response of cell rearrangements to material stresses. A different approach to study the emergence of tissue mechanics from cellular behavior are cell-based models. We characterize the properties of a cell-based model for 3D tissues that is a hybrid between single particle models and the so-called vertex models.

Progressive mechanical indentation of large-format Li-ion cells

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

Wang, Hsin; Kumar, Abhishek; Simunovic, Srdjan

We used large format Li-ion cells to study the mechanical responses of single cells of thickness 6.5 mm and stacks of three cells under compressive loading. We carried out various sequences of increasing depth indentations using a 1.0 inch (25.4 mm) diameter steel ball with steel plate as a rigid support surface. The indentation depths were between 0.025 and 0.250 with main indentation increments tests of 0.025 steps. Increment steps of 0.100 and 0.005 were used to pinpoint the onset of internal-short that occurred between 0.245 and 0.250 . The indented cells were disassembled and inspected for internal damage. Loadmore » vs. time curves were compared with the developed computer models. Separator thinning leading to the short circuit was simulated using both isotropic and anisotropic mechanical properties. This study show that separators behave differently when tested as a single layer vs. a stack in a typical pouch cell. The collective responses of the multiple layers must be taken into account in failure analysis. A model that resolves the details of the individual internal cell components was able to simulate the internal deformation of the large format cells and the onset of failure assumed to coincide with the onset of internal short circuit.« less

Progressive mechanical indentation of large-format Li-ion cells

NASA Astrophysics Data System (ADS)

Wang, Hsin; Kumar, Abhishek; Simunovic, Srdjan; Allu, Srikanth; Kalnaus, Sergiy; Turner, John A.; Helmers, Jacob C.; Rules, Evan T.; Winchester, Clinton S.; Gorney, Philip

2017-02-01

Large format Li-ion cells were used to study the mechanical responses of single cells of thickness 6.5 mm and stacks of three cells under compressive loading. Various sequences of increasing depth indentations were carried out using a 1.0 inch (25.4 mm) diameter steel ball with steel plate as a rigid support surface. The indentation depths were between 0.025″ and 0.250″ with main indentation increments tests of 0.025″ steps. Increment steps of 0.100″ and 0.005″ were used to pinpoint the onset of internal-short that occurred between 0.245″ and 0.250″. The indented cells were disassembled and inspected for internal damage. Load vs. time curves were compared with the developed computer models. Separator thinning leading to the short circuit was simulated using both isotropic and anisotropic mechanical properties. Our study show that separators behave differently when tested as a single layer vs. a stack in a typical pouch cell. The collective responses of the multiple layers must be taken into account in failure analysis. A model that resolves the details of the individual internal cell components was able to simulate the internal deformation of the large format cells and the onset of failure assumed to coincide with the onset of internal short circuit.

Progressive mechanical indentation of large-format Li-ion cells

DOE PAGES

Wang, Hsin; Kumar, Abhishek; Simunovic, Srdjan; ...

2016-12-07

We used large format Li-ion cells to study the mechanical responses of single cells of thickness 6.5 mm and stacks of three cells under compressive loading. We carried out various sequences of increasing depth indentations using a 1.0 inch (25.4 mm) diameter steel ball with steel plate as a rigid support surface. The indentation depths were between 0.025 and 0.250 with main indentation increments tests of 0.025 steps. Increment steps of 0.100 and 0.005 were used to pinpoint the onset of internal-short that occurred between 0.245 and 0.250 . The indented cells were disassembled and inspected for internal damage. Loadmore » vs. time curves were compared with the developed computer models. Separator thinning leading to the short circuit was simulated using both isotropic and anisotropic mechanical properties. This study show that separators behave differently when tested as a single layer vs. a stack in a typical pouch cell. The collective responses of the multiple layers must be taken into account in failure analysis. A model that resolves the details of the individual internal cell components was able to simulate the internal deformation of the large format cells and the onset of failure assumed to coincide with the onset of internal short circuit.« less

Clonal evolution in breast cancer revealed by single nucleus genome sequencing.

PubMed

Wang, Yong; Waters, Jill; Leung, Marco L; Unruh, Anna; Roh, Whijae; Shi, Xiuqing; Chen, Ken; Scheet, Paul; Vattathil, Selina; Liang, Han; Multani, Asha; Zhang, Hong; Zhao, Rui; Michor, Franziska; Meric-Bernstam, Funda; Navin, Nicholas E

2014-08-14

Sequencing studies of breast tumour cohorts have identified many prevalent mutations, but provide limited insight into the genomic diversity within tumours. Here we developed a whole-genome and exome single cell sequencing approach called nuc-seq that uses G2/M nuclei to achieve 91% mean coverage breadth. We applied this method to sequence single normal and tumour nuclei from an oestrogen-receptor-positive (ER(+)) breast cancer and a triple-negative ductal carcinoma. In parallel, we performed single nuclei copy number profiling. Our data show that aneuploid rearrangements occurred early in tumour evolution and remained highly stable as the tumour masses clonally expanded. In contrast, point mutations evolved gradually, generating extensive clonal diversity. Using targeted single-molecule sequencing, many of the diverse mutations were shown to occur at low frequencies (<10%) in the tumour mass. Using mathematical modelling we found that the triple-negative tumour cells had an increased mutation rate (13.3×), whereas the ER(+) tumour cells did not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer.

Indium Gallium Nitride Multijunction Solar Cell Simulation Using Silvaco Atlas

DTIC Science & Technology

2007-06-01

models is of great interest in space applications. By increasing the efficiency of photovoltaics, the number of solar panels is decreased. Therefore...obtained in single-junction solar cells by using Gallium Arsenide. Monocrystalline Gallium Arsenide has a maximum efficiency of approximately 25.1% [10

Chondrocyte Deformations as a Function of Tibiofemoral Joint Loading Predicted by a Generalized High-Throughput Pipeline of Multi-Scale Simulations

PubMed Central

Sibole, Scott C.; Erdemir, Ahmet

2012-01-01

Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method’s generalized nature also allows for substitution of any macro-scale and/or micro-scale model providing application for other multi-scale continuum mechanics problems. PMID:22649535

Exploiting the superior protein resistance of polymer brushes to control single cell adhesion and polarisation at the micron scale

PubMed Central

Gautrot, Julien E.; Trappmann, Britta; Oceguera-Yanez, Fabian; Connelly, John; He, Ximin; Watt, Fiona M.; Huck, Wilhelm T.S.

2010-01-01

The control of the cell microenvironment on model patterned substrates allows the systematic study of cell biology in well defined conditions, potentially using automated systems. The extreme protein resistance of poly(oligo(ethylene glycol methacrylate)) (POEGMA) brushes is exploited to achieve high fidelity patterning of single cells. These coatings can be patterned by soft lithography on large areas (a microscope slide) and scale (substrates were typically prepared in batches of 200). The present protocol relies on the adsorption of extra-cellular matrix (ECM) proteins on unprotected areas using simple incubation and washing steps. The stability of POEGMA brushes, as examined via ellipsometry and SPR, is found to be excellent, both during storage and cell culture. The impact of substrate treatment, brush thickness and incubation protocol on ECM deposition, both for ultra-thin gold and glass substrates, is investigated via fluorescence microscopy and AFM. Optimised conditions result in high quality ECM patterns at the micron scale, even on glass substrates, that are suitable for controlling cell spreading and polarisation. These patterns are compatible with state-of-the-art technologies (fluorescence microscopy, FRET) used for live cell imaging. This technology, combined with single cell analysis methods, provides a platform for exploring the mechanisms that regulate cell behaviour. PMID:20347135

Nascent RNA kinetics: Transient and steady state behavior of models of transcription

NASA Astrophysics Data System (ADS)

Choubey, Sandeep

2018-02-01

Regulation of transcription is a vital process in cells, but mechanistic details of this regulation still remain elusive. The dominant approach to unravel the dynamics of transcriptional regulation is to first develop mathematical models of transcription and then experimentally test the predictions these models make for the distribution of mRNA and protein molecules at the individual cell level. However, these measurements are affected by a multitude of downstream processes which make it difficult to interpret the measurements. Recent experimental advancements allow for counting the nascent mRNA number of a gene as a function of time at the single-inglr cell level. These measurements closely reflect the dynamics of transcription. In this paper, we consider a general mechanism of transcription with stochastic initiation and deterministic elongation and probe its impact on the temporal behavior of nascent RNA levels. Using techniques from queueing theory, we derive exact analytical expressions for the mean and variance of the nascent RNA distribution as functions of time. We apply these analytical results to obtain the mean and variance of nascent RNA distribution for specific models of transcription. These models of initiation exhibit qualitatively distinct transient behaviors for both the mean and variance which further allows us to discriminate between them. Stochastic simulations confirm these results. Overall the analytical results presented here provide the necessary tools to connect mechanisms of transcription initiation to single-cell measurements of nascent RNA.

Embedded silver PDMS electrodes for single cell electrical impedance spectroscopy

NASA Astrophysics Data System (ADS)

Wei, Yuan; Xu, Zhensong; Cachia, Mark A.; Nguyen, John; Zheng, Yi; Wang, Chen; Sun, Yu

2016-09-01

This paper presents a microfluidic device with wide channels and embedded AgPDMS electrodes for measuring the electrical properties of single cells. The work demonstrates the feasibility of using a large channel design and embedded electrodes for impedance spectroscopy to circumvent issues such as channel clogging and limited device re-usability. AgPDMS electrodes were formed on channel sidewalls for impedance detection and cell electrical properties measurement. Equivalent circuit models were used to interpret multi-frequency impedance data to quantify each cell’s cytoplasm conductivity and specific membrane capacitance. T24 cells were tested to validate the microfluidic system and modeling results. Comparisons were then made by measuring two leukemia cell lines (AML-2 and HL-60) which were found to have different cytoplasm conductivity values (0.29  ±  0.15 S m-1 versus 0.47  ±  0.20 S m-1) and specific membrane capacitance values (41  ±  25 mF m-2 versus 55  ±  26 mF m-2) when the cells were flown through the wide channel and measured by the AgPDMS electrodes.

Bone marrow stem and progenitor cell contribution to neovasculogenesis is dependent on model system with SDF-1 as a permissive trigger

PubMed Central

Madlambayan, Gerard J.; Butler, Jason M.; Hosaka, Koji; Jorgensen, Marda; Fu, Dongtao; Guthrie, Steven M.; Shenoy, Anitha K.; Brank, Adam; Russell, Kathryn J.; Otero, Jaclyn; Siemann, Dietmar W.

