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

PubMed

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

2014-11-04

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

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

PubMed Central

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

2014-01-01

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

Single-cell sequencing in stem cell biology.

PubMed

Wen, Lu; Tang, Fuchou

2016-04-15

Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of stem cell populations, but these differences are masked when bulk cells are used for omic analysis. Single-cell sequencing technologies serve as powerful tools to dissect cellular heterogeneity comprehensively and to identify distinct phenotypic cell types, even within a 'homogeneous' stem cell population. These technologies, including single-cell genome, epigenome, and transcriptome sequencing technologies, have been developing rapidly in recent years. The application of these methods to different types of stem cells, including pluripotent stem cells and tissue-specific stem cells, has led to exciting new findings in the stem cell field. In this review, we discuss the recent progress as well as future perspectives in the methodologies and applications of single-cell omic sequencing technologies.

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.

Microfluidic Platform for Parallel Single Cell Analysis for Diagnostic Applications.

PubMed

Le Gac, Séverine

2017-01-01

Cell populations are heterogeneous: they can comprise different cell types or even cells at different stages of the cell cycle and/or of biological processes. Furthermore, molecular processes taking place in cells are stochastic in nature. Therefore, cellular analysis must be brought down to the single cell level to get useful insight into biological processes, and to access essential molecular information that would be lost when using a cell population analysis approach. Furthermore, to fully characterize a cell population, ideally, information both at the single cell level and on the whole cell population is required, which calls for analyzing each individual cell in a population in a parallel manner. This single cell level analysis approach is particularly important for diagnostic applications to unravel molecular perturbations at the onset of a disease, to identify biomarkers, and for personalized medicine, not only because of the heterogeneity of the cell sample, but also due to the availability of a reduced amount of cells, or even unique cells. This chapter presents a versatile platform meant for the parallel analysis of individual cells, with a particular focus on diagnostic applications and the analysis of cancer cells. We first describe one essential step of this parallel single cell analysis protocol, which is the trapping of individual cells in dedicated structures. Following this, we report different steps of a whole analytical process, including on-chip cell staining and imaging, cell membrane permeabilization and/or lysis using either chemical or physical means, and retrieval of the cell molecular content in dedicated channels for further analysis. This series of experiments illustrates the versatility of the herein-presented platform and its suitability for various analysis schemes and different analytical purposes.

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.

Research Techniques Made Simple: Single-Cell RNA Sequencing and its Applications in Dermatology.

PubMed

Wu, Xiaojun; Yang, Bin; Udo-Inyang, Imo; Ji, Suyun; Ozog, David; Zhou, Li; Mi, Qing-Sheng

2018-05-01

RNA sequencing is one of the most highly reliable and reproducible methods of assessing the cell transcriptome. As high-throughput RNA sequencing libraries at the single cell level have recently developed, single cell RNA sequencing has become more feasible and popular in biology research. Single cell RNA sequencing allows investigators to evaluate cell transcriptional profiles at the single cell level. It has become a very useful tool to perform investigations that could not be addressed by other methodologies, such as the assessment of cell-to-cell variation, the identification of rare populations, and the determination of heterogeneity within a cell population. So far, the single cell RNA sequencing technique has been widely applied to embryonic development, immune cell development, and human disease progress and treatment. Here, we describe the history of single cell technology development and its potential application in the field of dermatology. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

Wu, Jincheng; Tzanakakis, Emmanuel S.

2014-01-01

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

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

PubMed

Klein, Allon M; Mazutis, Linas; Akartuna, Ilke; Tallapragada, Naren; Veres, Adrian; Li, Victor; Peshkin, Leonid; Weitz, David A; Kirschner, Marc W

2015-05-21

It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT. Copyright © 2015 Elsevier Inc. All rights reserved.

A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa

PubMed Central

Petegrosso, Raphael; Tolar, Jakub

2018-01-01

Single-cell RNA sequencing (scRNA-seq) has been widely applied to discover new cell types by detecting sub-populations in a heterogeneous group of cells. Since scRNA-seq experiments have lower read coverage/tag counts and introduce more technical biases compared to bulk RNA-seq experiments, the limited number of sampled cells combined with the experimental biases and other dataset specific variations presents a challenge to cross-dataset analysis and discovery of relevant biological variations across multiple cell populations. In this paper, we introduce a method of variance-driven multitask clustering of single-cell RNA-seq data (scVDMC) that utilizes multiple single-cell populations from biological replicates or different samples. scVDMC clusters single cells in multiple scRNA-seq experiments of similar cell types and markers but varying expression patterns such that the scRNA-seq data are better integrated than typical pooled analyses which only increase the sample size. By controlling the variance among the cell clusters within each dataset and across all the datasets, scVDMC detects cell sub-populations in each individual experiment with shared cell-type markers but varying cluster centers among all the experiments. Applied to two real scRNA-seq datasets with several replicates and one large-scale droplet-based dataset on three patient samples, scVDMC more accurately detected cell populations and known cell markers than pooled clustering and other recently proposed scRNA-seq clustering methods. In the case study applied to in-house Recessive Dystrophic Epidermolysis Bullosa (RDEB) scRNA-seq data, scVDMC revealed several new cell types and unknown markers validated by flow cytometry. MATLAB/Octave code available at https://github.com/kuanglab/scVDMC. PMID:29630593

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.

Heterogeneity of Metazoan Cells and Beyond: To Integrative Analysis of Cellular Populations at Single-Cell Level.

PubMed

Barteneva, Natasha S; Vorobjev, Ivan A

2018-01-01

In this paper, we review some of the recent advances in cellular heterogeneity and single-cell analysis methods. In modern research of cellular heterogeneity, there are four major approaches: analysis of pooled samples, single-cell analysis, high-throughput single-cell analysis, and lately integrated analysis of cellular population at a single-cell level. Recently developed high-throughput single-cell genetic analysis methods such as RNA-Seq require purification step and destruction of an analyzed cell often are providing a snapshot of the investigated cell without spatiotemporal context. Correlative analysis of multiparameter morphological, functional, and molecular information is important for differentiation of more uniform groups in the spectrum of different cell types. Simplified distributions (histograms and 2D plots) can underrepresent biologically significant subpopulations. Future directions may include the development of nondestructive methods for dissecting molecular events in intact cells, simultaneous correlative cellular analysis of phenotypic and molecular features by hybrid technologies such as imaging flow cytometry, and further progress in supervised and non-supervised statistical analysis algorithms.

GiniClust: detecting rare cell types from single-cell gene expression data with Gini index.

PubMed

Jiang, Lan; Chen, Huidong; Pinello, Luca; Yuan, Guo-Cheng

2016-07-01

High-throughput single-cell technologies have great potential to discover new cell types; however, it remains challenging to detect rare cell types that are distinct from a large population. We present a novel computational method, called GiniClust, to overcome this challenge. Validation against a benchmark dataset indicates that GiniClust achieves high sensitivity and specificity. Application of GiniClust to public single-cell RNA-seq datasets uncovers previously unrecognized rare cell types, including Zscan4-expressing cells within mouse embryonic stem cells and hemoglobin-expressing cells in the mouse cortex and hippocampus. GiniClust also correctly detects a small number of normal cells that are mixed in a cancer cell population.

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.

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

PubMed Central

2017-01-01

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

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

PubMed

Thomas, Philipp

2017-11-01

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

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

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.

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.

Single cell gene expression profiling of cortical osteoblast lineage cells.

PubMed

Flynn, James M; Spusta, Steven C; Rosen, Clifford J; Melov, Simon

2013-03-01

In tissues with complex architectures such as bone, it is often difficult to purify and characterize specific cell types via molecular profiling. Single cell gene expression profiling is an emerging technology useful for characterizing transcriptional profiles of individual cells isolated from heterogeneous populations. In this study we describe a novel procedure for the isolation and characterization of gene expression profiles of single osteoblast lineage cells derived from cortical bone. Mixed populations of different cell types were isolated from adult long bones of C57BL/6J mice by enzymatic digestion, and subsequently subjected to FACS to purify and characterize osteoblast lineage cells via a selection strategy using antibodies against CD31, CD45, and alkaline phosphatase (AP), specific for mature osteoblasts. The purified individual osteoblast lineage cells were then profiled at the single cell level via nanofluidic PCR. This method permits robust gene expression profiling on single osteoblast lineage cells derived from mature bone, potentially from anatomically distinct sites. In conjunction with this technique, we have also shown that it is possible to carry out single cell profiling on cells purified from fixed and frozen bone samples without compromising the gene expression signal. The latter finding means the technique can be extended to biopsies of bone from diseased individuals. Our approach for single cell expression profiling provides a new dimension to the transcriptional profile of the primary osteoblast lineage population in vivo, and has the capacity to greatly expand our understanding of how these cells may function in vivo under normal and diseased states. Copyright © 2012 Elsevier Inc. 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 analysis of population context advances RNAi screening at multiple levels

PubMed Central

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

2012-01-01

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

Comparison of Normalized and Unnormalized Single Cell and Population Assemblies (MICW - Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Hugenholtz, Phil

2018-02-12

University of Queensland's Phil Hugenholtz on "Comparison of Normalized and Unnormalized Single Cell and Population Assemblies" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Massively parallel digital transcriptional profiling of single cells

PubMed Central

Zheng, Grace X. Y.; Terry, Jessica M.; Belgrader, Phillip; Ryvkin, Paul; Bent, Zachary W.; Wilson, Ryan; Ziraldo, Solongo B.; Wheeler, Tobias D.; McDermott, Geoff P.; Zhu, Junjie; Gregory, Mark T.; Shuga, Joe; Montesclaros, Luz; Underwood, Jason G.; Masquelier, Donald A.; Nishimura, Stefanie Y.; Schnall-Levin, Michael; Wyatt, Paul W.; Hindson, Christopher M.; Bharadwaj, Rajiv; Wong, Alexander; Ness, Kevin D.; Beppu, Lan W.; Deeg, H. Joachim; McFarland, Christopher; Loeb, Keith R.; Valente, William J.; Ericson, Nolan G.; Stevens, Emily A.; Radich, Jerald P.; Mikkelsen, Tarjei S.; Hindson, Benjamin J.; Bielas, Jason H.

2017-01-01

Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3′ mRNA counting of tens of thousands of single cells per sample. Cell encapsulation, of up to 8 samples at a time, takes place in ∼6 min, with ∼50% cell capture efficiency. To demonstrate the system's technical performance, we collected transcriptome data from ∼250k single cells across 29 samples. We validated the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. We profiled 68k peripheral blood mononuclear cells to demonstrate the system's ability to characterize large immune populations. Finally, we used sequence variation in the transcriptome data to determine host and donor chimerism at single-cell resolution from bone marrow mononuclear cells isolated from transplant patients. PMID:28091601

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.

Optimizing cryopreservation of human spermatogonial stem cells: comparing the effectiveness of testicular tissue and single cell suspension cryopreservation

PubMed Central

Yango, Pamela; Altman, Eran; Smith, James F.; Klatsky, Peter C.; Tran, Nam D.

2015-01-01

Objective To determine whether optimal human spermatogonial stem cell (SSC) cryopreservation is best achieved with testicular tissue or single cell suspension cryopreservation. This study compares the effectiveness between these two approaches by using testicular SSEA-4+ cells, a known population containing SSCs. Design In vitro human testicular tissues. Setting Academic research unit. Patients Adult testicular tissues (n = 4) collected from subjects with normal spermatogenesis and normal fetal testicular tissues (n = 3). Intervention(s) Testicular tissue vs. single cell suspension cryopreservation. Main Outcome Measures Cell viability, total cell recovery per milligram of tissue, as well as, viable and SSEA-4+ cell recovery. Results Single cell suspension cryopreservation yielded higher recovery of SSEA-4+ cells enriched in adult SSCs whereas fetal SSEA-4+ cell recovery was similar between testicular tissue and single cell suspension cryopreservation. Conclusions Adult and fetal human SSEA-4+ populations exhibited differential sensitivity to cryopreservation based on whether they were cryopreserved in situ as testicular tissues or as single cells. Thus, optimal preservation of human SSCs depends on the patient age, type of samples cryopreserved, and end points of therapeutic applications. PMID:25241367

Fundamental trade-offs between information flow in single cells and cellular populations.

PubMed

Suderman, Ryan; Bachman, John A; Smith, Adam; Sorger, Peter K; Deeds, Eric J

2017-05-30

Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

Microselection – affinity selecting antibodies against a single rare cell in a heterogeneous population

PubMed Central

Sørensen, Morten Dræby; Agerholm, Inge Errebo; Christensen, Britta; Kølvraa, Steen; Kristensen, Peter

2010-01-01

Abstract Rare cells not normally present in the peripheral bloodstream, such as circulating tumour cells, have potential applications for development of non-invasive methods for diagnostics or follow up. Obtaining these cells however require some means of discrimination, achievable by cell type specific antibodies. Here we have generated a microselection method allowing antibody selection, by phage display, targeting a single cell in a heterogeneous population. One K562 cell (female origin) was positioned on glass slide among millions of lymphocytes from male donor, identifying the K562 cell by FISH (XX). Several single cell selections were performed on such individual slides. The phage particles bound to the target cell is protected by a minute disc, while inactivating all remaining phage by UV-irradiation; leaving only the phage bound to the target cell viable. We hereby retrieved up to eight antibodies per single cell selection, including three highly K562 cell type specific. PMID:20726925

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.