2009-01-01

Adult bone marrow (BM) contributes to neovascularization in some but not all settings, and reasons for these discordant results have remained unexplored. We conducted novel comparative studies in which multiple neovascularization models were established in single mice to reduce variations in experimental methodology. In different combinations, BM contribution was detected in ischemic retinas and, to a lesser extent, Lewis lung carcinoma cells, whereas B16 melanomas showed little to no BM contribution. Using this spectrum of BM contribution, we demonstrate the necessity for site-specific expression of stromal-derived factor-1α (SDF-1α) and its mobilizing effects on BM. Blocking SDF-1α activity with neutralizing antibodies abrogated BM-derived neovascularization in lung cancer and retinopathy. Furthermore, secondary transplantation of single hematopoietic stem cells (HSCs) showed that HSCs are a long-term source of neovasculogenesis and that CD133+CXCR4+ myeloid progenitor cells directly participate in new blood vessel formation in response to SDF-1α. The varied BM contribution seen in different model systems is suggestive of redundant mechanisms governing postnatal neovasculogenesis and provides an explanation for contradictory results observed in the field. PMID:19717647

An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability

PubMed Central

Schütte, Judith; Wang, Huange; Antoniou, Stella; Jarratt, Andrew; Wilson, Nicola K; Riepsaame, Joey; Calero-Nieto, Fernando J; Moignard, Victoria; Basilico, Silvia; Kinston, Sarah J; Hannah, Rebecca L; Chan, Mun Chiang; Nürnberg, Sylvia T; Ouwehand, Willem H; Bonzanni, Nicola; de Bruijn, Marella FTR; Göttgens, Berthold

2016-01-01

Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes. DOI: http://dx.doi.org/10.7554/eLife.11469.001 PMID:26901438

Improved Time-Lapsed Angular Scattering Microscopy of Single Cells

NASA Astrophysics Data System (ADS)

Cannaday, Ashley E.

By measuring angular scattering patterns from biological samples and fitting them with a Mie theory model, one can estimate the organelle size distribution within many cells. Quantitative organelle sizing of ensembles of cells using this method has been well established. Our goal is to develop the methodology to extend this approach to the single cell level, measuring the angular scattering at multiple time points and estimating the non-nuclear organelle size distribution parameters. The diameters of individual organelle-size beads were successfully extracted using scattering measurements with a minimum deflection angle of 20 degrees. However, the accuracy of size estimates can be limited by the angular range detected. In particular, simulations by our group suggest that, for cell organelle populations with a broader size distribution, the accuracy of size prediction improves substantially if the minimum angle of detection angle is 15 degrees or less. The system was therefore modified to collect scattering angles down to 10 degrees. To confirm experimentally that size predictions will become more stable when lower scattering angles are detected, initial validations were performed on individual polystyrene beads ranging in diameter from 1 to 5 microns. We found that the lower minimum angle enabled the width of this delta-function size distribution to be predicted more accurately. Scattering patterns were then acquired and analyzed from single mouse squamous cell carcinoma cells at multiple time points. The scattering patterns exhibit angular dependencies that look unlike those of any single sphere size, but are well-fit by a broad distribution of sizes, as expected. To determine the fluctuation level in the estimated size distribution due to measurement imperfections alone, formaldehyde-fixed cells were measured. Subsequent measurements on live (non-fixed) cells revealed an order of magnitude greater fluctuation in the estimated sizes compared to fixed cells. With our improved and better-understood approach to single cell angular scattering, we are now capable of reliably detecting changes in organelle size predictions due to biological causes above our measurement error of 20 nm, which enables us to apply our system to future studies of the investigation of various single cell biological processes.

A novel single-parameter approach for forecasting algal blooms.

PubMed

Xiao, Xi; He, Junyu; Huang, Haomin; Miller, Todd R; Christakos, George; Reichwaldt, Elke S; Ghadouani, Anas; Lin, Shengpan; Xu, Xinhua; Shi, Jiyan

2017-01-01

Harmful algal blooms frequently occur globally, and forecasting could constitute an essential proactive strategy for bloom control. To decrease the cost of aquatic environmental monitoring and increase the accuracy of bloom forecasting, a novel single-parameter approach combining wavelet analysis with artificial neural networks (WNN) was developed and verified based on daily online monitoring datasets of algal density in the Siling Reservoir, China and Lake Winnebago, U.S.A. Firstly, a detailed modeling process was illustrated using the forecasting of cyanobacterial cell density in the Chinese reservoir as an example. Three WNN models occupying various prediction time intervals were optimized through model training using an early stopped training approach. All models performed well in fitting historical data and predicting the dynamics of cyanobacterial cell density, with the best model predicting cyanobacteria density one-day ahead (r = 0.986 and mean absolute error = 0.103 × 10 4  cells mL -1 ). Secondly, the potential of this novel approach was further confirmed by the precise predictions of algal biomass dynamics measured as chl a in both study sites, demonstrating its high performance in forecasting algal blooms, including cyanobacteria as well as other blooming species. Thirdly, the WNN model was compared to current algal forecasting methods (i.e. artificial neural networks, autoregressive integrated moving average model), and was found to be more accurate. In addition, the application of this novel single-parameter approach is cost effective as it requires only a buoy-mounted fluorescent probe, which is merely a fraction (∼15%) of the cost of a typical auto-monitoring system. As such, the newly developed approach presents a promising and cost-effective tool for the future prediction and management of harmful algal blooms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cellular and molecular alterations in human epithelial cells transformed by high let radiation

NASA Astrophysics Data System (ADS)

Hei, T. K.; Piao, C. Q.; Sutter, T.; Willey, J. C.; Suzuki, K.

An understanding of the radiobiological effects of high LET radiation is essential for human risk estimation and radiation protection. In the present study, we show that a single, 30 cGy dose of 150 keV/mum ^4He ions can malignantly transform human papillomavirus immortalized human bronchial epithelial [BEP2D] cells. Transformed cells produce progressively growing tumors in nude mice. The transformation frequency by the single dose of alpha particles is estimated to be approximately 4 x 10^-7. Based on the average cross-sectional area of BEP2D cells, it can be calculated that a mean traversal of 1.4 particles per cell is sufficient to induce tumorigenic conversion of these cells 3 to 4 months post-irradiation. Tumorigenic BEP2D cells overexpress mutated p53 tumor suppressor oncoproteins in addition to the cell cycle control gene cyclin D1 and D2. This model provides an opportunity to study the cellular and molecular changes at the various stages in radiation carcinogenesis involving human cells.

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

Semianalytical computation of path lines for finite-difference models

USGS Publications Warehouse

Pollock, D.W.

1988-01-01

A semianalytical particle tracking method was developed for use with velocities generated from block-centered finite-difference ground-water flow models. Based on the assumption that each directional velocity component varies linearly within a grid cell in its own coordinate directions, the method allows an analytical expression to be obtained describing the flow path within an individual grid cell. Given the intitial position of a particle anywhere in a cell, the coordinates of any other point along its path line within the cell, and the time of travel between them, can be computed directly. For steady-state systems, the exit point for a particle entering a cell at any arbitrary location can be computed in a single step. By following the particle as it moves from cell to cell, this method can be used to trace the path of a particle through any multidimensional flow field generated from a block-centered finite-difference flow model. -Author

A fiber-reinforced-fluid model of anisotropic plant root cell growth

NASA Astrophysics Data System (ADS)

Jensen, Oliver E.; Dyson, Rosemary J.

2009-11-01

We present a theoretical model of a single cell in the expansion zone of the primary root of the plant Arabidopsis thaliana. The cell undergoes rapid elongation with approximately constant radius. Growth is driven by high internal turgor pressure causing viscous stretching of the cell wall, with embedded cellulose microfibrils providing the wall with strongly anisotropic properties. We represent the cell as a thin cylindrical fiber-reinforced viscous sheet between rigid end plates. Asymptotic reduction of the governing equations, under simple sets of assumptions about fiber and wall properties, yields variants of the traditional Lockhart equation that relates the axial cell growth rate to the internal pressure. The model provides insights into the geometric and biomechanical parameters underlying bulk quantities such as wall extensibility and shows how either dynamical changes in wall material properties or passive fibre reorientation may suppress cell elongation.

A two-scale model for correlation between B cell VDJ usage in zebrafish

NASA Astrophysics Data System (ADS)

Pan, Keyao; Deem, Michael

2011-03-01

The zebrafish (Danio rerio) is one of the model animals for study of immunology. The dynamics of the adaptive immune system in zebrafish is similar to that in higher animals. In this work, we built a two-scale model to simulate the dynamics of B cells in primary and secondary immune reactions in zebrafish and to explain the reported correlation between VDJ usage of B cell repertoires in distinct zebrafish. The first scale of the model consists of a generalized NK model to simulate the B cell maturation process in the 10-day primary immune response. The second scale uses a delay ordinary differential equation system to model the immune responses in the 6-month lifespan of zebrafish. The generalized NK model shows that mature B cells specific to one antigen mostly possess a single VDJ recombination. The probability that mature B cells in two zebrafish have the same VDJ recombination increases with the B cell population size or the B cell selection intensity and decreases with the B cell hypermutation rate. The ODE model shows a distribution of correlation in the VDJ usage of the B cell repertoires in two six-month-old zebrafish that is highly similar to that from experiment. This work presents a simple theory to explain the experimentally observed correlation in VDJ usage of distinct zebrafish B cell repertoires after an immune response.

Stochastic simulation tools and continuum models for describing two-dimensional collective cell spreading with universal growth functions

NASA Astrophysics Data System (ADS)

Jin, Wang; Penington, Catherine J.; McCue, Scott W.; Simpson, Matthew J.

2016-10-01

Two-dimensional collective cell migration assays are used to study cancer and tissue repair. These assays involve combined cell migration and cell proliferation processes, both of which are modulated by cell-to-cell crowding. Previous discrete models of collective cell migration assays involve a nearest-neighbour proliferation mechanism where crowding effects are incorporated by aborting potential proliferation events if the randomly chosen target site is occupied. There are two limitations of this traditional approach: (i) it seems unreasonable to abort a potential proliferation event based on the occupancy of a single, randomly chosen target site; and, (ii) the continuum limit description of this mechanism leads to the standard logistic growth function, but some experimental evidence suggests that cells do not always proliferate logistically. Motivated by these observations, we introduce a generalised proliferation mechanism which allows non-nearest neighbour proliferation events to take place over a template of r≥slant 1 concentric rings of lattice sites. Further, the decision to abort potential proliferation events is made using a crowding function, f(C), which accounts for the density of agents within a group of sites rather than dealing with the occupancy of a single randomly chosen site. Analysing the continuum limit description of the stochastic model shows that the standard logistic source term, λ C(1-C), where λ is the proliferation rate, is generalised to a universal growth function, λ C f(C). Comparing the solution of the continuum description with averaged simulation data indicates that the continuum model performs well for many choices of f(C) and r. For nonlinear f(C), the quality of the continuum-discrete match increases with r.

Stochastic simulation tools and continuum models for describing two-dimensional collective cell spreading with universal growth functions.

PubMed

Jin, Wang; Penington, Catherine J; McCue, Scott W; Simpson, Matthew J

2016-10-07

Two-dimensional collective cell migration assays are used to study cancer and tissue repair. These assays involve combined cell migration and cell proliferation processes, both of which are modulated by cell-to-cell crowding. Previous discrete models of collective cell migration assays involve a nearest-neighbour proliferation mechanism where crowding effects are incorporated by aborting potential proliferation events if the randomly chosen target site is occupied. There are two limitations of this traditional approach: (i) it seems unreasonable to abort a potential proliferation event based on the occupancy of a single, randomly chosen target site; and, (ii) the continuum limit description of this mechanism leads to the standard logistic growth function, but some experimental evidence suggests that cells do not always proliferate logistically. Motivated by these observations, we introduce a generalised proliferation mechanism which allows non-nearest neighbour proliferation events to take place over a template of [Formula: see text] concentric rings of lattice sites. Further, the decision to abort potential proliferation events is made using a crowding function, f(C), which accounts for the density of agents within a group of sites rather than dealing with the occupancy of a single randomly chosen site. Analysing the continuum limit description of the stochastic model shows that the standard logistic source term, [Formula: see text], where λ is the proliferation rate, is generalised to a universal growth function, [Formula: see text]. Comparing the solution of the continuum description with averaged simulation data indicates that the continuum model performs well for many choices of f(C) and r. For nonlinear f(C), the quality of the continuum-discrete match increases with r.

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

Deciphering the Minimal Algorithm for Development and Information-genesis

NASA Astrophysics Data System (ADS)

Li, Zhiyuan; Tang, Chao; Li, Hao

During development, cells with identical genomes acquires different fates in a highly organized manner. In order to decipher the principles underlining development, we used C.elegans as the model organism. Based on a large set of microscopy imaging, we first constructed a ``standard worm'' in silico: from the single zygotic cell to about 500 cell stage, the lineage, position, cell-cell contact and gene expression dynamics are quantified for each cell in order to investigate principles underlining these intensive data. Next, we reverse-engineered the possible gene-gene/cell-cell interaction rules that are capable of running a dynamic model recapitulating the early fate decisions during C.elegans development. we further formulized the C.elegans embryogenesis in the language of information genesis. Analysis towards data and model uncovered the global landscape of development in the cell fate space, suggested possible gene regulatory architectures and cell signaling processes, revealed diversity and robustness as the essential trade-offs in development, and demonstrated general strategies in building multicellular organisms.

Developing global regression models for metabolite concentration prediction regardless of cell line.

PubMed

André, Silvère; Lagresle, Sylvain; Da Sliva, Anthony; Heimendinger, Pierre; Hannas, Zahia; Calvosa, Éric; Duponchel, Ludovic

2017-11-01

Following the Process Analytical Technology (PAT) of the Food and Drug Administration (FDA), drug manufacturers are encouraged to develop innovative techniques in order to monitor and understand their processes in a better way. Within this framework, it has been demonstrated that Raman spectroscopy coupled with chemometric tools allow to predict critical parameters of mammalian cell cultures in-line and in real time. However, the development of robust and predictive regression models clearly requires many batches in order to take into account inter-batch variability and enhance models accuracy. Nevertheless, this heavy procedure has to be repeated for every new line of cell culture involving many resources. This is why we propose in this paper to develop global regression models taking into account different cell lines. Such models are finally transferred to any culture of the cells involved. This article first demonstrates the feasibility of developing regression models, not only for mammalian cell lines (CHO and HeLa cell cultures), but also for insect cell lines (Sf9 cell cultures). Then global regression models are generated, based on CHO cells, HeLa cells, and Sf9 cells. Finally, these models are evaluated considering a fourth cell line(HEK cells). In addition to suitable predictions of glucose and lactate concentration of HEK cell cultures, we expose that by adding a single HEK-cell culture to the calibration set, the predictive ability of the regression models are substantially increased. In this way, we demonstrate that using global models, it is not necessary to consider many cultures of a new cell line in order to obtain accurate models. Biotechnol. Bioeng. 2017;114: 2550-2559. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Modelling the Immune Response to Cancer: An Individual-Based Approach Accounting for the Difference in Movement Between Inactive and Activated T Cells.

PubMed

Macfarlane, Fiona R; Lorenzi, Tommaso; Chaplain, Mark A J

2018-06-01

A growing body of experimental evidence indicates that immune cells move in an unrestricted search pattern if they are in the pre-activated state, whilst they tend to stay within a more restricted area upon activation induced by the presence of tumour antigens. This change in movement is not often considered in the existing mathematical models of the interactions between immune cells and cancer cells. With the aim to fill such a gap in the existing literature, in this work we present a spatially structured individual-based model of tumour-immune competition that takes explicitly into account the difference in movement between inactive and activated immune cells. In our model, a Lévy walk is used to capture the movement of inactive immune cells, whereas Brownian motion is used to describe the movement of antigen-activated immune cells. The effects of activation of immune cells, the proliferation of cancer cells and the immune destruction of cancer cells are also modelled. We illustrate the ability of our model to reproduce qualitatively the spatial trajectories of immune cells observed in experimental data of single-cell tracking. Computational simulations of our model further clarify the conditions for the onset of a successful immune action against cancer cells and may suggest possible targets to improve the efficacy of cancer immunotherapy. Overall, our theoretical work highlights the importance of taking into account spatial interactions when modelling the immune response to cancer cells.

An automated approach for single-cell tracking in epifluorescence microscopy applied to E. coli growth analysis on microfluidics biochips

NASA Astrophysics Data System (ADS)

Fetita, Catalin; Kirov, Boris; Jaramillo, Alfonso; Lefevre, Christophe

2012-03-01

With the accumulation of knowledge for the intimate molecular mechanisms governing the processes inside the living cells in the later years, the ability to characterize the performance of elementary genetic circuits and parts at the single-cell level is becoming of crucial importance. Biological science is arriving to the point where it can develop hypothesis for the action of each molecule participating in the biochemical reactions and need proper techniques to test those hypothesis. Microfluidics is emerging as the technology that combined with high-magnification microscopy will allow for the long-term single-cell level observation of bacterial physiology. In this study we design, build and characterize the gene dynamics of genetic circuits as one of the basic parts governing programmed cell behavior. We use E. coli as model organism and grow it in microfluidics chips, which we observe with epifluorescence microscopy. One of the most invaluable segments of this technology is the consequent image processing, since it allows for the automated analysis of vast amount of single-cell observation and the fast and easy derivation of conclusions based on that data. Specifically, we are interested in promoter activity as function of time. We expect it to be oscillatory and for that we use GFP (green fluorescent protein) as a reporter in our genetic circuits. In this paper, an automated framework for single-cell tracking in phase-contrast microscopy is developed, combining 2D segmentation of cell time frames and graph-based reconstruction of their spatiotemporal evolution with fast tracking of the associated fluorescence signal. The results obtained on the investigated biological database are presented and discussed.

Cryo-imaging of fluorescently labeled single cells in a mouse

NASA Astrophysics Data System (ADS)

Steyer, Grant J.; Roy, Debashish; Salvado, Olivier; Stone, Meredith E.; Wilson, David L.

2009-02-01

We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryoimaging system consists of a fluorescence microscope, robotic imaging positioner, customized cryostat, PC-based control system, and visualization/analysis software. The system alternates between sectioning (10-40 μm) and imaging, collecting color brightfield and fluorescent blockface image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells, GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation parameters were found [uT : heart (267 +/- 47.6 μm), liver (218 +/- 27.1 μm), brain (161 +/- 27.4 μm)] to be within the range of estimates in the literature. "Next image" processing removed subsurface fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and analysis of 200 microsphere images in the brain gave 97+/-2% reduction of subsurface fluorescence. Fluorescent signals were determined to arise from single cells based upon geometric and integrated intensity measurements. Next image processing greatly improved axial resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells with connected component analysis by up to 24%. Analysis of image volumes identified metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere distribution correlated with blood flow patterns. We developed and evaluated cryo-imaging to provide single-cell detection of fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB), micron-scale, fluorescence, and bright field image data. Here we describe our image preprocessing, analysis, and visualization techniques. Processing improves axial resolution, reduces subsurface fluorescence by 97%, and enables single cell detection and counting. High quality 3D volume renderings enable us to evaluate cell distribution patterns. Applications include the myriad of biomedical experiments using fluorescent reporter gene and exogenous fluorophore labeling of cells in applications such as stem cell regenerative medicine, cancer, tissue engineering, etc.

Measuring Sparseness in the Brain: Comment on Bowers (2009)

ERIC Educational Resources Information Center

Quian Quiroga, Rodrigo; Kreiman, Gabriel

2010-01-01

Bowers challenged the common view in favor of distributed representations in psychological modeling and the main arguments given against localist and grandmother cell coding schemes. He revisited the results of several single-cell studies, arguing that they do not support distributed representations. We praise the contribution of Bowers (2009) for…

Droplet-based microfluidic analysis and screening of single plant cells.

PubMed

Yu, Ziyi; Boehm, Christian R; Hibberd, Julian M; Abell, Chris; Haseloff, Jim; Burgess, Steven J; Reyna-Llorens, Ivan

2018-01-01

Droplet-based microfluidics has been used to facilitate high-throughput analysis of individual prokaryote and mammalian cells. However, there is a scarcity of similar workflows applicable to rapid phenotyping of plant systems where phenotyping analyses typically are time-consuming and low-throughput. We report on-chip encapsulation and analysis of protoplasts isolated from the emergent plant model Marchantia polymorpha at processing rates of >100,000 cells per hour. We use our microfluidic system to quantify the stochastic properties of a heat-inducible promoter across a population of transgenic protoplasts to demonstrate its potential for assessing gene expression activity in response to environmental conditions. We further demonstrate on-chip sorting of droplets containing YFP-expressing protoplasts from wild type cells using dielectrophoresis force. This work opens the door to droplet-based microfluidic analysis of plant cells for applications ranging from high-throughput characterisation of DNA parts to single-cell genomics to selection of rare plant phenotypes.

Cellular recovery from exposure to sub-optimal concentrations of AB toxins that inhibit protein synthesis.

PubMed

Cherubin, Patrick; Quiñones, Beatriz; Teter, Ken

2018-02-06

Ricin, Shiga toxin, exotoxin A, and diphtheria toxin are AB-type protein toxins that act within the host cytosol and kill the host cell through pathways involving the inhibition of protein synthesis. It is thought that a single molecule of cytosolic toxin is sufficient to kill the host cell. Intoxication is therefore viewed as an irreversible process. Using flow cytometry and a fluorescent reporter system to monitor protein synthesis, we show a single molecule of cytosolic toxin is not sufficient for complete inhibition of protein synthesis or cell death. Furthermore, cells can recover from intoxication: cells with a partial loss of protein synthesis will, upon removal of the toxin, increase the level of protein production and survive the toxin challenge. Thus, in contrast to the prevailing model, ongoing toxin delivery to the cytosol appears to be required for the death of cells exposed to sub-optimal toxin concentrations.

IEEE Photovoltaic Specialists Conference, 20th, Las Vegas, NV, Sept. 26-30, 1988, Conference Record. Volumes 1 & 2

NASA Astrophysics Data System (ADS)

Various papers on photovoltaics are presented. The general topics considered include: amorphous materials and cells; amorphous silicon-based solar cells and modules; amorphous silicon-based materials and processes; amorphous materials characterization; amorphous silicon; high-efficiency single crystal solar cells; multijunction and heterojunction cells; high-efficiency III-V cells; modeling and characterization of high-efficiency cells; LIPS flight experience; space mission requirements and technology; advanced space solar cell technology; space environmental effects and modeling; space solar cell and array technology; terrestrial systems and array technology; terrestrial utility and stand-alone applications and testing; terrestrial concentrator and storage technology; terrestrial stand-alone systems applications; terrestrial systems test and evaluation; terrestrial flatplate and concentrator technology; use of polycrystalline materials; polycrystalline II-VI compound solar cells; analysis of and fabrication procedures for compound solar cells.