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.

Single-cell copy number variation detection

PubMed Central

2011-01-01

Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data. PMID:21854607

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.

Universal Temporal Profile of Replication Origin Activation in Eukaryotes

NASA Astrophysics Data System (ADS)

Goldar, Arach

2011-03-01

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

Characterization of rabbit limbal epithelial side population cells using RNA sequencing and single-cell qRT-PCR.

PubMed

Kameishi, Sumako; Umemoto, Terumasa; Matsuzaki, Yu; Fujita, Masako; Okano, Teruo; Kato, Takashi; Yamato, Masayuki

2016-05-06

Corneal epithelial stem cells reside in the limbus, a transitional zone between the cornea and conjunctiva, and are essential for maintaining homeostasis in the corneal epithelium. Although our previous studies demonstrated that rabbit limbal epithelial side population (SP) cells exhibit stem cell-like phenotypes with Hoechst 33342 staining, the different characteristics and/or populations of these cells remain unclear. Therefore, in this study, we determined the gene expression profiles of limbal epithelial SP cells by RNA sequencing using not only present public databases but also contigs that were created by de novo transcriptome assembly as references for mapping. Our transcriptome data indicated that limbal epithelial SP cells exhibited a stem cell-like phenotype compared with non-SP cells. Importantly, gene ontology analysis following RNA sequencing demonstrated that limbal epithelial SP cells exhibited significantly enhanced expression of mesenchymal/endothelial cell markers rather than epithelial cell markers. Furthermore, single-cell quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) demonstrated that the limbal epithelial SP population consisted of at least two immature cell populations with endothelial- or mesenchymal-like phenotypes. Therefore, our present results may propose the presence of a novel population of corneal epithelial stem cells distinct from conventional epithelial stem cells. Copyright © 2015 Elsevier Inc. All rights reserved.

Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia.

PubMed

Giustacchini, Alice; Thongjuea, Supat; Barkas, Nikolaos; Woll, Petter S; Povinelli, Benjamin J; Booth, Christopher A G; Sopp, Paul; Norfo, Ruggiero; Rodriguez-Meira, Alba; Ashley, Neil; Jamieson, Lauren; Vyas, Paresh; Anderson, Kristina; Segerstolpe, Åsa; Qian, Hong; Olsson-Strömberg, Ulla; Mustjoki, Satu; Sandberg, Rickard; Jacobsen, Sten Eirik W; Mead, Adam J

2017-06-01

Recent advances in single-cell transcriptomics are ideally placed to unravel intratumoral heterogeneity and selective resistance of cancer stem cell (SC) subpopulations to molecularly targeted cancer therapies. However, current single-cell RNA-sequencing approaches lack the sensitivity required to reliably detect somatic mutations. We developed a method that combines high-sensitivity mutation detection with whole-transcriptome analysis of the same single cell. We applied this technique to analyze more than 2,000 SCs from patients with chronic myeloid leukemia (CML) throughout the disease course, revealing heterogeneity of CML-SCs, including the identification of a subgroup of CML-SCs with a distinct molecular signature that selectively persisted during prolonged therapy. Analysis of nonleukemic SCs from patients with CML also provided new insights into cell-extrinsic disruption of hematopoiesis in CML associated with clinical outcome. Furthermore, we used this single-cell approach to identify a blast-crisis-specific SC population, which was also present in a subclone of CML-SCs during the chronic phase in a patient who subsequently developed blast crisis. This approach, which might be broadly applied to any malignancy, illustrates how single-cell analysis can identify subpopulations of therapy-resistant SCs that are not apparent through cell-population analysis.

Single-Cell RNA Sequencing of Glioblastoma Cells.

PubMed

Sen, Rajeev; Dolgalev, Igor; Bayin, N Sumru; Heguy, Adriana; Tsirigos, Aris; Placantonakis, Dimitris G

2018-01-01

Single-cell RNA sequencing (sc-RNASeq) is a recently developed technique used to evaluate the transcriptome of individual cells. As opposed to conventional RNASeq in which entire populations are sequenced in bulk, sc-RNASeq can be beneficial when trying to better understand gene expression patterns in markedly heterogeneous populations of cells or when trying to identify transcriptional signatures of rare cells that may be underrepresented when using conventional bulk RNASeq. In this method, we describe the generation and analysis of cDNA libraries from single patient-derived glioblastoma cells using the C1 Fluidigm system. The protocol details the use of the C1 integrated fluidics circuit (IFC) for capturing, imaging and lysing cells; performing reverse transcription; and generating cDNA libraries that are ready for sequencing and analysis.

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

PubMed

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

2017-12-15

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

Quantification of multiple gene expression in individual cells.

PubMed

Peixoto, António; Monteiro, Marta; Rocha, Benedita; Veiga-Fernandes, Henrique

2004-10-01

Quantitative gene expression analysis aims to define the gene expression patterns determining cell behavior. So far, these assessments can only be performed at the population level. Therefore, they determine the average gene expression within a population, overlooking possible cell-to-cell heterogeneity that could lead to different cell behaviors/cell fates. Understanding individual cell behavior requires multiple gene expression analyses of single cells, and may be fundamental for the understanding of all types of biological events and/or differentiation processes. We here describe a new reverse transcription-polymerase chain reaction (RT-PCR) approach allowing the simultaneous quantification of the expression of 20 genes in the same single cell. This method has broad application, in different species and any type of gene combination. RT efficiency is evaluated. Uniform and maximized amplification conditions for all genes are provided. Abundance relationships are maintained, allowing the precise quantification of the absolute number of mRNA molecules per cell, ranging from 2 to 1.28 x 10(9) for each individual gene. We evaluated the impact of this approach on functional genetic read-outs by studying an apparently homogeneous population (monoclonal T cells recovered 4 d after antigen stimulation), using either this method or conventional real-time RT-PCR. Single-cell studies revealed considerable cell-to-cell variation: All T cells did not express all individual genes. Gene coexpression patterns were very heterogeneous. mRNA copy numbers varied between different transcripts and in different cells. As a consequence, this single-cell assay introduces new and fundamental information regarding functional genomic read-outs. By comparison, we also show that conventional quantitative assays determining population averages supply insufficient information, and may even be highly misleading.

An integrated microfluidic chip system for single-cell secretion profiling of rare circulating tumor cells.

PubMed

Deng, Yuliang; Zhang, Yu; Sun, Shuai; Wang, Zhihua; Wang, Minjiao; Yu, Beiqin; Czajkowsky, Daniel M; Liu, Bingya; Li, Yan; Wei, Wei; Shi, Qihui

2014-12-16

Genetic and transcriptional profiling, as well as surface marker identification of single circulating tumor cells (CTCs) have been demonstrated. However, quantitatively profiling of functional proteins at single CTC resolution has not yet been achieved, owing to the limited purity of the isolated CTC populations and a lack of single-cell proteomic approaches to handle and analyze rare CTCs. Here, we develop an integrated microfluidic system specifically designed for streamlining isolation, purification and single-cell secretomic profiling of CTCs from whole blood. Key to this platform is the use of photocleavable ssDNA-encoded antibody conjugates to enable a highly purified CTC population with <75 'contaminated' blood cells. An enhanced poly-L-lysine barcode pattern is created on the single-cell barcode chip for efficient capture rare CTC cells in microchambers for subsequent secreted protein profiling. This system was extensively evaluated and optimized with EpCAM-positive HCT116 cells seeded into whole blood. Patient blood samples were employed to assess the utility of the system for isolation, purification and single-cell secretion profiling of CTCs. The CTCs present in patient blood samples exhibit highly heterogeneous secretion profile of IL-8 and VEGF. The numbers of secreting CTCs are found not in accordance with CTC enumeration based on immunostaining in the parallel experiments.

An Integrated Microfluidic Chip System for Single-Cell Secretion Profiling of Rare Circulating Tumor Cells

PubMed Central

Deng, Yuliang; Zhang, Yu; Sun, Shuai; Wang, Zhihua; Wang, Minjiao; Yu, Beiqin; Czajkowsky, Daniel M.; Liu, Bingya; Li, Yan; Wei, Wei; Shi, Qihui

2014-01-01

Genetic and transcriptional profiling, as well as surface marker identification of single circulating tumor cells (CTCs) have been demonstrated. However, quantitatively profiling of functional proteins at single CTC resolution has not yet been achieved, owing to the limited purity of the isolated CTC populations and a lack of single-cell proteomic approaches to handle and analyze rare CTCs. Here, we develop an integrated microfluidic system specifically designed for streamlining isolation, purification and single-cell secretomic profiling of CTCs from whole blood. Key to this platform is the use of photocleavable ssDNA-encoded antibody conjugates to enable a highly purified CTC population with <75 ‘contaminated' blood cells. An enhanced poly-L-lysine barcode pattern is created on the single-cell barcode chip for efficient capture rare CTC cells in microchambers for subsequent secreted protein profiling. This system was extensively evaluated and optimized with EpCAM-positive HCT116 cells seeded into whole blood. Patient blood samples were employed to assess the utility of the system for isolation, purification and single-cell secretion profiling of CTCs. The CTCs present in patient blood samples exhibit highly heterogeneous secretion profile of IL-8 and VEGF. The numbers of secreting CTCs are found not in accordance with CTC enumeration based on immunostaining in the parallel experiments. PMID:25511131

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Diversity in ATP concentrations in a single bacterial cell population revealed by quantitative single-cell imaging

PubMed Central

Yaginuma, Hideyuki; Kawai, Shinnosuke; Tabata, Kazuhito V.; Tomiyama, Keisuke; Kakizuka, Akira; Komatsuzaki, Tamiki; Noji, Hiroyuki; Imamura, Hiromi

2014-01-01

Recent advances in quantitative single-cell analysis revealed large diversity in gene expression levels between individual cells, which could affect the physiology and/or fate of each cell. In contrast, for most metabolites, the concentrations were only measureable as ensemble averages of many cells. In living cells, adenosine triphosphate (ATP) is a critically important metabolite that powers many intracellular reactions. Quantitative measurement of the absolute ATP concentration in individual cells has not been achieved because of the lack of reliable methods. In this study, we developed a new genetically-encoded ratiometric fluorescent ATP indicator “QUEEN”, which is composed of a single circularly-permuted fluorescent protein and a bacterial ATP binding protein. Unlike previous FRET-based indicators, QUEEN was apparently insensitive to bacteria growth rate changes. Importantly, intracellular ATP concentrations of numbers of bacterial cells calculated from QUEEN fluorescence were almost equal to those from firefly luciferase assay. Thus, QUEEN is suitable for quantifying the absolute ATP concentration inside bacteria cells. Finally, we found that, even for a genetically-identical Escherichia coli cell population, absolute concentrations of intracellular ATP were significantly diverse between individual cells from the same culture, by imaging QUEEN signals from single cells. PMID:25283467

Single-Cell RNA-Seq Reveals the Transcriptional Landscape and Heterogeneity of Aortic Macrophages in Murine Atherosclerosis.

PubMed

Cochain, Clément; Vafadarnejad, Ehsan; Arampatzi, Panagiota; Jaroslav, Pelisek; Winkels, Holger; Ley, Klaus; Wolf, Dennis; Saliba, Antoine-Emmanuel; Zernecke, Alma

2018-03-15

Rationale: It is assumed that atherosclerotic arteries contain several macrophage subsets endowed with specific functions. The precise identity of these subsets is poorly characterized as they ha ve been defined by the expression of a restricted number of markers. Objective: We have applied single-cell RNA-seq as an unbiased profiling strategy to interrogate and classify aortic macrophage heterogeneity at the single-cell level in atherosclerosis. Methods and Results: We performed single-cell RNA sequencing of total aortic CD45 + cells extracted from the non-diseased (chow fed) and atherosclerotic (11 weeks of high fat diet) aorta of Ldlr -/- mice. Unsupervised clustering singled out 13 distinct aortic cell clusters. Among the myeloid cell populations, Resident-like macrophages with a gene expression profile similar to aortic resident macrophages were found in healthy and diseased aortae, whereas monocytes, monocyte-derived dendritic cells (MoDC), and two populations of macrophages were almost exclusively detectable in atherosclerotic aortae, comprising Inflammatory macrophages showing enrichment in I l1b , and previously undescribed TREM2 hi macrophages. Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these three macrophage subsets and MoDC, and uncovered putative functions of each cell type. Notably, TREM2 hi macrophages appeared to be endowed with specialized functions in lipid metabolism and catabolism, and presented a gene expression signature reminiscent of osteoclasts, suggesting a role in lesion calcification. TREM2 expression was moreover detected in human lesional macrophages. Importantly, these macrophage populations were present also in advanced atherosclerosis and in Apoe -/- aortae, indicating relevance of our findings in different stages of atherosclerosis and mouse models. Conclusions: These data unprecedentedly uncovered the transcriptional landscape and phenotypic heterogeneity of aortic macrophages and MoDCs in atherosclerotic and identified previously unrecognized macrophage populations and their gene expression signature, suggesting specialized functions. Our findings will open up novel opportunities to explore distinct myeloid cell populations and their functions in atherosclerosis.