Variability in Cell Response of Cronobacter sakazakii after Mild-Heat Treatments and Its Impact on Food Safety

PubMed Central

Parra-Flores, Julio; Juneja, Vijay; Garcia de Fernando, Gonzalo; Aguirre, Juan

2016-01-01

Cronobacter spp. have been responsible for severe infections in infants associated with consumption of powdered infant formula and follow-up formulae. Despite several risk assessments described in published studies, few approaches have considered the tremendous variability in cell response that small micropopulations or single cells can have in infant formula during storage, preparation or post process/preparation before the feeding of infants. Stochastic approaches can better describe microbial single cell response than deterministic models as we prove in this study. A large variability of lag phase was observed in single cell and micropopulations of ≤50 cells. This variability increased as the heat shock increased and growth temperature decreased. Obviously, variability of growth of individual Cronobacter sakazakii cell is affected by inoculum size, growth temperature and the probability of cells able to grow at the conditions imposed by the experimental conditions should be taken into account, especially when errors in bottle-preparation practices, such as improper holding temperatures, or manipulation, may lead to growth of the pathogen to a critical cell level. The mean probability of illness from initial inoculum size of 1 cell was below 0.2 in all the cases and for inoculum size of 50 cells the mean probability of illness, in most of the cases, was above 0.7. PMID:27148223

Penium margaritaceum as a model organism for cell wall analysis of expanding plant cells.

PubMed

Rydahl, Maja G; Fangel, Jonatan U; Mikkelsen, Maria Dalgaard; Johansen, I Elisabeth; Andreas, Amanda; Harholt, Jesper; Ulvskov, Peter; Jørgensen, Bodil; Domozych, David S; Willats, William G T

2015-01-01

The growth of a plant cell encompasses a complex set of subcellular components interacting in a highly coordinated fashion. Ultimately, these activities create specific cell wall structural domains that regulate the prime force of expansion, internally generated turgor pressure. The precise organization of the polymeric networks of the cell wall around the protoplast also contributes to the direction of growth, the shape of the cell, and the proper positioning of the cell in a tissue. In essence, plant cell expansion represents the foundation of development. Most studies of plant cell expansion have focused primarily upon late divergent multicellular land plants and specialized cell types (e.g., pollen tubes, root hairs). Here, we describe a unicellular green alga, Penium margaritaceum (Penium), which can serve as a valuable model organism for understanding cell expansion and the underlying mechanics of the cell wall in a single plant cell.

Modeling the effect of boost timing in murine irradiated sporozoite prime-boost vaccines

PubMed Central

Zhang, Min; Herrero, Miguel A.; Acosta, Francisco J.; Tsuji, Moriya

2018-01-01

Vaccination with radiation-attenuated sporozoites has been shown to induce CD8+ T cell-mediated protection against pre-erythrocytic stages of malaria. Empirical evidence suggests that successive inoculations often improve the efficacy of this type of vaccines. An initial dose (prime) triggers a specific cellular response, and subsequent inoculations (boost) amplify this response to create a robust CD8+ T cell memory. In this work we propose a model to analyze the effect of T cell dynamics on the performance of prime-boost vaccines. This model suggests that boost doses and timings should be selected according to the T cell response elicited by priming. Specifically, boosting during late stages of clonal contraction would maximize T cell memory production for vaccines using lower doses of irradiated sporozoites. In contrast, single-dose inoculations would be indicated for higher vaccine doses. Experimental data have been obtained that support theoretical predictions of the model. PMID:29329308

Hypothesis driven single cell dual oscillator mathematical model of circadian rhythms

PubMed Central

S, Shiju

2017-01-01

Molecular mechanisms responsible for 24 h circadian oscillations, entrainment to external cues, encoding of day length and the time-of-day effects have been well studied experimentally. However, it is still debated from the molecular network point of view whether each cell in suprachiasmatic nuclei harbors two molecular oscillators, where one tracks dawn and the other tracks dusk activities. A single cell dual morning and evening oscillator was proposed by Daan et al., based on the molecular network that has two sets of similar non-redundant per1/cry1 and per2/cry2 circadian genes and each can independently maintain their endogenous oscillations. Understanding of dual oscillator dynamics in a single cell at molecular level may provide insight about the circadian mechanisms that encodes day length variations and its response to external zeitgebers. We present here a realistic dual oscillator model of circadian rhythms based on the series of hypotheses proposed by Daan et al., in which they conjectured that the circadian genes per1/cry1 track dawn while per2/cry2 tracks dusk and they together constitute the morning and evening oscillators (dual oscillator). Their hypothesis also provides explanations about the encoding of day length in terms of molecular mechanisms of per/cry expression. We frame a minimal mathematical model with the assumption that per1 acts a morning oscillator and per2 acts as an evening oscillator and to support and interpret this assumption we fit the model to the experimental data of per1/per2 circadian temporal dynamics, phase response curves (PRC's), and entrainment phenomena under various light-dark conditions. We also capture different patterns of splitting phenomena by coupling two single cell dual oscillators with neuropeptides vasoactive intestinal polypeptide (VIP) and arginine vasopressin (AVP) as the coupling agents and provide interpretation for the occurrence of splitting in terms of ME oscillators, though they are not required to explain the morning and evening oscillators. The proposed dual oscillator model based on Daan's hypothesis supports per1 and per2 playing the role of morning and evening oscillators respectively and this may be the first step towards the understanding of the core molecular mechanism responsible for encoding the day length. PMID:28486525

Hypothesis driven single cell dual oscillator mathematical model of circadian rhythms.

PubMed

S, Shiju; Sriram, K

2017-01-01

Molecular mechanisms responsible for 24 h circadian oscillations, entrainment to external cues, encoding of day length and the time-of-day effects have been well studied experimentally. However, it is still debated from the molecular network point of view whether each cell in suprachiasmatic nuclei harbors two molecular oscillators, where one tracks dawn and the other tracks dusk activities. A single cell dual morning and evening oscillator was proposed by Daan et al., based on the molecular network that has two sets of similar non-redundant per1/cry1 and per2/cry2 circadian genes and each can independently maintain their endogenous oscillations. Understanding of dual oscillator dynamics in a single cell at molecular level may provide insight about the circadian mechanisms that encodes day length variations and its response to external zeitgebers. We present here a realistic dual oscillator model of circadian rhythms based on the series of hypotheses proposed by Daan et al., in which they conjectured that the circadian genes per1/cry1 track dawn while per2/cry2 tracks dusk and they together constitute the morning and evening oscillators (dual oscillator). Their hypothesis also provides explanations about the encoding of day length in terms of molecular mechanisms of per/cry expression. We frame a minimal mathematical model with the assumption that per1 acts a morning oscillator and per2 acts as an evening oscillator and to support and interpret this assumption we fit the model to the experimental data of per1/per2 circadian temporal dynamics, phase response curves (PRC's), and entrainment phenomena under various light-dark conditions. We also capture different patterns of splitting phenomena by coupling two single cell dual oscillators with neuropeptides vasoactive intestinal polypeptide (VIP) and arginine vasopressin (AVP) as the coupling agents and provide interpretation for the occurrence of splitting in terms of ME oscillators, though they are not required to explain the morning and evening oscillators. The proposed dual oscillator model based on Daan's hypothesis supports per1 and per2 playing the role of morning and evening oscillators respectively and this may be the first step towards the understanding of the core molecular mechanism responsible for encoding the day length.

Quantitative Analysis of Protein Translocations by Microfluidic Total Internal Reflection Fluorescence Flow Cytometry

PubMed Central

Wang, Jun; Fei, Bei; Geahlen, Robert L.

2010-01-01

Protein translocation, or the change in a protein’s location between different subcellular compartments, is a critical process by which intracellular proteins carry out their cellular functions. Aberrant translocation events contribute to various diseases ranging from metabolic disorders to cancer. In this study, we demonstrate the use of a newly developed single-cell tool, microfluidic total internal reflection fluorescence flow cytometry (TIRF-FC), for detecting both cytosol to plasma membrane and cytosol to nucleus translocations using the tyrosine kinase Syk and the transcription factor NF-κB as models. This technique detects fluorescent molecules at the plasma membrane and in the membrane-proximal cytosol in single cells. We were able to record quantitatively changes in the fluorescence density in the evanescent field associated with these translocation processes for large cell populations with single cell resolution. We envision that TIRF-FC will provide a new approach to explore the molecular biology and clinical relevance of protein translocations. PMID:20820633

Single-cell isolation by a modular single-cell pipette for RNA-sequencing.

PubMed

Zhang, Kai; Gao, Min; Chong, Zechen; Li, Ying; Han, Xin; Chen, Rui; Qin, Lidong

2016-11-29

Single-cell transcriptome sequencing highly requires a convenient and reliable method to rapidly isolate a live cell into a specific container such as a PCR tube. Here, we report a modular single-cell pipette (mSCP) consisting of three modular components, a SCP-Tip, an air-displacement pipette (ADP), and ADP-Tips, that can be easily assembled, disassembled, and reassembled. By assembling the SCP-Tip containing a hydrodynamic trap, the mSCP can isolate single cells from 5-10 cells per μL of cell suspension. The mSCP is compatible with microscopic identification of captured single cells to finally achieve 100% single-cell isolation efficiency. The isolated live single cells are in submicroliter volumes and well suitable for single-cell PCR analysis and RNA-sequencing. The mSCP possesses merits of convenience, rapidness, and high efficiency, making it a powerful tool to isolate single cells for transcriptome analysis.

A rigorous multiple independent binding site model for determining cell-based equilibrium dissociation constants.

PubMed

Drake, Andrew W; Klakamp, Scott L

2007-01-10

A new 4-parameter nonlinear equation based on the standard multiple independent binding site model (MIBS) is presented for fitting cell-based ligand titration data in order to calculate the ligand/cell receptor equilibrium dissociation constant and the number of receptors/cell. The most commonly used linear (Scatchard Plot) or nonlinear 2-parameter model (a single binding site model found in commercial programs like Prism(R)) used for analysis of ligand/receptor binding data assumes only the K(D) influences the shape of the titration curve. We demonstrate using simulated data sets that, depending upon the cell surface receptor expression level, the number of cells titrated, and the magnitude of the K(D) being measured, this assumption of always being under K(D)-controlled conditions can be erroneous and can lead to unreliable estimates for the binding parameters. We also compare and contrast the fitting of simulated data sets to the commonly used cell-based binding equation versus our more rigorous 4-parameter nonlinear MIBS model. It is shown through these simulations that the new 4-parameter MIBS model, when used for cell-based titrations under optimal conditions, yields highly accurate estimates of all binding parameters and hence should be the preferred model to fit cell-based experimental nonlinear titration data.

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

PubMed

Roeder, Ingo; Herberg, Maria; Horn, Matthias

2009-04-01

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

Prospective guidance in a free-swimming cell.

PubMed

Delafield-Butt, Jonathan T; Pepping, Gert-Jan; McCaig, Colin D; Lee, David N

2012-07-01

A systems theory of movement control in animals is presented in this article and applied to explaining the controlled behaviour of the single-celled Paramecium caudatum in an electric field. The theory-General Tau Theory-is founded on three basic principles: (i) all purposive movement entails prospectively controlling the closure of action-gaps (e.g. a distance gap when reaching, or an angle gap when steering); (ii) the sole informational variable required for controlling gaps is the relative rate of change of the gap (the time derivative of the gap size divided by the size), which can be directly sensed; and (iii) a coordinated movement is achieved by keeping the relative rates of change of gaps in a constant ratio. The theory is supported by studies of controlled movement in mammals, birds and insects. We now show for the first time that it is also supported by single-celled paramecia steering to the cathode in a bi-polar electric field. General Tau Theory is deployed to explain this guided steering by the cell. This article presents the first computational model of prospective perceptual control in a non-neural, single-celled system.

Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters

NASA Astrophysics Data System (ADS)

Munsky, Brian; Trinh, Brooke; Khammash, Mustafa

2010-03-01

The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations exhibit cell-to-cell variability that can manifest significant prototypical differences. Noise induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified using flow cytometry, single molecule fluorescence in situ hybridization, time lapse fluorescence microscopy and other single cell and single molecule measurement techniques. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. We use theoretical investigations to establish experimental guidelines for the identification of gene regulatory networks, and we apply these guideline to experimentally identify predictive models for different regulatory mechanisms in bacteria and yeast.

SU-E-T-146: Effects of Uncertainties of Radiation Sensitivity of Biological Modelling for Treatment Planning

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

Oita, M; Department of Life System, Institute of Technology and Science, Graduate School, The Tokushima University; Uto, Y

Purpose: The aim of this study was to evaluate the distribution of uncertainty of cell survival by radiation, and assesses the usefulness of stochastic biological model applying for gaussian distribution. Methods: For single cell experiments, exponentially growing cells were harvested from the standard cell culture dishes by trypsinization, and suspended in test tubes containing 1 ml of MEM(2x10{sup 6} cells/ml). The hypoxic cultures were treated with 95% N{sub 2}−5% CO{sub 2} gas for 30 minutes. In vitro radiosensitization was also measured in EMT6/KU single cells to add radiosensitizer under hypoxic conditions. X-ray irradiation was carried out by using an Xraymore » unit (Hitachi X-ray unit, model MBR-1505R3) with 0.5 mm Al/1.0 mm Cu filter, 150 kV, 4 Gy/min). In vitro assay, cells on the dish were irradiated with 1 Gy to 24 Gy, respectively. After irradiation, colony formation assays were performed. Variations of biological parameters were investigated at standard cell culture(n=16), hypoxic cell culture(n=45) and hypoxic cell culture(n=21) with radiosensitizers, respectively. The data were obtained by separate schedule to take account for the variation of radiation sensitivity of cell cycle. Results: At standard cell culture, hypoxic cell culture and hypoxic cell culture with radiosensitizers, median and standard deviation of alpha/beta ratio were 37.1±73.4 Gy, 9.8±23.7 Gy, 20.7±21.9 Gy, respectively. Average and standard deviation of D{sub 50} were 2.5±2.5 Gy, 6.1±2.2 Gy, 3.6±1.3 Gy, respectively. Conclusion: In this study, we have challenged to apply these uncertainties of parameters for the biological model. The variation of alpha values, beta values, D{sub 50} as well as cell culture might have highly affected by probability of cell death. Further research is in progress for precise prediction of the cell death as well as tumor control probability for treatment planning.« less

Viral coinfection is shaped by host ecology and virus-virus interactions across diverse microbial taxa and environments.

PubMed

Díaz-Muñoz, Samuel L

2017-01-01

Infection of more than one virus in a host, coinfection, is common across taxa and environments. Viral coinfection can enable genetic exchange, alter the dynamics of infections, and change the course of viral evolution. Yet, a systematic test of the factors explaining variation in viral coinfection across different taxa and environments awaits completion. Here I employ three microbial data sets of virus-host interactions covering cross-infectivity, culture coinfection, and single-cell coinfection (total: 6,564 microbial hosts, 13,103 viruses) to provide a broad, comprehensive picture of the ecological and biological factors shaping viral coinfection. I found evidence that ecology and virus-virus interactions are recurrent factors shaping coinfection patterns. Host ecology was a consistent and strong predictor of coinfection across all three data sets: cross-infectivity, culture coinfection, and single-cell coinfection. Host phylogeny or taxonomy was a less consistent predictor, being weak or absent in the cross-infectivity and single-cell coinfection models, yet it was the strongest predictor in the culture coinfection model. Virus-virus interactions strongly affected coinfection. In the largest test of superinfection exclusion to date, prophage sequences reduced culture coinfection by other prophages, with a weaker effect on extrachromosomal virus coinfection. At the single-cell level, prophage sequences eliminated coinfection. Virus-virus interactions also increased culture coinfection with ssDNA-dsDNA coinfections >2× more likely than ssDNA-only coinfections. The presence of CRISPR spacers was associated with a ∼50% reduction in single-cell coinfection in a marine bacteria, despite the absence of exact spacer matches in any active infection. Collectively, these results suggest the environment bacteria inhabit and the interactions among surrounding viruses are two factors consistently shaping viral coinfection patterns. These findings highlight the role of virus-virus interactions in coinfection with implications for phage therapy, microbiome dynamics, and viral infection treatments.

Modeling heterogeneous responsiveness of intrinsic apoptosis pathway

PubMed Central

2013-01-01

Background Apoptosis is a cell suicide mechanism that enables multicellular organisms to maintain homeostasis and to eliminate individual cells that threaten the organism’s survival. Dependent on the type of stimulus, apoptosis can be propagated by extrinsic pathway or intrinsic pathway. The comprehensive understanding of the molecular mechanism of apoptotic signaling allows for development of mathematical models, aiming to elucidate dynamical and systems properties of apoptotic signaling networks. There have been extensive efforts in modeling deterministic apoptosis network accounting for average behavior of a population of cells. Cellular networks, however, are inherently stochastic and significant cell-to-cell variability in apoptosis response has been observed at single cell level. Results To address the inevitable randomness in the intrinsic apoptosis mechanism, we develop a theoretical and computational modeling framework of intrinsic apoptosis pathway at single-cell level, accounting for both deterministic and stochastic behavior. Our deterministic model, adapted from the well-accepted Fussenegger model, shows that an additional positive feedback between the executioner caspase and the initiator caspase plays a fundamental role in yielding the desired property of bistability. We then examine the impact of intrinsic fluctuations of biochemical reactions, viewed as intrinsic noise, and natural variation of protein concentrations, viewed as extrinsic noise, on behavior of the intrinsic apoptosis network. Histograms of the steady-state output at varying input levels show that the intrinsic noise could elicit a wider region of bistability over that of the deterministic model. However, the system stochasticity due to intrinsic fluctuations, such as the noise of steady-state response and the randomness of response delay, shows that the intrinsic noise in general is insufficient to produce significant cell-to-cell variations at physiologically relevant level of molecular numbers. Furthermore, the extrinsic noise represented by random variations of two key apoptotic proteins, namely Cytochrome C and inhibitor of apoptosis proteins (IAP), is modeled separately or in combination with intrinsic noise. The resultant stochasticity in the timing of intrinsic apoptosis response shows that the fluctuating protein variations can induce cell-to-cell stochastic variability at a quantitative level agreeing with experiments. Finally, simulations illustrate that the mean abundance of fluctuating IAP protein is positively correlated with the degree of cellular stochasticity of the intrinsic apoptosis pathway. Conclusions Our theoretical and computational study shows that the pronounced non-genetic heterogeneity in intrinsic apoptosis responses among individual cells plausibly arises from extrinsic rather than intrinsic origin of fluctuations. In addition, it predicts that the IAP protein could serve as a potential therapeutic target for suppression of the cell-to-cell variation in the intrinsic apoptosis responsiveness. PMID:23875784

A predictive pharmacokinetic-pharmacodynamic model of tumor growth kinetics in xenograft mice after administration of anticancer agents given in combination.

PubMed

Terranova, Nadia; Germani, Massimiliano; Del Bene, Francesca; Magni, Paolo

2013-08-01

In clinical oncology, combination treatments are widely used and increasingly preferred over single drug administrations. A better characterization of the interaction between drug effects and the selection of synergistic combinations represent an open challenge in drug development process. To this aim, preclinical studies are routinely performed, even if they are only qualitatively analyzed due to the lack of generally applicable mathematical models. This paper presents a new pharmacokinetic-pharmacodynamic model that, starting from the well-known single agent Simeoni TGI model, is able to describe tumor growth in xenograft mice after the co-administration of two anticancer agents. Due to the drug action, tumor cells are divided in two groups: damaged and not damaged ones. The damaging rate has two terms proportional to drug concentrations (as in the single drug administration model) and one interaction term proportional to their product. Six of the eight pharmacodynamic parameters assume the same value as in the corresponding single drug models. Only one parameter summarizes the interaction, and it can be used to compute two important indexes that are a clear way to score the synergistic/antagonistic interaction among drug effects. The model was successfully applied to four new compounds co-administered with four drugs already available on the market for the treatment of three different tumor cell lines. It also provided reliable predictions of different combination regimens in which the same drugs were administered at different doses/schedules. A good and quantitative measurement of the intensity and nature of interaction between drug effects, as well as the capability to correctly predict new combination arms, suggest the use of this generally applicable model for supporting the experiment optimal design and the prioritization of different therapies.

Live-Cell Imaging of the Adult Drosophila Ovary Using Confocal Microscopy.

PubMed

Shalaby, Nevine A; Buszczak, Michael

2017-01-01

The Drosophila ovary represents a key in vivo model used to study germline stem cell (GSC) maintenance and stem cell daughter differentiation because these cells and their somatic cell neighbors can be identified at single-cell resolution within their native environment. Here we describe a fluorescent-based technique for the acquisition of 4D datasets of the Drosophila ovariole for periods that can exceed 12 consecutive hours. Live-cell imaging facilitates the investigation of molecular and cellular dynamics that were not previously possible using still images.

Global Effects of DDX3 Inhibition on Cell Cycle Regulation Identified by a Combined Phosphoproteomics and Single Cell Tracking Approach.

PubMed

Heerma van Voss, Marise R; Kammers, Kai; Vesuna, Farhad; Brilliant, Justin; Bergman, Yehudit; Tantravedi, Saritha; Wu, Xinyan; Cole, Robert N; Holland, Andrew; van Diest, Paul J; Raman, Venu

2018-06-01

DDX3 is an RNA helicase with oncogenic properties. The small molecule inhibitor RK-33 is designed to fit into the ATP binding cleft of DDX3 and hereby block its activity. RK-33 has shown potent activity in preclinical cancer models. However, the mechanism behind the antineoplastic activity of RK-33 remains largely unknown. In this study we used a dual phosphoproteomic and single cell tracking approach to evaluate the effect of RK-33 on cancer cells. MDA-MB-435 cells were treated for 24 hours with RK-33 or vehicle control. Changes in phosphopeptide abundance were analyzed with quantitative mass spectrometry using isobaric mass tags (Tandem Mass Tags). At the proteome level we mainly observed changes in mitochondrial translation, cell division pathways and proteins related to cell cycle progression. Analysis of the phosphoproteome indicated decreased CDK1 activity after RK-33 treatment. To further evaluate the effect of DDX3 inhibition on cell cycle progression over time, we performed timelapse microscopy of Fluorescent Ubiquitin Cell Cycle Indicators labeled cells after RK-33 or siDDX3 exposure. Single cell tracking indicated that DDX3 inhibition resulted in a global delay in cell cycle progression in interphase and mitosis. In addition, we observed an increase in endoreduplication. Overall, we conclude that DDX3 inhibition affects cells in all phases and causes a global cell cycle progression delay. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Cell-ECM Interactions During Cancer Invasion

NASA Astrophysics Data System (ADS)

Jiang, Yi

The extracellular matrix (ECM), a fibrous material that forms a network in a tissue, significantly affects many aspects of cellular behavior, including cell movement and proliferation. Transgenic mouse tumor studies indicate that excess collagen, a major component of ECM, enhances tumor formation and invasiveness. Clinically, tumor associated collagen signatures are strong markers for breast cancer survival. However, the underlying mechanisms are unclear since the properties of ECM are complex, with diverse structural and mechanical properties depending on various biophysical parameters. We have developed a three-dimensional elastic fiber network model, and parameterized it with in vitro collagen mechanics. Using this model, we study ECM remodeling as a result of local deformation and cell migration through the ECM as a network percolation problem. We have also developed a three-dimensional, multiscale model of cell migration and interaction with ECM. Our model reproduces quantitative single cell migration experiments. This model is a first step toward a fully biomechanical cell-matrix interaction model and may shed light on tumor associated collagen signatures in breast cancer. This work was partially supported by NIH-U01CA143069.