Interrogating the variation of element masses and distribution patterns in single cells using ICP-MS with a high efficiency cell introduction system.

PubMed

Wang, Hailong; Wang, Meng; Wang, Bing; Zheng, Lingna; Chen, Hanqing; Chai, Zhifang; Feng, Weiyue

2017-02-01

Cellular heterogeneity is an inherent condition of cell populations, which results from stochastic expression of genes, proteins, and metabolites. The heterogeneity of individual cells can dramatically influence cellular decision-making and cell fate. So far, our knowledge about how the variation of endogenous metals and non-metals in individual eukaryotic cells is limited. In this study, ICP-MS equipped with a high efficiency cell introduction system (HECIS) was developed as a method of single-cell ICP-MS (SC-ICP-MS). The method was applied to the single-cell analysis of Mn, Fe, Co, Cu, Zn, P, and S in human cancer cell lines (HeLa and A549) and normal human bronchial epithelial cell line (16HBE). The analysis showed obvious variation of the masses of Cu, Fe, Zn, and P in individual HeLa cells, and variation of Fe, Zn, and P in individual A549 cells. On the basis of the single-cell data, a multimodal distribution of the elements in the cell population was fitted, which showed marked differences among the various cell lines. Importantly, subpopulations of the elements were found in the cell populations, especially in the HeLa cancer cells. This study demonstrates that SC-ICP-MS is able to unravel the extent of variation of endogenous elements in individual cells, which will help to improve our fundamental understanding of cellular biology and reveal novel insights into human biology and medicine. Graphical abstract The variations of masses and distribution patterns of elements Mn, Fe, Co, Cu, Zn, P, and S in single cells were successfully detected by ICP-MS coupled with a high efficiency cell introduction system (HECIS).

Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells

PubMed Central

Han, Lin; Wu, Hua-Jun; Zhu, Haiying; Kim, Kun-Yong; Marjani, Sadie L.; Riester, Markus; Euskirchen, Ghia; Zi, Xiaoyuan; Yang, Jennifer; Han, Jasper; Snyder, Michael; Park, In-Hyun; Irizarry, Rafael; Weissman, Sherman M.

2017-01-01

Abstract Conventional DNA bisulfite sequencing has been extended to single cell level, but the coverage consistency is insufficient for parallel comparison. Here we report a novel method for genome-wide CpG island (CGI) methylation sequencing for single cells (scCGI-seq), combining methylation-sensitive restriction enzyme digestion and multiple displacement amplification for selective detection of methylated CGIs. We applied this method to analyzing single cells from two types of hematopoietic cells, K562 and GM12878 and small populations of fibroblasts and induced pluripotent stem cells. The method detected 21 798 CGIs (76% of all CGIs) per cell, and the number of CGIs consistently detected from all 16 profiled single cells was 20 864 (72.7%), with 12 961 promoters covered. This coverage represents a substantial improvement over results obtained using single cell reduced representation bisulfite sequencing, with a 66-fold increase in the fraction of consistently profiled CGIs across individual cells. Single cells of the same type were more similar to each other than to other types, but also displayed epigenetic heterogeneity. The method was further validated by comparing the CpG methylation pattern, methylation profile of CGIs/promoters and repeat regions and 41 classes of known regulatory markers to the ENCODE data. Although not every minor methylation differences between cells are detectable, scCGI-seq provides a solid tool for unsupervised stratification of a heterogeneous cell population. PMID:28126923

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.

Isolation and gene expression analysis of single potential human spermatogonial stem cells.

PubMed

von Kopylow, K; Schulze, W; Salzbrunn, A; Spiess, A-N

2016-04-01

It is possible to isolate pure populations of single potential human spermatogonial stem cells without somatic contamination for down-stream applications, for example cell culture and gene expression analysis. We isolated pure populations of single potential human spermatogonial stem cells (hSSC) without contaminating somatic cells and analyzed gene expression of these cells via single-cell real-time RT-PCR. The isolation of a pure hSSC fraction could enable clinical applications such as fertility preservation for prepubertal boys and in vitro-spermatogenesis. By utilizing largely nonspecific markers for the isolation of spermatogonia (SPG) and hSSC, previously published cell selection methods are not able to deliver pure target cell populations without contamination by testicular somatic cells. However, uniform cell populations free of somatic cells are necessary to guarantee defined growth conditions in cell culture experiments and to prevent unintended stem cell differentiation. Fibroblast growth factor receptor 3 (FGFR3) is a cell surface protein of human undifferentiated A-type SPG and a promising candidate marker for hSSC. It is exclusively expressed in small, non-proliferating subgroups of this spermatogonial cell type together with the pluripotency-associated protein and spermatogonial nuclear marker undifferentiated embryonic cell transcription factor 1 (UTF1). We specifically selected the FGFR3-positive spermatogonial subpopulation from two 30 mg biopsies per patient from a total of 37 patients with full spermatogenesis and three patients with meiotic arrest. We then employed cell selection with magnetic beads in combination with a fluorescence-activated cell sorter antibody directed against human FGFR3 to tag and visually identify human FGFR3-positive spermatogonia. Positively selected and bead-labeled cells were subsequently picked with a micromanipulator. Analysis of the isolated cells was carried out by single-cell real-time RT-PCR, real-time RT-PCR, immunocytochemistry and live/dead staining. Single-cell real-time RT-PCR and real-time RT-PCR of pooled cells indicate that bead-labeled single cells express FGFR3 with high heterogeneity at the mRNA level, while bead-unlabeled cells lack FGFR3 mRNA. Furthermore, isolated cells exhibit strong immunocytochemical staining for the stem cell factor UTF1 and are viable. The cell population isolated in this study has to be tested for their potential stem cell characteristics via xenotransplantation. Due to the small amount of the isolated cells, propagation by cell culture will be essential. Other potential hSSC without FGFR3 surface expression will not be captured with the provided experimental design. The technical approach as developed in this work could encourage the scientific community to test other established or novel hSSC markers on single SPG that present with potential stem cell-like features. The project was funded by the DFG Research Unit FOR1041 Germ cell potential (SCH 587/3-2) and DFG grants to K.v.K. (KO 4769/2-1) and A.-N.S. (SP 721/4-1). The authors declare no competing interests. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Identification and genetic analysis of cancer cells with PCR-activated cell sorting

PubMed Central

Eastburn, Dennis J.; Sciambi, Adam; Abate, Adam R.

2014-01-01

Cell sorting is a central tool in life science research for analyzing cellular heterogeneity or enriching rare cells out of large populations. Although methods like FACS and FISH-FC can characterize and isolate cells from heterogeneous populations, they are limited by their reliance on antibodies, or the requirement to chemically fix cells. We introduce a new cell sorting technology that robustly sorts based on sequence-specific analysis of cellular nucleic acids. Our approach, PCR-activated cell sorting (PACS), uses TaqMan PCR to detect nucleic acids within single cells and trigger their sorting. With this method, we identified and sorted prostate cancer cells from a heterogeneous population by performing >132 000 simultaneous single-cell TaqMan RT-PCR reactions targeting vimentin mRNA. Following vimentin-positive droplet sorting and downstream analysis of recovered nucleic acids, we found that cancer-specific genomes and transcripts were significantly enriched. Additionally, we demonstrate that PACS can be used to sort and enrich cells via TaqMan PCR reactions targeting single-copy genomic DNA. PACS provides a general new technical capability that expands the application space of cell sorting by enabling sorting based on cellular information not amenable to existing approaches. PMID:25030902

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.

Comparison of EpCAMhighCD44+ cancer stem cells with EpCAMhighCD44- tumor cells in colon cancer by single-cell sequencing.

PubMed

Liu, Mingshan; Di, Jiabo; Liu, Yang; Su, Zhe; Jiang, Beihai; Wang, Zaozao; Su, Xiangqian

2018-03-26

Cancer stem cells (CSCs) are considered to be responsible for tumorigenesis and cancer relapse. EpCAM high CD44 + tumor cells are putative colorectal CSCs that express high levels of stem cell genes, while the EpCAM high CD44 - population mostly contains differentiated tumor cells (DTCs). This study aims to determine whether single CSC (EpCAM high CD44 + ) and DTC (EpCAM high CD44 - ) can be distinguished in terms of somatic copy number alterations (SCNAs). We applied fluorescence-activated cell sorting to isolate the CD45 - EpCAM high CD44 + and CD45 - EpCAM high CD44 - populations from two primary colon tumors, on which low-coverage single-cell whole-genome sequencing (WGS) was then performed ∼0.1x depth. We compared the SCNAs of the CSCs and DTCs at single-cell resolution. In total, 47 qualified single cells of the two populations underwent WGS. The single-cell SCNA profiles showed that there were obvious SCNAs in both the CSCs and DTCs of each patient, and each patient had a specific copy number alteration pattern. Hierarchical clustering and correlation analysis both showed that the SCNA profiles of CSCs and DTCs from the same patient had similar SCNA pattern, while there were regional differences in the CSCs and DTCs in certain patient. SCNAs of CSCs in the same patient were highly reproducible. Our data suggest that major SCNAs occurred at an early stage and were inherited steadily. The similarity of ubiquitous SCNAs between the CSCs and DTCs might have arisen from lineage differentiation. CSCs from the same patient had reproducible SCNA profiles, indicating that gain or loss in certain chromosome is required for colon cancer development.

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

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.

Flow cytometric single cell analysis reveals heterogeneity between adipose depots

PubMed Central

Boumelhem, Badwi B.; Assinder, Stephen J.; Bell-Anderson, Kim S.; Fraser, Stuart T.

2017-01-01

ABSTRACT Understanding adipose tissue heterogeneity is hindered by the paucity of methods to analyze mature adipocytes at the single cell level. Here, we report a system for analyzing live adipocytes from different adipose depots in the adult mouse. Single cell suspensions of buoyant adipocytes were separated from the stromal vascular fraction and analyzed by flow cytometry. Compared to other lipophilic dyes, Nile Red uptake effectively distinguished adipocyte populations. Nile Red fluorescence increased with adipocyte size and granularity and could be combined with MitoTracker® Deep Red or fluorescent antibody labeling to further dissect adipose populations. Epicardial adipocytes exhibited the least mitochondrial membrane depolarization and highest fatty-acid translocase CD36 surface expression. In contrast, brown adipocytes showed low surface CD36 expression. Pregnancy resulted in reduced mitochondrial membrane depolarisation and increased CD36 surface expression in brown and epicardial adipocyte populations respectively. Our protocol revealed unreported heterogeneity between adipose depots and highlights the utility of flow cytometry for screening adipocytes at the single cell level. PMID:28453382

In silico lineage tracing through single cell transcriptomics identifies a neural stem cell population in planarians.

PubMed

Molinaro, Alyssa M; Pearson, Bret J

2016-04-27

The planarian Schmidtea mediterranea is a master regenerator with a large adult stem cell compartment. The lack of transgenic labeling techniques in this animal has hindered the study of lineage progression and has made understanding the mechanisms of tissue regeneration a challenge. However, recent advances in single-cell transcriptomics and analysis methods allow for the discovery of novel cell lineages as differentiation progresses from stem cell to terminally differentiated cell. Here we apply pseudotime analysis and single-cell transcriptomics to identify adult stem cells belonging to specific cellular lineages and identify novel candidate genes for future in vivo lineage studies. We purify 168 single stem and progeny cells from the planarian head, which were subjected to single-cell RNA sequencing (scRNAseq). Pseudotime analysis with Waterfall and gene set enrichment analysis predicts a molecularly distinct neoblast sub-population with neural character (νNeoblasts) as well as a novel alternative lineage. Using the predicted νNeoblast markers, we demonstrate that a novel proliferative stem cell population exists adjacent to the brain. scRNAseq coupled with in silico lineage analysis offers a new approach for studying lineage progression in planarians. The lineages identified here are extracted from a highly heterogeneous dataset with minimal prior knowledge of planarian lineages, demonstrating that lineage purification by transgenic labeling is not a prerequisite for this approach. The identification of the νNeoblast lineage demonstrates the usefulness of the planarian system for computationally predicting cellular lineages in an adult context coupled with in vivo verification.

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

PubMed

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

2016-11-23

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

In Situ Probing of Cholesterol in Astrocytes at the Single Cell Level using Laser Desorption Ionization Mass Spectrometric Imaging with Colloidal Silver

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

Perdian, D.C.; Cha, Sangwon; Oh, Jisun

2010-03-18

Mass spectrometric imaging has been utilized to localize individual astrocytes and to obtain cholesterol populations at the single-cell level in laser desorption ionization (LDI) with colloidal silver. The silver ion adduct of membrane-bound cholesterol was monitored to detect individual cells. Good correlation between mass spectrometric and optical images at different cell densities indicates the ability to perform single-cell studies of cholesterol abundance. The feasibility of quantification is confirmed by the agreement between the LDI-MS ion signals and the results from a traditional enzymatic fluorometric assay. We propose that this approach could be an effective tool to study chemical populations atmore » the cellular level.« less

Single-Cell Genomic Analysis in Plants

PubMed Central

Hu, Haifei; Scheben, Armin; Edwards, David

2018-01-01

Individual cells in an organism are variable, which strongly impacts cellular processes. Advances in sequencing technologies have enabled single-cell genomic analysis to become widespread, addressing shortcomings of analyses conducted on populations of bulk cells. While the field of single-cell plant genomics is in its infancy, there is great potential to gain insights into cell lineage and functional cell types to help understand complex cellular interactions in plants. In this review, we discuss current approaches for single-cell plant genomic analysis, with a focus on single-cell isolation, DNA amplification, next-generation sequencing, and bioinformatics analysis. We outline the technical challenges of analysing material from a single plant cell, and then examine applications of single-cell genomics and the integration of this approach with genome editing. Finally, we indicate future directions we expect in the rapidly developing field of plant single-cell genomic analysis. PMID:29361790

One Bacterial Cell, One Complete Genome

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

Woyke, Tanja; Tighe, Damon; Mavrommatis, Konstantinos

2010-04-26

While the bulk of the finished microbial genomes sequenced to date are derived from cultured bacterial and archaeal representatives, the vast majority of microorganisms elude current culturing attempts, severely limiting the ability to recover complete or even partial genomes from these environmental species. Single cell genomics is a novel culture-independent approach, which enables access to the genetic material of an individual cell. No single cell genome has to our knowledge been closed and finished to date. Here we report the completed genome from an uncultured single cell of Candidatus Sulcia muelleri DMIN. Digital PCR on single symbiont cells isolated frommore » the bacteriome of the green sharpshooter Draeculacephala minerva bacteriome allowed us to assess that this bacteria is polyploid with genome copies ranging from approximately 200?900 per cell, making it a most suitable target for single cell finishing efforts. For single cell shotgun sequencing, an individual Sulcia cell was isolated and whole genome amplified by multiple displacement amplification (MDA). Sanger-based finishing methods allowed us to close the genome. To verify the correctness of our single cell genome and exclude MDA-derived artifacts, we independently shotgun sequenced and assembled the Sulcia genome from pooled bacteriomes using a metagenomic approach, yielding a nearly identical genome. Four variations we detected appear to be genuine biological differences between the two samples. Comparison of the single cell genome with bacteriome metagenomic sequence data detected two single nucleotide polymorphisms (SNPs), indicating extremely low genetic diversity within a Sulcia population. This study demonstrates the power of single cell genomics to generate a complete, high quality, non-composite reference genome within an environmental sample, which can be used for population genetic analyzes.« less

Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells.

PubMed

Han, Lin; Wu, Hua-Jun; Zhu, Haiying; Kim, Kun-Yong; Marjani, Sadie L; Riester, Markus; Euskirchen, Ghia; Zi, Xiaoyuan; Yang, Jennifer; Han, Jasper; Snyder, Michael; Park, In-Hyun; Irizarry, Rafael; Weissman, Sherman M; Michor, Franziska; Fan, Rong; Pan, Xinghua

2017-06-02

Conventional DNA bisulfite sequencing has been extended to single cell level, but the coverage consistency is insufficient for parallel comparison. Here we report a novel method for genome-wide CpG island (CGI) methylation sequencing for single cells (scCGI-seq), combining methylation-sensitive restriction enzyme digestion and multiple displacement amplification for selective detection of methylated CGIs. We applied this method to analyzing single cells from two types of hematopoietic cells, K562 and GM12878 and small populations of fibroblasts and induced pluripotent stem cells. The method detected 21 798 CGIs (76% of all CGIs) per cell, and the number of CGIs consistently detected from all 16 profiled single cells was 20 864 (72.7%), with 12 961 promoters covered. This coverage represents a substantial improvement over results obtained using single cell reduced representation bisulfite sequencing, with a 66-fold increase in the fraction of consistently profiled CGIs across individual cells. Single cells of the same type were more similar to each other than to other types, but also displayed epigenetic heterogeneity. The method was further validated by comparing the CpG methylation pattern, methylation profile of CGIs/promoters and repeat regions and 41 classes of known regulatory markers to the ENCODE data. Although not every minor methylation differences between cells are detectable, scCGI-seq provides a solid tool for unsupervised stratification of a heterogeneous cell population. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Plasmonic imaging of protein interactions with single bacterial cells.

PubMed

Syal, Karan; Wang, Wei; Shan, Xiaonan; Wang, Shaopeng; Chen, Hong-Yuan; Tao, Nongjian

2015-01-15

Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population. Copyright © 2014 Elsevier B.V. All rights reserved.

Advanced Method for Isolation of Mouse Hepatocytes, Liver Sinusoidal Endothelial Cells, and Kupffer Cells.

PubMed

Liu, Jia; Huang, Xuan; Werner, Melanie; Broering, Ruth; Yang, Dongliang; Lu, Mengji

2017-01-01

Separation of pure cell populations from the liver is a prerequisite to study the role of hepatic parenchymal and non-parenchymal cells in liver physiology, pathophysiology, and immunology. Traditional methods for hepatic cell separation usually purify only single cell types from liver specimens. Here, we describe an efficient method that can simultaneously purify populations of hepatocytes (HCs), liver sinusoidal endothelial cells (LSECs), and Kupffer cells (KCs) from a single mouse liver specimen. A liberase-based perfusion technique in combination with a low-speed centrifugation and magnetic-activated cell sorting (MACS) led to the isolation and purification of HCs, KCs, and LSECs with high yields and purity.

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

PubMed

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

2014-01-28

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

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.

A transdisciplinary approach to the initial validation of a single cell protein as an alternative protein source for use in aquafeeds

USDA-ARS?s Scientific Manuscript database

The human population is growing and, globally, we must meet the challenge of increased protein needs required to feed this population. Single cell proteins (SCP), when coupled to aquaculture production, offers a means to ensure future protein needs can be met without direct competition with food for...

Droplet Microarray Based on Superhydrophobic-Superhydrophilic Patterns for Single Cell Analysis.

PubMed

Jogia, Gabriella E; Tronser, Tina; Popova, Anna A; Levkin, Pavel A

2016-12-09

Single-cell analysis provides fundamental information on individual cell response to different environmental cues and is a growing interest in cancer and stem cell research. However, current existing methods are still facing challenges in performing such analysis in a high-throughput manner whilst being cost-effective. Here we established the Droplet Microarray (DMA) as a miniaturized screening platform for high-throughput single-cell analysis. Using the method of limited dilution and varying cell density and seeding time, we optimized the distribution of single cells on the DMA. We established culturing conditions for single cells in individual droplets on DMA obtaining the survival of nearly 100% of single cells and doubling time of single cells comparable with that of cells cultured in bulk cell population using conventional methods. Our results demonstrate that the DMA is a suitable platform for single-cell analysis, which carries a number of advantages compared with existing technologies allowing for treatment, staining and spot-to-spot analysis of single cells over time using conventional analysis methods such as microscopy.

A monolithic glass chip for active single-cell sorting based on mechanical phenotyping.

PubMed

Faigle, Christoph; Lautenschläger, Franziska; Whyte, Graeme; Homewood, Philip; Martín-Badosa, Estela; Guck, Jochen

2015-03-07

The mechanical properties of biological cells have long been considered as inherent markers of biological function and disease. However, the screening and active sorting of heterogeneous populations based on serial single-cell mechanical measurements has not been demonstrated. Here we present a novel monolithic glass chip for combined fluorescence detection and mechanical phenotyping using an optical stretcher. A new design and manufacturing process, involving the bonding of two asymmetrically etched glass plates, combines exact optical fiber alignment, low laser damage threshold and high imaging quality with the possibility of several microfluidic inlet and outlet channels. We show the utility of such a custom-built optical stretcher glass chip by measuring and sorting single cells in a heterogeneous population based on their different mechanical properties and verify sorting accuracy by simultaneous fluorescence detection. This offers new possibilities of exact characterization and sorting of small populations based on rheological properties for biological and biomedical applications.

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

PubMed

Dueck, Hannah; Eberwine, James; Kim, Junhyong

2016-02-01

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

Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.

PubMed

Gatto, Sole; Puri, Pier Lorenzo; Malecova, Barbora

2017-01-01

Single cell gene expression profiling is a fundamental tool for studying the heterogeneity of a cell population by addressing the phenotypic and functional characteristics of each cell. Technological advances that have coupled microfluidic technologies with high-throughput quantitative RT-PCR analyses have enabled detailed analyses of single cells in various biological contexts. In this chapter, we describe the procedure for isolating the skeletal muscle interstitial cells termed Fibro-Adipogenic Progenitors (FAPs ) and their gene expression profiling at the single cell level. Moreover, we accompany our bench protocol with bioinformatics analysis designed to process raw data as well as to visualize single cell gene expression data. Single cell gene expression profiling is therefore a useful tool in the investigation of FAPs heterogeneity and their contribution to muscle homeostasis.

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

PubMed Central

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

2016-01-01

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

Single-Cell Growth Rates in Photoautotrophic Populations Measured by Stable Isotope Probing and Resonance Raman Microspectrometry

PubMed Central

Taylor, Gordon T.; Suter, Elizabeth A.; Li, Zhuo Q.; Chow, Stephanie; Stinton, Dallyce; Zaliznyak, Tatiana; Beaupré, Steven R.

2017-01-01

A new method to measure growth rates of individual photoautotrophic cells by combining stable isotope probing (SIP) and single-cell resonance Raman microspectrometry is introduced. This report explores optimal experimental design and the theoretical underpinnings for quantitative responses of Raman spectra to cellular isotopic composition. Resonance Raman spectra of isogenic cultures of the cyanobacterium, Synechococcus sp., grown in 13C-bicarbonate revealed linear covariance between wavenumber (cm−1) shifts in dominant carotenoid Raman peaks and a broad range of cellular 13C fractional isotopic abundance. Single-cell growth rates were calculated from spectra-derived isotopic content and empirical relationships. Growth rates among any 25 cells in a sample varied considerably; mean coefficient of variation, CV, was 29 ± 3% (σ/x¯), of which only ~2% was propagated analytical error. Instantaneous population growth rates measured independently by in vivo fluorescence also varied daily (CV ≈ 53%) and were statistically indistinguishable from single-cell growth rates at all but the lowest levels of cell labeling. SCRR censuses of mixtures prepared from Synechococcus sp. and T. pseudonana (a diatom) populations with varying 13C-content and growth rates closely approximated predicted spectral responses and fractional labeling of cells added to the sample. This approach enables direct microspectrometric interrogation of isotopically- and phylogenetically-labeled cells and detects as little as 3% changes in cellular fractional labeling. This is the first description of a non-destructive technique to measure single-cell photoautotrophic growth rates based on Raman spectroscopy and well-constrained assumptions, while requiring few ancillary measurements. PMID:28824580

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

PubMed

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

2017-03-22

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

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.

In situ probing of cholesterol in astrocytes at the single-cell level using laser desorption ionization mass spectrometric imaging with colloidal silver.

PubMed

Perdian, D C; Cha, Sangwon; Oh, Jisun; Sakaguchi, Donald S; Yeung, Edward S; Lee, Young Jin

2010-04-30

Mass spectrometric imaging has been utilized to localize individual astrocytes and to obtain cholesterol populations at the single-cell level in laser desorption ionization (LDI) with colloidal silver. The silver ion adduct of membrane-bound cholesterol was monitored to detect individual cells. Good correlation between mass spectrometric and optical images at different cell densities indicates the ability to perform single-cell studies of cholesterol abundance. The feasibility of quantification is confirmed by the agreement between the LDI-MS ion signals and the results from a traditional enzymatic fluorometric assay. We propose that this approach could be an effective tool to study chemical populations at the cellular level. Published in 2010 by John Wiley & Sons, Ltd.

Ultra-localized single cell electroporation using silicon nanowires.

PubMed

Jokilaakso, Nima; Salm, Eric; Chen, Aaron; Millet, Larry; Guevara, Carlos Duarte; Dorvel, Brian; Reddy, Bobby; Karlstrom, Amelie Eriksson; Chen, Yu; Ji, Hongmiao; Chen, Yu; Sooryakumar, Ratnasingham; Bashir, Rashid

2013-02-07

Analysis of cell-to-cell variation can further the understanding of intracellular processes and the role of individual cell function within a larger cell population. The ability to precisely lyse single cells can be used to release cellular components to resolve cellular heterogeneity that might be obscured when whole populations are examined. We report a method to position and lyse individual cells on silicon nanowire and nanoribbon biological field effect transistors. In this study, HT-29 cancer cells were positioned on top of transistors by manipulating magnetic beads using external magnetic fields. Ultra-rapid cell lysis was subsequently performed by applying 600-900 mV(pp) at 10 MHz for as little as 2 ms across the transistor channel and the bulk substrate. We show that the fringing electric field at the device surface disrupts the cell membrane, leading to lysis from irreversible electroporation. This methodology allows rapid and simple single cell lysis and analysis with potential applications in medical diagnostics, proteome analysis and developmental biology studies.