In vitro ovine articular chondrocyte proliferation: experiments and modelling.

PubMed

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

2010-06-01

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

Single-cell analysis of pyroptosis dynamics reveals conserved GSDMD-mediated subcellular events that precede plasma membrane rupture.

PubMed

de Vasconcelos, Nathalia M; Van Opdenbosch, Nina; Van Gorp, Hanne; Parthoens, Eef; Lamkanfi, Mohamed

2018-04-17

Pyroptosis is rapidly emerging as a mechanism of anti-microbial host defense, and of extracellular release of the inflammasome-dependent cytokines interleukin (IL)-1β and IL-18, which contributes to autoinflammatory pathology. Caspases 1, 4, 5 and 11 trigger this regulated form of necrosis by cleaving the pyroptosis effector gasdermin D (GSDMD), causing its pore-forming amino-terminal domain to oligomerize and perforate the plasma membrane. However, the subcellular events that precede pyroptotic cell lysis are ill defined. In this study, we triggered primary macrophages to undergo pyroptosis from three inflammasome types and recorded their dynamics and morphology using high-resolution live-cell spinning disk confocal laser microscopy. Based on quantitative analysis of single-cell subcellular events, we propose a model of pyroptotic cell disintegration that is initiated by opening of GSDMD-dependent ion channels or pores that are more restrictive than recently proposed GSDMD pores, followed by osmotic cell swelling, commitment of mitochondria and other membrane-bound organelles prior to sudden rupture of the plasma membrane and full permeability to intracellular proteins. This study provides a dynamic framework for understanding cellular changes that occur during pyroptosis, and charts a chronological sequence of GSDMD-mediated subcellular events that define pyroptotic cell death at the single-cell level.

Tumoral stem cell reprogramming as a driver of cancer: Theory, biological models, implications in cancer therapy.

PubMed

Vicente-Dueñas, Carolina; Hauer, Julia; Ruiz-Roca, Lucía; Ingenhag, Deborah; Rodríguez-Meira, Alba; Auer, Franziska; Borkhardt, Arndt; Sánchez-García, Isidro

2015-06-01

Cancer is a clonal malignant disease originated in a single cell and characterized by the accumulation of partially differentiated cells that are phenotypically reminiscent of normal stages of differentiation. According to current models, therapeutic strategies that block oncogene activity are likely to selectively target tumor cells. However, recent evidences have revealed that cancer stem cells could arise through a tumor stem cell reprogramming mechanism, suggesting that genetic lesions that initiate the cancer process might be dispensable for tumor progression and maintenance. This review addresses the impact of these results toward a better understanding of cancer development and proposes new approaches to treat cancer in the future. Copyright © 2014 Elsevier Ltd. All rights reserved.

A multi-scale model for correlation in B cell VDJ usage of zebrafish

NASA Astrophysics Data System (ADS)

Pan, Keyao; Deem, Michael W.

2011-10-01

The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment.

Spiral ganglion cell site of excitation I: comparison of scala tympani and intrameatal electrode responses.

PubMed

Cartee, Lianne A; Miller, Charles A; van den Honert, Chris

2006-05-01

To determine the site of excitation on the spiral ganglion cell in response to electrical stimulation similar to that from a cochlear implant, single-fiber responses to electrical stimuli delivered by an electrode positioned in the scala tympani were compared to responses from stimuli delivered by an electrode placed in the internal auditory meatus. The response to intrameatal stimulation provided a control set of data with a known excitation site, the central axon of the spiral ganglion cell. For both intrameatal and scala tympani stimuli, the responses to single-pulse, summation, and refractory stimulus protocols were recorded. The data demonstrated that summation pulses, as opposed to single pulses, are likely to give the most insightful measures for determination of the site of excitation. Single-fiber summation data for both scala tympani and intrameatally stimulated fibers were analyzed with a clustering algorithm. Combining cluster analysis and additional numerical modeling data, it was hypothesized that the scala tympani responses corresponded to central excitation, peripheral excitation adjacent to the cell body, and peripheral excitation at a site distant from the cell body. Fibers stimulated by an intrameatal electrode demonstrated the greatest range of jitter measurements indicating that greater fiber independence may be achieved with intrameatal stimulation.

Implications of cellular models of dopamine neurons for disease

PubMed Central

Evans, Rebekah C.; Oster, Andrew M.; Pissadaki, Eleftheria K.; Drion, Guillaume; Kuznetsov, Alexey S.; Gutkin, Boris S.

2016-01-01

This review addresses the present state of single-cell models of the firing pattern of midbrain dopamine neurons and the insights that can be gained from these models into the underlying mechanisms for diseases such as Parkinson's, addiction, and schizophrenia. We will explain the analytical technique of separation of time scales and show how it can produce insights into mechanisms using simplified single-compartment models. We also use morphologically realistic multicompartmental models to address spatially heterogeneous aspects of neural signaling and neural metabolism. Separation of time scale analyses are applied to pacemaking, bursting, and depolarization block in dopamine neurons. Differences in subpopulations with respect to metabolic load are addressed using multicompartmental models. PMID:27582295

Influence of substrate diffusion on degradation of dibenzofuran and 3-chlorodibenzofuran by attached and suspended bacteria.

PubMed Central

Harms, H; Zehnder, A J

1994-01-01

Dibenzofuran uptake-associated kinetic parameters of suspended and attached Sphingomonas sp. strain HH19k cells were compared. The suspended cells were studied in a batch system, whereas glass beads in percolated columns were used as the solid support for attached cells. The maximum specific activities of cells in the two systems were the same. The apparent half-maximum uptake rate-associated concentrations (Kt') of attached cells, however, were considerably greater than those of suspended cells and depended on cell density and on percolation velocity. A mathematical model was developed to explain the observed differences in terms of substrate transport to the cells. This model was based on the assumptions that the intrinsic half-maximum uptake rate-associated concentration (Kt) was unchanged and that deviations of Kt' from Kt resulted from the stereometry and the hydrodynamics around the cells. Our calculations showed that (i) diffusion to suspended cells and to single attached cells is efficient and therefore only slightly affects Kt'; (ii) diffusion to cells located on crowded surfaces is considerably lower than that to single attached cells and greatly increases Kt', which depends on the cell density; (iii) the convective-diffusive transport to attached cells that occurs in a percolated column is influenced by the liquid flow and results in dependency of Kt' on the flow rate; and (iv) higher specific affinity of cells correlates with higher susceptibility to diffusion limitation. Properties of the experimental system which limited quantitative proof of exclusively transport-controlled variations of Kt' are discussed. PMID:8085817

Computer modeling of batteries from nonlinear circuit elements

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

Waaben, S.; Dyer, C.K.; Federico, J.

1985-06-01

Circuit analogs for a single battery cell have previously been composed of resistors, capacitors, and inductors. This work introduces a nonlinear circuit model for cell behavior. The circuit is configured around the PIN junction diode, whose charge-storage behavior has features similar to those of electrochemical cells. A user-friendly integrated circuit simulation computer program has reproduced a variety of complex cell responses including electrica isolation effects causing capacity loss, as well as potentiodynamic peaks and discharge phenomena hitherto thought to be thermodynamic in origin. However, in this work, they are shown to be simply due to spatial distribution of stored chargemore » within a practical electrode.« less

Low-dose cyclophosphamide administered as daily or single dose enhances the antitumor effects of a therapeutic HPV vaccine

PubMed Central

Peng, Shiwen; Lyford-Pike, Sofia; Akpeng, Belinda; Wu, Annie; Hung, Chien-Fu; Hannaman, Drew; Saunders, John R.; Wu, T.-C.

2012-01-01

Although therapeutic HPV vaccines are able to elicit systemic HPV-specific immunity, clinical responses have not always correlated with levels of vaccine-induced CD8+ T cells in human clinical trials. This observed discrepancy may be attributable to an immunosuppressive tumor microenvironment in which the CD8+ T cells are recruited. Regulatory T cells (Tregs) are cells that can dampen cytotoxic CD8+ T-cell function. Cyclophosphamide (CTX) is a systemic chemotherapeutic agent, which can eradicate immune cells, including inhibitory Tregs. The optimal dose and schedule of CTX administration in combination with immunotherapy to eliminate the Treg population without adversely affecting vaccine-induced T-cell responses is unknown. Therefore, we investigated various dosing and administration schedules of CTX in combination with a therapeutic HPV vaccine in a preclinical tumor model. HPV tumor-bearing mice received either a single preconditioning dose or a daily dose of CTX in combination with the pNGVL4a-CRT/E7(detox) DNA vaccine. Both single and daily dosing of CTX in combination with vaccine had a synergistic anti-tumor effect as compared to monotherapy alone. The potent antitumor responses were attributed to the reduction in Treg frequency and increased infiltration of HPV16 E7-specific CD8+ T cells, which led to higher ratios of CD8+/Treg and CD8+/CD11b+Gr-1+ myeloid-derived suppressor cells (MDSCs). There was an observed trend toward decreased vaccine-induced CD8+ T-cell frequency with daily dosing of CTX. We recommend a single, preconditioning dose of CTX prior to vaccination due to its efficacy, ease of administration, and reduced cumulative adverse effect on vaccine-induced T cells. PMID:23011589

Single-cell-type quantitative proteomic and ionomic analysis of epidermal bladder cells from the halophyte model plant Mesembryanthemum crystallinum to identify salt-responsive proteins.

PubMed

Barkla, Bronwyn J; Vera-Estrella, Rosario; Raymond, Carolyn

2016-05-10

Epidermal bladder cells (EBC) are large single-celled, specialized, and modified trichomes found on the aerial parts of the halophyte Mesembryanthemum crystallinum. Recent development of a simple but high throughput technique to extract the contents from these cells has provided an opportunity to conduct detailed single-cell-type analyses of their molecular characteristics at high resolution to gain insight into the role of these cells in the salt tolerance of the plant. In this study, we carry out large-scale complementary quantitative proteomic studies using both a label (DIGE) and label-free (GeLC-MS) approach to identify salt-responsive proteins in the EBC extract. Additionally we perform an ionomics analysis (ICP-MS) to follow changes in the amounts of 27 different elements. Using these methods, we were able to identify 54 proteins and nine elements that showed statistically significant changes in the EBC from salt-treated plants. GO enrichment analysis identified a large number of transport proteins but also proteins involved in photosynthesis, primary metabolism and Crassulacean acid metabolism (CAM). Validation of results by western blot, confocal microscopy and enzyme analysis helped to strengthen findings and further our understanding into the role of these specialized cells. As expected EBC accumulated large quantities of sodium, however, the most abundant element was chloride suggesting the sequestration of this ion into the EBC vacuole is just as important for salt tolerance. This single-cell type omics approach shows that epidermal bladder cells of M. crystallinum are metabolically active modified trichomes, with primary metabolism supporting cell growth, ion accumulation, compatible solute synthesis and CAM. Data are available via ProteomeXchange with identifier PXD004045.