Usefulness of Daily Fractionated Administration of Wortmannin Combined With γ-Ray Irradiation in Terms of Local Tumor Response and Lung Metastasis

PubMed Central

Masunaga, Shin-ichiro; Sakurai, Yoshinori; Tanaka, Hiroki; Suzuki, Minoru; Kondo, Natsuko; Narabayashi, Masaru; Tano, Keizo; Maruhashi, Akira; Ono, Koji

2013-01-01

Background To evaluate the usefulness of fractionated administration of wortmannin combined with γ-ray irradiation in terms of local tumor response and lung metastatic potential, referring to the response of intratumor quiescent (Q) cells. Methods B16-BL6 melanoma tumor-bearing C57BL/6 mice were continuously given 5-bromo-2’-deoxyuridine (BrdU) to label all proliferating (P) cells. The tumor-bearing mice then received γ-ray irradiation after wortmannin treatment through a single or 4 consecutive daily intraperitoneal administrations up to a total dose of 4 mg/kg in combination with an acute hypoxia-releasing agent (nicotinamide) or mild temperature hyperthermia (MTH). Immediately after the irradiation, cells from some tumors were isolated and incubated with a cytokinesis blocker. The responses of the Q and total (= P + Q) cell populations were assessed based on the frequency of micronuclei using immunofluorescence staining for BrdU. In other tumor-bearing mice, 17 days after irradiation, macroscopic lung metastases were enumerated. Results Wortmannin raised the sensitivity of Q cells more remarkably than the total cell population in both single and daily administrations. Daily administration of wortmannin elevated the sensitivity of both the total and Q cell populations, but especially the total cell population, compared with single administration. Daily administration, especially combined with MTH, decreased the number of lung metastases. Conclusion Daily fractionated administration of wortmannin in combination with γ-ray irradiation was thought to be more promising than single administration because of its potential to enhance local tumor response and repress lung metastatic potential. PMID:29147327

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

PubMed Central

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

2012-01-01

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

Compartmental Genomics in Living Cells Revealed by Single-Cell Nanobiopsy

PubMed Central

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

2014-01-01

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

Evaluation of tools for highly variable gene discovery from single-cell RNA-seq data.

PubMed

Yip, Shun H; Sham, Pak Chung; Wang, Junwen

2018-02-21

Traditional RNA sequencing (RNA-seq) allows the detection of gene expression variations between two or more cell populations through differentially expressed gene (DEG) analysis. However, genes that contribute to cell-to-cell differences are not discoverable with RNA-seq because RNA-seq samples are obtained from a mixture of cells. Single-cell RNA-seq (scRNA-seq) allows the detection of gene expression in each cell. With scRNA-seq, highly variable gene (HVG) discovery allows the detection of genes that contribute strongly to cell-to-cell variation within a homogeneous cell population, such as a population of embryonic stem cells. This analysis is implemented in many software packages. In this study, we compare seven HVG methods from six software packages, including BASiCS, Brennecke, scLVM, scran, scVEGs and Seurat. Our results demonstrate that reproducibility in HVG analysis requires a larger sample size than DEG analysis. Discrepancies between methods and potential issues in these tools are discussed and recommendations are made.

ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data.

PubMed

Salehi, Sohrab; Steif, Adi; Roth, Andrew; Aparicio, Samuel; Bouchard-Côté, Alexandre; Shah, Sohrab P

2017-03-01

Next-generation sequencing (NGS) of bulk tumour tissue can identify constituent cell populations in cancers and measure their abundance. This requires computational deconvolution of allelic counts from somatic mutations, which may be incapable of fully resolving the underlying population structure. Single cell sequencing (SCS) is a more direct method, although its replacement of NGS is impeded by technical noise and sampling limitations. We propose ddClone, which analytically integrates NGS and SCS data, leveraging their complementary attributes through joint statistical inference. We show on real and simulated datasets that ddClone produces more accurate results than can be achieved by either method alone.

Heteroresistance at the single-cell level: adapting to antibiotic stress through a population-based strategy and growth-controlled interphenotypic coordination.

PubMed

Wang, Xiaorong; Kang, Yu; Luo, Chunxiong; Zhao, Tong; Liu, Lin; Jiang, Xiangdan; Fu, Rongrong; An, Shuchang; Chen, Jichao; Jiang, Ning; Ren, Lufeng; Wang, Qi; Baillie, J Kenneth; Gao, Zhancheng; Yu, Jun

2014-02-11

Heteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of "resistant" cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population "hedges" its "bet" on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a blaCTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger "resistance"). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance--the gradually decreased colony-forming capability in the presence of antibiotic--was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses. Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of "resistant" cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.

Cell mechanics and human disease states

NASA Astrophysics Data System (ADS)

Suresh, Subra

2006-03-01

This presentation will provide summary of our very recent studies exploring the effects of biochemical factors, influenced by foreign organisms or in vivo processes, on intracellular structural reorganization, single-cell mechanical response and motility of a population of cells in the context of two human diseases: malaria induced by Plasmodium falciparum merozoites that invade red blood cells, and gastrointestinal cancer metastasis involving epithelial cells. In both cases, particular attention will be devoted to systematic changes induced in specific molecular species in response to controlled alterations in disease state. The role of critical proteins in influencing the mechanical response of human red bloods during the intra-erythrocytic development of P. falciparum merozoites has also been assessed quantitatively using specific protein knock-out experiments by recourse to gene inactivation methods. Single-cell mechanical response characterization entails such tools as optical tweezers and mechanical plate stretchers whereas cell motility assays and cell-population biorheology characterization involves microfluidic channels. The experimental studies are accompanied by three-dimensional computational simulations at the continuum and mesoscopic scales of cell deformation. An outcome of such combined experimental and computational biophysical studies is the realization of how chemical factors influence single-cell mechanical response, cytoadherence, the biorheology of a large population of cells through microchannels representative of in vivo conditions, and the onset and progression of disease states.

The future is now: single-cell genomics of bacteria and archaea

PubMed Central

Blainey, Paul C.

2013-01-01

Interest in the expanding catalog of uncultivated microorganisms, increasing recognition of heterogeneity among seemingly similar cells, and technological advances in whole-genome amplification and single-cell manipulation are driving considerable progress in single-cell genomics. Here, the spectrum of applications for single-cell genomics, key advances in the development of the field, and emerging methodology for single-cell genome sequencing are reviewed by example with attention to the diversity of approaches and their unique characteristics. Experimental strategies transcending specific methodologies are identified and organized as a road map for future studies in single-cell genomics of environmental microorganisms. Over the next decade, increasingly powerful tools for single-cell genome sequencing and analysis will play key roles in accessing the genomes of uncultivated organisms, determining the basis of microbial community functions, and fundamental aspects of microbial population biology. PMID:23298390

Regulation of Hemopoietic Stem Cell Turnover and Population Size in Neonatal Mice

DTIC Science & Technology

1975-04-01

Following birth the hematopoietic stem cell population of the liver as measured by the in vivo spleen nodule assay (CFU) declines with a halving time...of about 48 hours. The stem cell population of the spleen grows exponentially with a doubling time of about 17 hours. In vitro incubation with high...single spleen colonies derived from neonatal liver and spleen CFU that both stem cell populations have a high self-renewal capacity. Thus, the decline in

Highly multiplexed targeted DNA sequencing from single nuclei.

PubMed

Leung, Marco L; Wang, Yong; Kim, Charissa; Gao, Ruli; Jiang, Jerry; Sei, Emi; Navin, Nicholas E

2016-02-01

Single-cell DNA sequencing methods are challenged by poor physical coverage, high technical error rates and low throughput. To address these issues, we developed a single-cell DNA sequencing protocol that combines flow-sorting of single nuclei, time-limited multiple-displacement amplification (MDA), low-input library preparation, DNA barcoding, targeted capture and next-generation sequencing (NGS). This approach represents a major improvement over our previous single nucleus sequencing (SNS) Nature Protocols paper in terms of generating higher-coverage data (>90%), thereby enabling the detection of genome-wide variants in single mammalian cells at base-pair resolution. Furthermore, by pooling 48-96 single-cell libraries together for targeted capture, this approach can be used to sequence many single-cell libraries in parallel in a single reaction. This protocol greatly reduces the cost of single-cell DNA sequencing, and it can be completed in 5-6 d by advanced users. This single-cell DNA sequencing protocol has broad applications for studying rare cells and complex populations in diverse fields of biological research and medicine.

Noninvasive High-Throughput Single-Cell Analysis of the Intracellular pH of Saccharomyces cerevisiae by Ratiometric Flow Cytometry

PubMed Central

Valkonen, Mari; Mojzita, Dominik; Penttilä, Merja

2013-01-01

The ability of cells to maintain pH homeostasis in response to environmental changes has elicited interest in basic and applied research and has prompted the development of methods for intracellular pH measurements. Many traditional methods provide information at population level and thus the average values of the studied cell physiological phenomena, excluding the fact that cell cultures are very heterogeneous. Single-cell analysis, on the other hand, offers more detailed insight into population variability, thereby facilitating a considerably deeper understanding of cell physiology. Although microscopy methods can address this issue, they suffer from limitations in terms of the small number of individual cells that can be studied and complicated image processing. We developed a noninvasive high-throughput method that employs flow cytometry to analyze large populations of cells that express pHluorin, a genetically encoded ratiometric fluorescent probe that is sensitive to pH. The method described here enables measurement of the intracellular pH of single cells with high sensitivity and speed, which is a clear improvement compared to previously published methods that either require pretreatment of the cells, measure cell populations, or require complex data analysis. The ratios of fluorescence intensities, which correlate to the intracellular pH, are independent of the expression levels of the pH probe, making the use of transiently or extrachromosomally expressed probes possible. We conducted an experiment on the kinetics of the pH homeostasis of Saccharomyces cerevisiae cultures grown to a stationary phase after ethanol or glucose addition and after exposure to weak acid stress and glucose pulse. Minor populations with pH homeostasis behaving differently upon treatments were identified. PMID:24038689

Noninvasive high-throughput single-cell analysis of the intracellular pH of Saccharomyces cerevisiae by ratiometric flow cytometry.

PubMed

Valkonen, Mari; Mojzita, Dominik; Penttilä, Merja; Bencina, Mojca

2013-12-01

The ability of cells to maintain pH homeostasis in response to environmental changes has elicited interest in basic and applied research and has prompted the development of methods for intracellular pH measurements. Many traditional methods provide information at population level and thus the average values of the studied cell physiological phenomena, excluding the fact that cell cultures are very heterogeneous. Single-cell analysis, on the other hand, offers more detailed insight into population variability, thereby facilitating a considerably deeper understanding of cell physiology. Although microscopy methods can address this issue, they suffer from limitations in terms of the small number of individual cells that can be studied and complicated image processing. We developed a noninvasive high-throughput method that employs flow cytometry to analyze large populations of cells that express pHluorin, a genetically encoded ratiometric fluorescent probe that is sensitive to pH. The method described here enables measurement of the intracellular pH of single cells with high sensitivity and speed, which is a clear improvement compared to previously published methods that either require pretreatment of the cells, measure cell populations, or require complex data analysis. The ratios of fluorescence intensities, which correlate to the intracellular pH, are independent of the expression levels of the pH probe, making the use of transiently or extrachromosomally expressed probes possible. We conducted an experiment on the kinetics of the pH homeostasis of Saccharomyces cerevisiae cultures grown to a stationary phase after ethanol or glucose addition and after exposure to weak acid stress and glucose pulse. Minor populations with pH homeostasis behaving differently upon treatments were identified.

Single-cell intracellular nano-pH probes.

PubMed

Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader

2015-01-01

Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular pH of individual cells within a cell population is challenging with existing technologies, and there is a need to engineer new methodologies. In this paper, we discuss the use of nanopipette technology to overcome the limitations of intracellular pH measurements at the single-cell level. We have developed a nano-pH probe through physisorption of chitosan onto hydroxylated quartz nanopipettes with extremely small pore sizes (~100 nm). The dynamic pH range of the nano-pH probe was from 2.6 to 10.7 with a sensitivity of 0.09 units. We have performed single-cell intracellular pH measurements using non-cancerous and cancerous cell lines, including human fibroblasts, HeLa, MDA-MB-231 and MCF-7, with the pH nanoprobe. We have further demonstrated the real-time continuous single-cell pH measurement capability of the sensor, showing the cellular pH response to pharmaceutical manipulations. These findings suggest that the chitosan-functionalized nanopore is a powerful nano-tool for pH sensing at the single-cell level with high temporal and spatial resolution.

Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data.