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications.

PubMed

Van den Berge, Koen; Perraudeau, Fanny; Soneson, Charlotte; Love, Michael I; Risso, Davide; Vert, Jean-Philippe; Robinson, Mark D; Dudoit, Sandrine; Clement, Lieven

2018-02-26

Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce a weighting strategy, based on a zero-inflated negative binomial model, that identifies excess zero counts and generates gene- and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq.

A Role for Single-Stranded Exonucleases in the Use of DNA as a Nutrient▿

PubMed Central

Palchevskiy, Vyacheslav; Finkel, Steven E.

2009-01-01

Nutritional competence is the ability of bacterial cells to utilize exogenous double-stranded DNA molecules as a nutrient source. We previously identified several genes in Escherichia coli that are important for this process and proposed a model, based on models of natural competence and transformation in bacteria, where it is assumed that single-stranded DNA (ssDNA) is degraded following entry into the cytoplasm. Since E. coli has several exonucleases, we determined whether they play a role in the long-term survival and the catabolism of DNA as a nutrient. We show here that mutants lacking either ExoI, ExoVII, ExoX, or RecJ are viable during all phases of the bacterial life cycle yet cannot compete with wild-type cells during long-term stationary-phase incubation. We also show that nuclease mutants, alone or in combination, are defective in DNA catabolism, with the exception of the ExoX− single mutant. The ExoX− mutant consumes double-stranded DNA better than wild-type cells, possibly implying the presence of two pathways in E. coli for the processing of ssDNA as it enters the cytoplasm. PMID:19329645

Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics.

PubMed

Beattie, Kylie A; Hill, Adam P; Bardenet, Rémi; Cui, Yi; Vandenberg, Jamie I; Gavaghan, David J; de Boer, Teun P; Mirams, Gary R

2018-03-24

Ion current kinetics are commonly represented by current-voltage relationships, time constant-voltage relationships and subsequently mathematical models fitted to these. These experiments take substantial time, which means they are rarely performed in the same cell. Rather than traditional square-wave voltage clamps, we fitted a model to the current evoked by a novel sum-of-sinusoids voltage clamp that was only 8 s long. Short protocols that can be performed multiple times within a single cell will offer many new opportunities to measure how ion current kinetics are affected by changing conditions. The new model predicts the current under traditional square-wave protocols well, with better predictions of underlying currents than literature models. The current under a novel physiologically relevant series of action potential clamps is predicted extremely well. The short sinusoidal protocols allow a model to be fully fitted to individual cells, allowing us to examine cell-cell variability in current kinetics for the first time. Understanding the roles of ion currents is crucial to predict the action of pharmaceuticals and mutations in different scenarios, and thereby to guide clinical interventions in the heart, brain and other electrophysiological systems. Our ability to predict how ion currents contribute to cellular electrophysiology is in turn critically dependent on our characterisation of ion channel kinetics - the voltage-dependent rates of transition between open, closed and inactivated channel states. We present a new method for rapidly exploring and characterising ion channel kinetics, applying it to the hERG potassium channel as an example, with the aim of generating a quantitatively predictive representation of the ion current. We fitted a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells overexpressing hERG1a. The model was then used to predict over 5 minutes of recordings in the same cell in response to further protocols: a series of traditional square step voltage clamps, and also a novel voltage clamp comprising a collection of physiologically relevant action potentials. We demonstrate that we can make predictive cell-specific models that outperform the use of averaged data from a number of different cells, and thereby examine which changes in gating are responsible for cell-cell variability in current kinetics. Our technique allows rapid collection of consistent and high quality data, from single cells, and produces more predictive mathematical ion channel models than traditional approaches. © 2018 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

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.

Imaging the beating heart in the mouse using intravital microscopy techniques

PubMed Central

Vinegoni, Claudio; Aguirre, Aaron D; Lee, Sungon; Weissleder, Ralph

2017-01-01

Real-time microscopic imaging of moving organs at single-cell resolution represents a major challenge in studying complex biology in living systems. Motion of the tissue from the cardiac and respiratory cycles severely limits intravital microscopy by compromising ultimate spatial and temporal imaging resolution. However, significant recent advances have enabled single-cell resolution imaging to be achieved in vivo. In this protocol, we describe experimental procedures for intravital microscopy based on a combination of thoracic surgery, tissue stabilizers and acquisition gating methods, which enable imaging at the single-cell level in the beating heart in the mouse. Setup of the model is typically completed in 1 h, which allows 2 h or more of continuous cardiac imaging. This protocol can be readily adapted for the imaging of other moving organs, and it will therefore broadly facilitate in vivo high-resolution microscopy studies. PMID:26492138

Rapid determination of cell mass and density using digitally controlled electric field in a microfluidic chip.

PubMed

Zhao, Yuliang; Lai, Hok Sum Sam; Zhang, Guanglie; Lee, Gwo-Bin; Li, Wen Jung

2014-11-21

The density of a single cell is a fundamental property of cells. Cells in the same cycle phase have similar volume, but the differences in their mass and density could elucidate each cell's physiological state. Here we report a novel technique to rapidly measure the density and mass of a single cell using an optically induced electrokinetics (OEK) microfluidic platform. Presently, single cellular mass and density measurement devices require a complicated fabrication process and their output is not scalable, i.e., it is extremely difficult to measure the mass and density of a large quantity of cells rapidly. The technique reported here operates on a principle combining sedimentation theory, computer vision, and microparticle manipulation techniques in an OEK microfluidic platform. We will show in this paper that this technique enables the measurement of single-cell volume, density, and mass rapidly and accurately in a repeatable manner. The technique is also scalable - it allows simultaneous measurement of volume, density, and mass of multiple cells. Essentially, a simple time-controlled projected light pattern is used to illuminate the selected area on the OEK microfluidic chip that contains cells to lift the cells to a particular height above the chip's surface. Then, the cells are allowed to "free fall" to the chip's surface, with competing buoyancy, gravitational, and fluidic drag forces acting on the cells. By using a computer vision algorithm to accurately track the motion of the cells and then relate the cells' motion trajectory to sedimentation theory, the volume, mass, and density of each cell can be rapidly determined. A theoretical model of micro-sized spheres settling towards an infinite plane in a microfluidic environment is first derived and validated experimentally using standard micropolystyrene beads to demonstrate the viability and accuracy of this new technique. Next, we show that the yeast cell volume, mass, and density could be rapidly determined using this technology, with results comparable to those using the existing method suspended microchannel resonator.

Real-time Attack of LL-37 on Single Bacillus subtilis Cells

PubMed Central

Barns, Kenneth J.; Weisshaar, James C.

2013-01-01

Time-lapse fluorescence microscopy of single, growing Bacillus subtilis cells with 2-12 s time resolution reveals the mechanisms of antimicrobial peptide (AMP) action on a Gram-positive species with unprecedented detail. For the human cathelicidin LL-37 attacking B. subtilis, the symptoms of antimicrobial stress differ dramatically depending on the bulk AMP concentration. At 2 μM LL-37, the mean single-cell growth rate decreases, but membrane permeabilization does not occur. At 4 μM LL-37, cells abruptly shrink in size at the same time that Sytox Green enters the cytoplasm and stains the nucleoids. We interpret the shrinkage event as loss of turgor pressure (and presumably the membrane potential) due to permeabilization of the membrane. Movies of Sytox Green staining at 0.5 frame/s show that nucleoid staining is initially local, more consistent with pore formation than with global permeabilization models. In a novel “growth recovery” assay, cells are incubated with LL-37 for a variable period and then rinsed with fresh growth medium lacking LL-37. The growth rate attenuation observed at 2 μM LL-37 is a recoverable symptom, while the abrupt cell shrinkage observed at 4 μM LL-37 is not. PMID:23454084

Lattice-cell orientation disorder in complex spinel oxides

DOE PAGES

Chen, Yan; Cheng, Yongqiang; Li, Juchuan; ...

2016-11-07

Transition metal (TM) substitution has been widely applied to change complex oxides crystal structures to create high energy density electrodes materials in high performance rechargeable lithium-ion batteries. The complex local structure in the oxides imparted by the TM arrangement often impacts their electrochemical behaviors by influencing the diffusion and intercalation of lithium. Here, a major discrepancy is demonstrated between the global and local structures of the promising high energy density and high voltage LiNi 0.5Mn 1.5O 4 spinel cathode material that contradicts the existing structural models. A new single-phase lattice-cell orientation disorder model is proposed as the mechanism for themore » local ordering that explains how the inhomogeneous local distortions and the coherent connection give rise to the global structure in the complex oxide. As a result, the single-phase model is consistent with the electrochemical behavior observation of the materials.« less

Raman-Activated Droplet Sorting (RADS) for Label-Free High-Throughput Screening of Microalgal Single-Cells.

PubMed

Wang, Xixian; Ren, Lihui; Su, Yetian; Ji, Yuetong; Liu, Yaoping; Li, Chunyu; Li, Xunrong; Zhang, Yi; Wang, Wei; Hu, Qiang; Han, Danxiang; Xu, Jian; Ma, Bo

2017-11-21

Raman-activated cell sorting (RACS) has attracted increasing interest, yet throughput remains one major factor limiting its broader application. Here we present an integrated Raman-activated droplet sorting (RADS) microfluidic system for functional screening of live cells in a label-free and high-throughput manner, by employing AXT-synthetic industrial microalga Haematococcus pluvialis (H. pluvialis) as a model. Raman microspectroscopy analysis of individual cells is carried out prior to their microdroplet encapsulation, which is then directly coupled to DEP-based droplet sorting. To validate the system, H. pluvialis cells containing different levels of AXT were mixed and underwent RADS. Those AXT-hyperproducing cells were sorted with an accuracy of 98.3%, an enrichment ratio of eight folds, and a throughput of ∼260 cells/min. Of the RADS-sorted cells, 92.7% remained alive and able to proliferate, which is equivalent to the unsorted cells. Thus, the RADS achieves a much higher throughput than existing RACS systems, preserves the vitality of cells, and facilitates seamless coupling with downstream manipulations such as single-cell sequencing and cultivation.

Single-Cell RNA Sequencing Reveals T Helper Cells Synthesizing Steroids De Novo to Contribute to Immune Homeostasis

PubMed Central

Mahata, Bidesh; Zhang, Xiuwei; Kolodziejczyk, Aleksandra A.; Proserpio, Valentina; Haim-Vilmovsky, Liora; Taylor, Angela E.; Hebenstreit, Daniel; Dingler, Felix A.; Moignard, Victoria; Göttgens, Berthold; Arlt, Wiebke; McKenzie, Andrew N.J.; Teichmann, Sarah A.

2014-01-01

Summary T helper 2 (Th2) cells regulate helminth infections, allergic disorders, tumor immunity, and pregnancy by secreting various cytokines. It is likely that there are undiscovered Th2 signaling molecules. Although steroids are known to be immunoregulators, de novo steroid production from immune cells has not been previously characterized. Here, we demonstrate production of the steroid pregnenolone by Th2 cells in vitro and in vivo in a helminth infection model. Single-cell RNA sequencing and quantitative PCR analysis suggest that pregnenolone synthesis in Th2 cells is related to immunosuppression. In support of this, we show that pregnenolone inhibits Th cell proliferation and B cell immunoglobulin class switching. We also show that steroidogenic Th2 cells inhibit Th cell proliferation in a Cyp11a1 enzyme-dependent manner. We propose pregnenolone as a “lymphosteroid,” a steroid produced by lymphocytes. We speculate that this de novo steroid production may be an intrinsic phenomenon of Th2-mediated immune responses to actively restore immune homeostasis. PMID:24813893

Automated analysis of siRNA screens of cells infected by hepatitis C and dengue viruses based on immunofluorescence microscopy images

NASA Astrophysics Data System (ADS)

Matula, Petr; Kumar, Anil; Wörz, Ilka; Harder, Nathalie; Erfle, Holger; Bartenschlager, Ralf; Eils, Roland; Rohr, Karl

2008-03-01

We present an image analysis approach as part of a high-throughput microscopy siRNA-based screening system using cell arrays for the identification of cellular genes involved in hepatitis C and dengue virus replication. Our approach comprises: cell nucleus segmentation, quantification of virus replication level in the neighborhood of segmented cell nuclei, localization of regions with transfected cells, cell classification by infection status, and quality assessment of an experiment and single images. In particular, we propose a novel approach for the localization of regions of transfected cells within cell array images, which combines model-based circle fitting and grid fitting. By this scheme we integrate information from single cell array images and knowledge from the complete cell arrays. The approach is fully automatic and has been successfully applied to a large number of cell array images from screening experiments. The experimental results show a good agreement with the expected behaviour of positive as well as negative controls and encourage the application to screens from further high-throughput experiments.

Atmospheric pressure reaction cell for operando sum frequency generation spectroscopy of ultrahigh vacuum grown model catalysts

NASA Astrophysics Data System (ADS)

Roiaz, Matteo; Pramhaas, Verena; Li, Xia; Rameshan, Christoph; Rupprechter, Günther

2018-04-01

A new custom-designed ultrahigh vacuum (UHV) chamber coupled to a UHV and atmospheric-pressure-compatible spectroscopic and catalytic reaction cell is described, which allows us to perform IR-vis sum frequency generation (SFG) vibrational spectroscopy during catalytic (kinetic) measurements. SFG spectroscopy is an exceptional tool to study vibrational properties of surface adsorbates under operando conditions, close to those of technical catalysis. This versatile setup allows performing surface science, SFG spectroscopy, catalysis, and electrochemical investigations on model systems, including single crystals, thin films, and deposited metal nanoparticles, under well-controlled conditions of gas composition, pressure, temperature, and potential. The UHV chamber enables us to prepare the model catalysts and to analyze their surface structure and composition by low energy electron diffraction and Auger electron spectroscopy, respectively. Thereafter, a sample transfer mechanism moves samples under UHV to the spectroscopic cell, avoiding air exposure. In the catalytic cell, SFG spectroscopy and catalytic tests (reactant/product analysis by mass spectrometry or gas chromatography) are performed simultaneously. A dedicated sample manipulation stage allows the model catalysts to be examined from LN2 temperature to 1273 K, with gaseous reactants in a pressure range from UHV to atmospheric. For post-reaction analysis, the SFG cell is rapidly evacuated and samples are transferred back to the UHV chamber. The capabilities of this new setup are demonstrated by benchmark results of CO adsorption on Pt and Pd(111) single crystal surfaces and of CO adsorption and oxidation on a ZrO2 supported Pt nanoparticle model catalyst grown by atomic layer deposition.

Advances in understanding tumour evolution through single-cell sequencing.

PubMed

Kuipers, Jack; Jahn, Katharina; Beerenwinkel, Niko

2017-04-01

The mutational heterogeneity observed within tumours poses additional challenges to the development of effective cancer treatments. A thorough understanding of a tumour's subclonal composition and its mutational history is essential to open up the design of treatments tailored to individual patients. Comparative studies on a large number of tumours permit the identification of mutational patterns which may refine forecasts of cancer progression, response to treatment and metastatic potential. The composition of tumours is shaped by evolutionary processes. Recent advances in next-generation sequencing offer the possibility to analyse the evolutionary history and accompanying heterogeneity of tumours at an unprecedented resolution, by sequencing single cells. New computational challenges arise when moving from bulk to single-cell sequencing data, leading to the development of novel modelling frameworks. In this review, we present the state of the art methods for understanding the phylogeny encoded in bulk or single-cell sequencing data, and highlight future directions for developing more comprehensive and informative pictures of tumour evolution. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Deterministic versus stochastic model of reprogramming: new evidence from cellular barcoding technique

PubMed Central

Yunusova, Anastasia M.; Fishman, Veniamin S.; Vasiliev, Gennady V.

2017-01-01

Factor-mediated reprogramming of somatic cells towards pluripotency is a low-efficiency process during which only small subsets of cells are successfully reprogrammed. Previous analyses of the determinants of the reprogramming potential are based on average measurements across a large population of cells or on monitoring a relatively small number of single cells with live imaging. Here, we applied lentiviral genetic barcoding, a powerful tool enabling the identification of familiar relationships in thousands of cells. High-throughput sequencing of barcodes from successfully reprogrammed cells revealed a significant number of barcodes from related cells. We developed a computer model, according to which a probability of synchronous reprogramming of sister cells equals 10–30%. We conclude that the reprogramming success is pre-established in some particular cells and, being a heritable trait, can be maintained through cell division. Thus, reprogramming progresses in a deterministic manner, at least at the level of cell lineages. PMID:28446707

The effects of RPM and recycle on separation efficiency in a clinical blood cell centrifuge.

PubMed

Drumheller, P D; Van Wie, B J; Petersen, J N; Oxford, R J; Schneider, G W

1987-11-01

A COBE blood cell centrifuge, model 2997 with a single stage channel, was modified to allow computer controlled sampling, and to allow recycle of red blood cells (RBCs) and plasma streams using bovine whole blood. The effects of recycle of the packed RBC and plasma product streams, and of the centrifuge RPM on platelet and white blood cell (WBC) separation efficiencies were quantified using a central composite factorial experimental design. These data were then fit using second order models. Both the model for the WBC separation efficiency and the model for the platelet separation efficiency predict that RPM has the greatest effect on separation efficiency and that RBC and plasma recycle have detrimental effects at moderate to low RPM, but have negligible impact on separation efficiency at high RPM.

A single-cell analysis platform for electrochemiluminescent detection of platelets adhesion to endothelial cells based on Au@DL-ZnCQDs nanoprobes.

PubMed

Long, Dongping; Shang, Yunfei; Qiu, Youyi; Zhou, Bin; Yang, Peihui

2018-04-15

A novel single-cell analysis platform (SCA) was developed for the investigation of platelets adhesion to single human umbilical vein endothelial cell (HUVEC) via using the adhesion molecule (E-selectin) on the damaged HUVEC as the marker site, and integrating electrochemiluminescence (ECL) with the ultrasensitive Au@DL-ZnCQDs nanoprobes. The Au@DL-ZnCQDs nanocomposite, a kind of double layer zinc-coadsorbed carbon quantum dot (ZnCQDs) core-shell nanoprobe, was firstly constructed by using gold nanoparticles (AuNPs) as the core to load with ZnCQDs and then the citrate-modified silver nanoparticles (AgNPs) as the bridge to link AuNPs-ZnCQDs with ZnCQDs to form the core-shell with double layer ZnCQDs (DL-ZnCQDs) nanoprobe, revealed a 10-fold signal amplification. The H 2 O 2 -induced oxidative damage HUVECs were utilized as the cellular model on which anti-E-selectin functionalized nanoprobes specially recognized E-selectin, the SCA showed that the ECL signals decreased with platelets adhesion to single HUVEC. The proposed SCA could effectively and dynamically monitor the adhesion between single HUVEC and platelets in the absence and presence of collagen activation, moreover, be able to quantitatively detect the number of platelets adhesion to single HUVEC, and show a good analytical performance with linear range from 1 to 15 platelets. In contrast, the HUVEC was down-regulated the expression of adhesion molecules by treating with quercetin inhibitor, and the SCA also exhibited the feasibility for analysis of platelets adhesion to single HUVEC. Therefore, the single-cell analysis platform provided a novel and promising protocol for analysis of the single intercellular adhesion, and it will be beneficial to elucidate the pathogenesis of cardiovascular diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

Photoacoustic bio-quantification of graphene based nanomaterials at a single cell level (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nedosekin, Dmitry A.; Nolan, Jacqueline; Biris, Alexandru S.; Zharov, Vladimir P.

2017-03-01

Arkansas Nanomedicine Center at the University of Arkansas for Medical Sciences in collaboration with other Arkansas Universities and the FDA-based National Center of Toxicological Research in Jefferson, AR is developing novel techniques for rapid quantification of graphene-based nanomaterials (GBNs) in various biological samples. All-carbon GBNs have wide range of potential applications in industry, agriculture, food processing and medicine; however, quantification of GBNs is difficult in carbon reach biological tissues. The accurate quantification of GBNs is essential for research on material toxicity and the development of GBNs-based drug delivery platforms. We have developed microscopy and cytometry platforms for detection and quantification of GBNs in single cells, tissue and blood samples using photoacoustic contrast of GBNs. We demonstrated PA quantification of individual graphene uptake by single cells. High-resolution PA microscopy provided mapping of GBN distribution within live cells to establish correlation with intracellular toxic phenomena using apoptotic and necrotic assays. This new methodology and corresponding technical platform provide the insight on possible toxicological risks of GBNs at singe cells levels. In addition, in vivo PA image flow cytometry demonstrated the capability to monitor of GBNs pharmacokinetics in mouse model and to map the resulting biodistribution of GBNs in mouse tissues. The integrated PA platform provided an unprecedented sensitivity toward GBNs and allowed to enhance conventional toxicology research by providing a direct correlation between uptake of GBNs at a single cell level and cell viability status.

Reprogramming cellular identity for regenerative medicine

PubMed Central

Cherry, Anne B.C.; Daley, George Q.

2012-01-01

The choreographed development of over 200 distinct differentiated cell types from a single zygote is a complex and poorly understood process. Whereas development leads unidirectionally towards more restricted cell fates, recent work in cellular reprogramming has proven that striking conversions of one cellular identity into another can be engineered, promising countless applications in biomedical research and paving the way for modeling disease with patient-derived stem cells. To date, there has been little discussion of which disease models are likely to be most informative. We here review evidence demonstrating that because environmental influences and epigenetic signatures are largely erased during reprogramming, patient-specific models of diseases with strong genetic bases and high penetrance are likely to prove most informative in the near term. However, manipulating in vitro culture conditions may ultimately enable cell-based models to recapitulate gene-environment interactions. Here, we discuss the implications of the new reprogramming paradigm in biomedicine and outline how reprogramming of cell identities is enhancing our understanding of cell differentiation and prospects for cellular therapies and in vivo regeneration. PMID:22424223