PubMed

Ezer, Daphne; Moignard, Victoria; Göttgens, Berthold; Adryan, Boris

2016-08-01

Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete pipeline for the analysis of single cell qPCR data that uses the mathematics behind bursty expression to develop more accurate and robust algorithms for analyzing the origin of heterogeneity in experimental samples, specifically an algorithm for clustering cells by their bursting behavior (Simulated Annealing for Bursty Expression Clustering, SABEC) and a statistical tool for comparing the kinetic parameters of bursty expression across populations of cells (Estimation of Parameter changes in Kinetics, EPiK). We applied these methods to hematopoiesis, including a new single cell dataset in which transcription factors (TFs) involved in the earliest branchpoint of blood differentiation were individually up- and down-regulated. We could identify two unique sub-populations within a seemingly homogenous group of hematopoietic stem cells. In addition, we could predict regulatory mechanisms controlling the expression levels of eighteen key hematopoietic transcription factors throughout differentiation. Detailed information about gene regulatory mechanisms can therefore be obtained simply from high throughput single cell gene expression data, which should be widely applicable given the rapid expansion of single cell genomics.

Simultaneous Multiparameter Cellular Energy Metabolism Profiling of Small Populations of Cells.

PubMed

Kelbauskas, Laimonas; Ashili, Shashaanka P; Lee, Kristen B; Zhu, Haixin; Tian, Yanqing; Meldrum, Deirdre R

2018-03-12

Functional and genomic heterogeneity of individual cells are central players in a broad spectrum of normal and disease states. Our knowledge about the role of cellular heterogeneity in tissue and organism function remains limited due to analytical challenges one encounters when performing single cell studies in the context of cell-cell interactions. Information based on bulk samples represents ensemble averages over populations of cells, while data generated from isolated single cells do not account for intercellular interactions. We describe a new technology and demonstrate two important advantages over existing technologies: first, it enables multiparameter energy metabolism profiling of small cell populations (<100 cells)-a sample size that is at least an order of magnitude smaller than other, commercially available technologies; second, it can perform simultaneous real-time measurements of oxygen consumption rate (OCR), extracellular acidification rate (ECAR), and mitochondrial membrane potential (MMP)-a capability not offered by any other commercially available technology. Our results revealed substantial diversity in response kinetics of the three analytes in dysplastic human epithelial esophageal cells and suggest the existence of varying cellular energy metabolism profiles and their kinetics among small populations of cells. The technology represents a powerful analytical tool for multiparameter studies of cellular function.

Single-Cell Mass Spectrometry Reveals Changes in Lipid and Metabolite Expression in RAW 264.7 Cells upon Lipopolysaccharide Stimulation

NASA Astrophysics Data System (ADS)

Yang, Bo; Patterson, Nathan Heath; Tsui, Tina; Caprioli, Richard M.; Norris, Jeremy L.

2018-05-01

It has been widely recognized that individual cells that exist within a large population of cells, even if they are genetically identical, can have divergent molecular makeups resulting from a variety of factors, including local environmental factors and stochastic processes within each cell. Presently, numerous approaches have been described that permit the resolution of these single-cell expression differences for RNA and protein; however, relatively few techniques exist for the study of lipids and metabolites in this manner. This study presents a methodology for the analysis of metabolite and lipid expression at the level of a single cell through the use of imaging mass spectrometry on a high-performance Fourier transform ion cyclotron resonance mass spectrometer. This report provides a detailed description of the overall experimental approach, including sample preparation as well as the data acquisition and analysis strategy for single cells. Applying this approach to the study of cultured RAW264.7 cells, we demonstrate that this method can be used to study the variation in molecular expression with cell populations and is sensitive to alterations in that expression that occurs upon lipopolysaccharide stimulation. [Figure not available: see fulltext.

Single-Cell Mass Spectrometry Reveals Changes in Lipid and Metabolite Expression in RAW 264.7 Cells upon Lipopolysaccharide Stimulation

NASA Astrophysics Data System (ADS)

Yang, Bo; Patterson, Nathan Heath; Tsui, Tina; Caprioli, Richard M.; Norris, Jeremy L.

2018-03-01

It has been widely recognized that individual cells that exist within a large population of cells, even if they are genetically identical, can have divergent molecular makeups resulting from a variety of factors, including local environmental factors and stochastic processes within each cell. Presently, numerous approaches have been described that permit the resolution of these single-cell expression differences for RNA and protein; however, relatively few techniques exist for the study of lipids and metabolites in this manner. This study presents a methodology for the analysis of metabolite and lipid expression at the level of a single cell through the use of imaging mass spectrometry on a high-performance Fourier transform ion cyclotron resonance mass spectrometer. This report provides a detailed description of the overall experimental approach, including sample preparation as well as the data acquisition and analysis strategy for single cells. Applying this approach to the study of cultured RAW264.7 cells, we demonstrate that this method can be used to study the variation in molecular expression with cell populations and is sensitive to alterations in that expression that occurs upon lipopolysaccharide stimulation. [Figure not available: see fulltext.

Resolution of Conflicting Signals at the Single-Cell Level in the Regulation of Cyanobacterial Photosynthesis and Nitrogen Fixation.

PubMed

Mohr, Wiebke; Vagner, Tomas; Kuypers, Marcel M M; Ackermann, Martin; Laroche, Julie

2013-01-01

Unicellular, diazotrophic cyanobacteria temporally separate dinitrogen (N2) fixation and photosynthesis to prevent inactivation of the nitrogenase by oxygen. This temporal segregation is regulated by a circadian clock with oscillating activities of N2 fixation in the dark and photosynthesis in the light. On the population level, this separation is not always complete, since the two processes can overlap during transitions from dark to light. How do single cells avoid inactivation of nitrogenase during these periods? One possibility is that phenotypic heterogeneity in populations leads to segregation of the two processes. Here, we measured N2 fixation and photosynthesis of individual cells using nanometer-scale secondary ion mass spectrometry (nanoSIMS) to assess both processes in a culture of the unicellular, diazotrophic cyanobacterium Crocosphaera watsonii during a dark-light and a continuous light phase. We compared single-cell rates with bulk rates and gene expression profiles. During the regular dark and light phases, C. watsonii exhibited the temporal segregation of N2 fixation and photosynthesis commonly observed. However, N2 fixation and photosynthesis were concurrently measurable at the population level during the subjective dark phase in which cells were kept in the light rather than returned to the expected dark phase. At the single-cell level, though, cells discriminated against either one of the two processes. Cells that showed high levels of photosynthesis had low nitrogen fixing activities, and vice versa. These results suggest that, under ambiguous environmental signals, single cells discriminate against either photosynthesis or nitrogen fixation, and thereby might reduce costs associated with running incompatible processes in the same cell.

Resolution of Conflicting Signals at the Single-Cell Level in the Regulation of Cyanobacterial Photosynthesis and Nitrogen Fixation

PubMed Central

Mohr, Wiebke; Vagner, Tomas; Kuypers, Marcel M. M.; Ackermann, Martin; LaRoche, Julie

2013-01-01

Unicellular, diazotrophic cyanobacteria temporally separate dinitrogen (N2) fixation and photosynthesis to prevent inactivation of the nitrogenase by oxygen. This temporal segregation is regulated by a circadian clock with oscillating activities of N2 fixation in the dark and photosynthesis in the light. On the population level, this separation is not always complete, since the two processes can overlap during transitions from dark to light. How do single cells avoid inactivation of nitrogenase during these periods? One possibility is that phenotypic heterogeneity in populations leads to segregation of the two processes. Here, we measured N2 fixation and photosynthesis of individual cells using nanometer-scale secondary ion mass spectrometry (nanoSIMS) to assess both processes in a culture of the unicellular, diazotrophic cyanobacterium Crocosphaera watsonii during a dark-light and a continuous light phase. We compared single-cell rates with bulk rates and gene expression profiles. During the regular dark and light phases, C. watsonii exhibited the temporal segregation of N2 fixation and photosynthesis commonly observed. However, N2 fixation and photosynthesis were concurrently measurable at the population level during the subjective dark phase in which cells were kept in the light rather than returned to the expected dark phase. At the single-cell level, though, cells discriminated against either one of the two processes. Cells that showed high levels of photosynthesis had low nitrogen fixing activities, and vice versa. These results suggest that, under ambiguous environmental signals, single cells discriminate against either photosynthesis or nitrogen fixation, and thereby might reduce costs associated with running incompatible processes in the same cell. PMID:23805199

Insertional Mutagenesis by CRISPR/Cas9 Ribonucleoprotein Gene Editing in Cells Targeted for Point Mutation Repair Directed by Short Single-Stranded DNA Oligonucleotides.

PubMed

Rivera-Torres, Natalia; Banas, Kelly; Bialk, Pawel; Bloh, Kevin M; Kmiec, Eric B

2017-01-01

CRISPR/Cas9 and single-stranded DNA oligonucleotides (ssODNs) have been used to direct the repair of a single base mutation in human genes. Here, we examine a method designed to increase the precision of RNA guided genome editing in human cells by utilizing a CRISPR/Cas9 ribonucleoprotein (RNP) complex to initiate DNA cleavage. The RNP is assembled in vitro and induces a double stranded break at a specific site surrounding the mutant base designated for correction by the ssODN. We use an integrated mutant eGFP gene, bearing a single base change rendering the expressed protein nonfunctional, as a single copy target in HCT 116 cells. We observe significant gene correction activity of the mutant base, promoted by the RNP and single-stranded DNA oligonucleotide with validation through genotypic and phenotypic readout. We demonstrate that all individual components must be present to obtain successful gene editing. Importantly, we examine the genotype of individually sorted corrected and uncorrected clonally expanded cell populations for the mutagenic footprint left by the action of these gene editing tools. While the DNA sequence of the corrected population is exact with no adjacent sequence modification, the uncorrected population exhibits heterogeneous mutagenicity with a wide variety of deletions and insertions surrounding the target site. We designate this type of DNA aberration as on-site mutagenicity. Analyses of two clonal populations bearing specific DNA insertions surrounding the target site, indicate that point mutation repair has occurred at the level of the gene. The phenotype, however, is not rescued because a section of the single-stranded oligonucleotide has been inserted altering the reading frame and generating truncated proteins. These data illustrate the importance of analysing mutagenicity in uncorrected cells. Our results also form the basis of a simple model for point mutation repair directed by a short single-stranded DNA oligonucleotides and CRISPR/Cas9 ribonucleoprotein complex.

Insertional Mutagenesis by CRISPR/Cas9 Ribonucleoprotein Gene Editing in Cells Targeted for Point Mutation Repair Directed by Short Single-Stranded DNA Oligonucleotides

PubMed Central

Rivera-Torres, Natalia; Bialk, Pawel; Bloh, Kevin M.; Kmiec, Eric B.

2017-01-01

CRISPR/Cas9 and single-stranded DNA oligonucleotides (ssODNs) have been used to direct the repair of a single base mutation in human genes. Here, we examine a method designed to increase the precision of RNA guided genome editing in human cells by utilizing a CRISPR/Cas9 ribonucleoprotein (RNP) complex to initiate DNA cleavage. The RNP is assembled in vitro and induces a double stranded break at a specific site surrounding the mutant base designated for correction by the ssODN. We use an integrated mutant eGFP gene, bearing a single base change rendering the expressed protein nonfunctional, as a single copy target in HCT 116 cells. We observe significant gene correction activity of the mutant base, promoted by the RNP and single-stranded DNA oligonucleotide with validation through genotypic and phenotypic readout. We demonstrate that all individual components must be present to obtain successful gene editing. Importantly, we examine the genotype of individually sorted corrected and uncorrected clonally expanded cell populations for the mutagenic footprint left by the action of these gene editing tools. While the DNA sequence of the corrected population is exact with no adjacent sequence modification, the uncorrected population exhibits heterogeneous mutagenicity with a wide variety of deletions and insertions surrounding the target site. We designate this type of DNA aberration as on-site mutagenicity. Analyses of two clonal populations bearing specific DNA insertions surrounding the target site, indicate that point mutation repair has occurred at the level of the gene. The phenotype, however, is not rescued because a section of the single-stranded oligonucleotide has been inserted altering the reading frame and generating truncated proteins. These data illustrate the importance of analysing mutagenicity in uncorrected cells. Our results also form the basis of a simple model for point mutation repair directed by a short single-stranded DNA oligonucleotides and CRISPR/Cas9 ribonucleoprotein complex. PMID:28052104

Identifying EGFR-Expressed Cells and Detecting EGFR Multi-Mutations at Single-Cell Level by Microfluidic Chip

NASA Astrophysics Data System (ADS)

Li, Ren; Zhou, Mingxing; Li, Jine; Wang, Zihua; Zhang, Weikai; Yue, Chunyan; Ma, Yan; Peng, Hailin; Wei, Zewen; Hu, Zhiyuan

2018-03-01

EGFR mutations companion diagnostics have been proved to be crucial for the efficacy of tyrosine kinase inhibitor targeted cancer therapies. To uncover multiple mutations occurred in minority of EGFR-mutated cells, which may be covered by the noises from majority of un-mutated cells, is currently becoming an urgent clinical requirement. Here we present the validation of a microfluidic-chip-based method for detecting EGFR multi-mutations at single-cell level. By trapping and immunofluorescently imaging single cells in specifically designed silicon microwells, the EGFR-expressed cells were easily identified. By in situ lysing single cells, the cell lysates of EGFR-expressed cells were retrieved without cross-contamination. Benefited from excluding the noise from cells without EGFR expression, the simple and cost-effective Sanger's sequencing, but not the expensive deep sequencing of the whole cell population, was used to discover multi-mutations. We verified the new method with precisely discovering three most important EGFR drug-related mutations from a sample in which EGFR-mutated cells only account for a small percentage of whole cell population. The microfluidic chip is capable of discovering not only the existence of specific EGFR multi-mutations, but also other valuable single-cell-level information: on which specific cells the mutations occurred, or whether different mutations coexist on the same cells. This microfluidic chip constitutes a promising method to promote simple and cost-effective Sanger's sequencing to be a routine test before performing targeted cancer therapy.[Figure not available: see fulltext.

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

PubMed Central

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

2013-01-01

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

Single-cell RNA sequencing reveals developmental heterogeneity among early lymphoid progenitors.

PubMed

Alberti-Servera, Llucia; von Muenchow, Lilly; Tsapogas, Panagiotis; Capoferri, Giuseppina; Eschbach, Katja; Beisel, Christian; Ceredig, Rhodri; Ivanek, Robert; Rolink, Antonius

2017-12-15

Single-cell RNA sequencing is a powerful technology for assessing heterogeneity within defined cell populations. Here, we describe the heterogeneity of a B220 + CD117 int CD19 - NK1.1 - uncommitted hematopoietic progenitor having combined lymphoid and myeloid potential. Phenotypic and functional assays revealed four subpopulations within the progenitor with distinct lineage developmental potentials. Among them, the Ly6D + SiglecH - CD11c - fraction was lymphoid-restricted exhibiting strong B-cell potential, whereas the Ly6D - SiglecH - CD11c - fraction showed mixed lympho-myeloid potential. Single-cell RNA sequencing of these subsets revealed that the latter population comprised a mixture of cells with distinct lymphoid and myeloid transcriptional signatures and identified a subgroup as the potential precursor of Ly6D + SiglecH - CD11c - Subsequent functional assays confirmed that B220 + CD117 int CD19 - NK1.1 - single cells are, with rare exceptions, not bipotent for lymphoid and myeloid lineages. A B-cell priming gradient was observed within the Ly6D + SiglecH - CD11c - subset and we propose a herein newly identified subgroup as the direct precursor of the first B-cell committed stage. Therefore, the apparent multipotency of B220 + CD117 int CD19 - NK1.1 - progenitors results from underlying heterogeneity at the single-cell level and highlights the validity of single-cell transcriptomics for resolving cellular heterogeneity and developmental relationships among hematopoietic progenitors. © 2017 The Authors.

Single Cell Profiling using Ionic Liquid Matrix-Enhanced Secondary Ion Mass Spectrometry for Neuronal Cell Type Differentiation

PubMed Central

Do, Thanh D.; Comi, Troy J.; Dunham, Sage J. B.; Rubakhin, Stanislav S.; Sweedler, Jonathan V.

2017-01-01

A high-throughput single cell profiling method has been developed for matrix-enhanced secondary ion mass spectrometry (ME-SIMS) to investigate the lipid profiles of neuronal cells. Populations of cells are dispersed onto the substrate, their locations determined using optical microscopy, and the cell locations used to guide the acquisition of SIMS spectra from the cells. Up to 2,000 cells can be assayed in one experiment at a rate of 6 s per cell. Multiple saturated and unsaturated phosphatidylcholines (PCs) and their fragments are detected and verified with tandem mass spectrometry from individual cells when ionic liquids are employed as a matrix. Optically guided single cell profiling with ME-SIMS is suitable for a range of cell sizes, from Aplysia californica neurons larger than 75 μm to 7-μm rat cerebellar neurons. ME-SIMS analysis followed by t-distributed stochastic neighbor embedding of peaks in the lipid molecular mass range (m/z 700–850) distinguishes several cell types from the rat central nervous system, largely based on the relative proportions of the four dominant lipids, PC(32:0), PC(34:1), PC(36:1), and PC(38:5). Furthermore, subpopulations within each cell type are tentatively classified consistent with their endogenous lipid ratios. The results illustrate the efficacy of a new approach to classify single cell populations and subpopulations using SIMS profiling of lipid and metabolite contents. These methods are broadly applicable for high throughput single cell chemical analyses. PMID:28194949

Clonal architecture of secondary acute myeloid leukemia defined by single-cell sequencing.

PubMed

Hughes, Andrew E O; Magrini, Vincent; Demeter, Ryan; Miller, Christopher A; Fulton, Robert; Fulton, Lucinda L; Eades, William C; Elliott, Kevin; Heath, Sharon; Westervelt, Peter; Ding, Li; Conrad, Donald F; White, Brian S; Shao, Jin; Link, Daniel C; DiPersio, John F; Mardis, Elaine R; Wilson, Richard K; Ley, Timothy J; Walter, Matthew J; Graubert, Timothy A

2014-07-01

Next-generation sequencing has been used to infer the clonality of heterogeneous tumor samples. These analyses yield specific predictions-the population frequency of individual clones, their genetic composition, and their evolutionary relationships-which we set out to test by sequencing individual cells from three subjects diagnosed with secondary acute myeloid leukemia, each of whom had been previously characterized by whole genome sequencing of unfractionated tumor samples. Single-cell mutation profiling strongly supported the clonal architecture implied by the analysis of bulk material. In addition, it resolved the clonal assignment of single nucleotide variants that had been initially ambiguous and identified areas of previously unappreciated complexity. Accordingly, we find that many of the key assumptions underlying the analysis of tumor clonality by deep sequencing of unfractionated material are valid. Furthermore, we illustrate a single-cell sequencing strategy for interrogating the clonal relationships among known variants that is cost-effective, scalable, and adaptable to the analysis of both hematopoietic and solid tumors, or any heterogeneous population of cells.

78 FR 27186 - Application(s) for Duty-Free Entry of Scientific Instruments

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-09

... cell regeneration in damaged tissue, and examine the regulatory mechanisms for metabolic activity in... populations of cells develop into a coherent circuit that capably detects directional movement in a visual... a single neuron or large numbers of cells in a neuronal population. The instrument's capabilities...

Significance of Fractionated Administration of Thalidomide Combined With γ-Ray Irradiation in Terms of Local Tumor Response and Lung Metastasis

PubMed Central

Masunaga, Shin-ichiro; Sanada, Yu; Moriwaki, Takahiro; Tano, Keizo; Sakurai, Yoshinori; Tanaka, Hiroki; Suzuki, Minoru; Kondo, Natsuko; Narabayashi, Masaru; Watanabe, Tsubasa; Nakagawa, Yosuke; Maruhashi, Akira; Ono, Koji

2014-01-01

Background The aim of this study was to evaluate the significance of fractionated administration of thalidomide combined with γ-ray irradiation in terms of local tumor response and lung metastatic potential, referring to the response of intratumor quiescent (Q) cells. Methods B16-BL6 melanoma tumor-bearing C57BL/6 mice were continuously given 5-bromo-2’-deoxyuridine (BrdU) to label all proliferating (P) cells. The tumor-bearing mice then received γ-ray irradiation after thalidomide treatment through a single or two consecutive daily intraperitoneal administrations up to a total dose of 400 mg/kg in combination with an acute hypoxia-releasing agent (nicotinamide) or mild temperature hyperthermia (MTH). Immediately after the irradiation, cells from some tumors were isolated and incubated with a cytokinesis blocker. The responses of the Q and total (= P + Q) cell populations were assessed based on the frequency of micronuclei using immunofluorescence staining for BrdU. In other tumor-bearing mice, 17 days after irradiation, macroscopic lung metastases were enumerated. Results Thalidomide raised the sensitivity of the total cell population more remarkably than Q cells in both single and daily administrations. Daily administration of thalidomide elevated the sensitivity of both the total and Q cell populations, but especially the total cell population, compared with single administration. Daily administration, especially combined with MTH, decreased the number of lung metastases. Conclusion Daily fractionated administration of thalidomide in combination with γ-ray irradiation was thought to be more promising than single administration because of its potential to enhance local tumor response and repress lung metastatic potential. PMID:29147396

Fundamental limits on dynamic inference from single-cell snapshots

PubMed Central

Weinreb, Caleb; Tusi, Betsabeh K.; Socolovsky, Merav

2018-01-01

Single-cell expression profiling reveals the molecular states of individual cells with unprecedented detail. Because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. However, some information on dynamics is present in the data: the continuum of molecular states in the population can reflect the trajectory of a typical cell. Many methods for extracting single-cell dynamics from population data have been proposed. However, all such attempts face a common limitation: for any measured distribution of cell states, there are multiple dynamics that could give rise to it, and by extension, multiple possibilities for underlying mechanisms of gene regulation. Here, we describe the aspects of gene expression dynamics that cannot be inferred from a static snapshot alone and identify assumptions necessary to constrain a unique solution for cell dynamics from static snapshots. We translate these constraints into a practical algorithmic approach, population balance analysis (PBA), which makes use of a method from spectral graph theory to solve a class of high-dimensional differential equations. We use simulations to show the strengths and limitations of PBA, and then apply it to single-cell profiles of hematopoietic progenitor cells (HPCs). Cell state predictions from this analysis agree with HPC fate assays reported in several papers over the past two decades. By highlighting the fundamental limits on dynamic inference faced by any method, our framework provides a rigorous basis for dynamic interpretation of a gene expression continuum and clarifies best experimental designs for trajectory reconstruction from static snapshot measurements. PMID:29463712

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.

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

Reliable measurement of E. coli single cell fluorescence distribution using a standard microscope set-up.

PubMed

Cortesi, Marilisa; Bandiera, Lucia; Pasini, Alice; Bevilacqua, Alessandro; Gherardi, Alessandro; Furini, Simone; Giordano, Emanuele

2017-01-01

Quantifying gene expression at single cell level is fundamental for the complete characterization of synthetic gene circuits, due to the significant impact of noise and inter-cellular variability on the system's functionality. Commercial set-ups that allow the acquisition of fluorescent signal at single cell level (flow cytometers or quantitative microscopes) are expensive apparatuses that are hardly affordable by small laboratories. A protocol that makes a standard optical microscope able to acquire quantitative, single cell, fluorescent data from a bacterial population transformed with synthetic gene circuitry is presented. Single cell fluorescence values, acquired with a microscope set-up and processed with custom-made software, are compared with results that were obtained with a flow cytometer in a bacterial population transformed with the same gene circuitry. The high correlation between data from the two experimental set-ups, with a correlation coefficient computed over the tested dynamic range > 0.99, proves that a standard optical microscope- when coupled with appropriate software for image processing- might be used for quantitative single-cell fluorescence measurements. The calibration of the set-up, together with its validation, is described. The experimental protocol described in this paper makes quantitative measurement of single cell fluorescence accessible to laboratories equipped with standard optical microscope set-ups. Our method allows for an affordable measurement/quantification of intercellular variability, whose better understanding of this phenomenon will improve our comprehension of cellular behaviors and the design of synthetic gene circuits. All the required software is freely available to the synthetic biology community (MUSIQ Microscope flUorescence SIngle cell Quantification).

Massively parallel polymerase cloning and genome sequencing of single cells using nanoliter microwells

PubMed Central

Gole, Jeff; Gore, Athurva; Richards, Andrew; Chiu, Yu-Jui; Fung, Ho-Lim; Bushman, Diane; Chiang, Hsin-I; Chun, Jerold; Lo, Yu-Hwa; Zhang, Kun

2013-01-01

Genome sequencing of single cells has a variety of applications, including characterizing difficult-to-culture microorganisms and identifying somatic mutations in single cells from mammalian tissues. A major hurdle in this process is the bias in amplifying the genetic material from a single cell, a procedure known as polymerase cloning. Here we describe the microwell displacement amplification system (MIDAS), a massively parallel polymerase cloning method in which single cells are randomly distributed into hundreds to thousands of nanoliter wells and simultaneously amplified for shotgun sequencing. MIDAS reduces amplification bias because polymerase cloning occurs in physically separated nanoliter-scale reactors, facilitating the de novo assembly of near-complete microbial genomes from single E. coli cells. In addition, MIDAS allowed us to detect single-copy number changes in primary human adult neurons at 1–2 Mb resolution. MIDAS will further the characterization of genomic diversity in many heterogeneous cell populations. PMID:24213699

Unveiling adaptation using high-resolution lineage tracking

NASA Astrophysics Data System (ADS)

Blundell, Jamie; Levy, Sasha; Fisher, Daniel; Petrov, Dmitri; Sherlock, Gavin

2013-03-01

Human diseases such as cancer and microbial infections are adaptive processes inside the human body with enormous population sizes: between 106 -1012 cells. In spite of this our understanding of adaptation in large populations is limited. The key problem is the difficulty in identifying anything more than a handful of rare, large-effect beneficial mutations. The development and use of molecular barcodes allows us to uniquely tag hundreds of thousands of cells and enable us to track tens of thousands of adaptive mutations in large yeast populations. We use this system to test some of the key theories on which our understanding of adaptation in large populations is based. We (i) measure the fitness distribution in an evolving population at different times, (ii) identify when an appreciable fraction of clones in the population have at most a single adaptive mutation and isolate a large number of clones with independent single adaptive mutations, and (iii) use this clone collection to determine the distribution of fitness effects of single beneficial mutations.

Profiling DNA methylome landscapes of mammalian cells with single-cell reduced-representation bisulfite sequencing.

PubMed

Guo, Hongshan; Zhu, Ping; Guo, Fan; Li, Xianlong; Wu, Xinglong; Fan, Xiaoying; Wen, Lu; Tang, Fuchou

2015-05-01

The heterogeneity of DNA methylation within a population of cells necessitates DNA methylome profiling at single-cell resolution. Recently, we developed a single-cell reduced-representation bisulfite sequencing (scRRBS) technique in which we modified the original RRBS method by integrating all the experimental steps before PCR amplification into a single-tube reaction. These modifications enable scRRBS to provide digitized methylation information on ∼1 million CpG sites within an individual diploid mouse or human cell at single-base resolution. Compared with the single-cell bisulfite sequencing (scBS) technique, scRRBS covers fewer CpG sites, but it provides better coverage for CpG islands (CGIs), which are likely to be the most informative elements for DNA methylation. The entire procedure takes ∼3 weeks, and it requires strong molecular biology skills.

Clustering single cells: a review of approaches on high-and low-depth single-cell RNA-seq data.

PubMed

Menon, Vilas

2017-12-11

Advances in single-cell RNA-sequencing technology have resulted in a wealth of studies aiming to identify transcriptomic cell types in various biological systems. There are multiple experimental approaches to isolate and profile single cells, which provide different levels of cellular and tissue coverage. In addition, multiple computational strategies have been proposed to identify putative cell types from single-cell data. From a data generation perspective, recent single-cell studies can be classified into two groups: those that distribute reads shallowly over large numbers of cells and those that distribute reads more deeply over a smaller cell population. Although there are advantages to both approaches in terms of cellular and tissue coverage, it is unclear whether different computational cell type identification methods are better suited to one or the other experimental paradigm. This study reviews three cell type clustering algorithms, each representing one of three broad approaches, and finds that PCA-based algorithms appear most suited to low read depth data sets, whereas gene clustering-based and biclustering algorithms perform better on high read depth data sets. In addition, highly related cell classes are better distinguished by higher-depth data, given the same total number of reads; however, simultaneous discovery of distinct and similar types is better served by lower-depth, higher cell number data. Overall, this study suggests that the depth of profiling should be determined by initial assumptions about the diversity of cells in the population, and that the selection of clustering algorithm(s) is subsequently based on the depth of profiling will allow for better identification of putative transcriptomic cell types. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Single-cell intracellular nano-pH probes†

PubMed Central

Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader

2016-01-01

Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular pH of individual cells within a cell population is challenging with existing technologies, and there is a need to engineer new methodologies. In this paper, we discuss the use of nanopipette technology to overcome the limitations of intracellular pH measurements at the single-cell level. We have developed a nano-pH probe through physisorption of chitosan onto hydroxylated quartz nanopipettes with extremely small pore sizes (~100 nm). The dynamic pH range of the nano-pH probe was from 2.6 to 10.7 with a sensitivity of 0.09 units. We have performed single-cell intracellular pH measurements using non-cancerous and cancerous cell lines, including human fibroblasts, HeLa, MDA-MB-231 and MCF-7, with the pH nanoprobe. We have further demonstrated the real-time continuous single-cell pH measurement capability of the sensor, showing the cellular pH response to pharmaceutical manipulations. These findings suggest that the chitosan-functionalized nanopore is a powerful nano-tool for pH sensing at the single-cell level with high temporal and spatial resolution. PMID:27708772

Single Cell-Based Vector Tracing in Patients with ADA-SCID Treated with Stem Cell Gene Therapy.

PubMed

Igarashi, Yuka; Uchiyama, Toru; Minegishi, Tomoko; Takahashi, Sirirat; Watanabe, Nobuyuki; Kawai, Toshinao; Yamada, Masafumi; Ariga, Tadashi; Onodera, Masafumi

2017-09-15

Clinical improvement in stem cell gene therapy (SCGT) for primary immunodeficiencies depends on the engraftment levels of genetically corrected cells, and tracing the transgene in each hematopoietic lineage is therefore extremely important in evaluating the efficacy of SCGT. We established a single cell-based droplet digital PCR (sc-ddPCR) method consisting of the encapsulation of a single cell into each droplet, followed by emulsion PCR with primers and probes specific for the transgene. A fluorescent signal in a droplet indicates the presence of a single cell carrying the target gene in its genome, and this system can clearly determine the ratio of transgene-positive cells in the entire population at the genomic level. Using sc-ddPCR, we analyzed the engraftment of vector-transduced cells in two patients with severe combined immunodeficiency (SCID) who were treated with SCGT. Sufficient engraftment of the transduced cells was limited to the T cell lineage in peripheral blood (PB), and a small percentage of CD34 + cells exhibited vector integration in bone marrow, indicating that the transgene-positive cells in PB might have differentiated from a small population of stem cells or lineage-restricted precursor cells. sc-ddPCR is a simplified and powerful tool for the detailed assessment of transgene-positive cell distribution in patients treated with SCGT.

High-throughput full-length single-cell mRNA-seq of rare cells.

PubMed

Ooi, Chin Chun; Mantalas, Gary L; Koh, Winston; Neff, Norma F; Fuchigami, Teruaki; Wong, Dawson J; Wilson, Robert J; Park, Seung-Min; Gambhir, Sanjiv S; Quake, Stephen R; Wang, Shan X

2017-01-01

Single-cell characterization techniques, such as mRNA-seq, have been applied to a diverse range of applications in cancer biology, yielding great insight into mechanisms leading to therapy resistance and tumor clonality. While single-cell techniques can yield a wealth of information, a common bottleneck is the lack of throughput, with many current processing methods being limited to the analysis of small volumes of single cell suspensions with cell densities on the order of 107 per mL. In this work, we present a high-throughput full-length mRNA-seq protocol incorporating a magnetic sifter and magnetic nanoparticle-antibody conjugates for rare cell enrichment, and Smart-seq2 chemistry for sequencing. We evaluate the efficiency and quality of this protocol with a simulated circulating tumor cell system, whereby non-small-cell lung cancer cell lines (NCI-H1650 and NCI-H1975) are spiked into whole blood, before being enriched for single-cell mRNA-seq by EpCAM-functionalized magnetic nanoparticles and the magnetic sifter. We obtain high efficiency (> 90%) capture and release of these simulated rare cells via the magnetic sifter, with reproducible transcriptome data. In addition, while mRNA-seq data is typically only used for gene expression analysis of transcriptomic data, we demonstrate the use of full-length mRNA-seq chemistries like Smart-seq2 to facilitate variant analysis of expressed genes. This enables the use of mRNA-seq data for differentiating cells in a heterogeneous population by both their phenotypic and variant profile. In a simulated heterogeneous mixture of circulating tumor cells in whole blood, we utilize this high-throughput protocol to differentiate these heterogeneous cells by both their phenotype (lung cancer versus white blood cells), and mutational profile (H1650 versus H1975 cells), in a single sequencing run. This high-throughput method can help facilitate single-cell analysis of rare cell populations, such as circulating tumor or endothelial cells, with demonstrably high-quality transcriptomic data.

Characterization of circulating tumor cell aggregates identified in patients with epithelial tumors

NASA Astrophysics Data System (ADS)

Cho, Edward H.; Wendel, Marco; Luttgen, Madelyn; Yoshioka, Craig; Marrinucci, Dena; Lazar, Daniel; Schram, Ethan; Nieva, Jorge; Bazhenova, Lyudmila; Morgan, Alison; Ko, Andrew H.; Korn, W. Michael; Kolatkar, Anand; Bethel, Kelly; Kuhn, Peter

2012-02-01

Circulating tumor cells (CTCs) have been implicated as a population of cells that may seed metastasis and venous thromboembolism (VTE), two major causes of mortality in cancer patients. Thus far, existing CTC detection technologies have been unable to reproducibly detect CTC aggregates in order to address what contribution CTC aggregates may make to metastasis or VTE. We report here an enrichment-free immunofluorescence detection method that can reproducibly detect and enumerate homotypic CTC aggregates in patient samples. We identified CTC aggregates in 43% of 86 patient samples. The fraction of CTC aggregation was investigated in blood draws from 24 breast, 14 non-small cell lung, 18 pancreatic, 15 prostate stage IV cancer patients and 15 normal blood donors. Both single CTCs and CTC aggregates were measured to determine whether differences exist in the physical characteristics of these two populations. Cells contained in CTC aggregates had less area and length, on average, than single CTCs. Nuclear to cytoplasmic ratios between single CTCs and CTC aggregates were similar. This detection method may assist future studies in determining which population of cells is more physically likely to contribute to metastasis and VTE.

Single-cell-based breeding: Rational strategy for the establishment of cell lines from a single cell with the most favorable properties.

PubMed

Yoshimoto, Nobuo; Kuroda, Shun'ichi

2014-04-01

For efficient biomolecule production (e.g., antibodies, recombinant proteins), mammalian cells with high expression rates should be selected from cell libraries, propagated while maintaining a homogenous expression rate, and subsequently stabilized at their high expression rate. Clusters of isogenic cells (i.e., colonies) have been used for these processes. However, cellular heterogeneity makes it difficult to obtain cell lines with the highest expression rates by using single-colony-based breeding. Furthermore, even among the single cells in an isogenic cell population, the desired cell properties fluctuate stochastically during long-term culture. Therefore, although the molecular mechanisms underlying stochastic fluctuation are poorly understood, it is necessary to establish excellent cell lines in order to breed single cells to have higher expression, higher stability, and higher homogeneity while suppressing stochastic fluctuation (i.e., single-cell-based breeding). In this review, we describe various methods for manipulating single cells and facilitating single-cell analysis in order to better understand stochastic fluctuation. We demonstrated that single-cell-based breeding is practical and promising by using a high-throughput automated system to analyze and manipulate single cells. Copyright © 2013 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Identity and Diversity of Human Peripheral Th and T Regulatory Cells Defined by Single-Cell Mass Cytometry.

PubMed

Kunicki, Matthew A; Amaya Hernandez, Laura C; Davis, Kara L; Bacchetta, Rosa; Roncarolo, Maria-Grazia

2018-01-01

Human CD3 + CD4 + Th cells, FOXP3 + T regulatory (Treg) cells, and T regulatory type 1 (Tr1) cells are essential for ensuring peripheral immune response and tolerance, but the diversity of Th, Treg, and Tr1 cell subsets has not been fully characterized. Independent functional characterization of human Th1, Th2, Th17, T follicular helper (Tfh), Treg, and Tr1 cells has helped to define unique surface molecules, transcription factors, and signaling profiles for each subset. However, the adequacy of these markers to recapitulate the whole CD3 + CD4 + T cell compartment remains questionable. In this study, we examined CD3 + CD4 + T cell populations by single-cell mass cytometry. We characterize the CD3 + CD4 + Th, Treg, and Tr1 cell populations simultaneously across 23 memory T cell-associated surface and intracellular molecules. High-dimensional analysis identified several new subsets, in addition to the already defined CD3 + CD4 + Th, Treg, and Tr1 cell populations, for a total of 11 Th cell, 4 Treg, and 1 Tr1 cell subsets. Some of these subsets share markers previously thought to be selective for Treg, Th1, Th2, Th17, and Tfh cells, including CD194 (CCR4) + FOXP3 + Treg and CD183 (CXCR3) + T-bet + Th17 cell subsets. Unsupervised clustering displayed a phenotypic organization of CD3 + CD4 + T cells that confirmed their diversity but showed interrelation between the different subsets, including similarity between Th1-Th2-Tfh cell populations and Th17 cells, as well as similarity of Th2 cells with Treg cells. In conclusion, the use of single-cell mass cytometry provides a systems-level characterization of CD3 + CD4 + T cells in healthy human blood, which represents an important baseline reference to investigate abnormalities of different subsets in immune-mediated pathologies. Copyright © 2017 by The American Association of Immunologists, Inc.

Cryptosporidium as a testbed for single cell genome characterization of unicellular eukaryotes.

PubMed

Troell, Karin; Hallström, Björn; Divne, Anna-Maria; Alsmark, Cecilia; Arrighi, Romanico; Huss, Mikael; Beser, Jessica; Bertilsson, Stefan

2016-06-23

Infectious disease involving multiple genetically distinct populations of pathogens is frequently concurrent, but difficult to detect or describe with current routine methodology. Cryptosporidium sp. is a widespread gastrointestinal protozoan of global significance in both animals and humans. It cannot be easily maintained in culture and infections of multiple strains have been reported. To explore the potential use of single cell genomics methodology for revealing genome-level variation in clinical samples from Cryptosporidium-infected hosts, we sorted individual oocysts for subsequent genome amplification and full-genome sequencing. Cells were identified with fluorescent antibodies with an 80 % success rate for the entire single cell genomics workflow, demonstrating that the methodology can be applied directly to purified fecal samples. Ten amplified genomes from sorted single cells were selected for genome sequencing and compared both to the original population and a reference genome in order to evaluate the accuracy and performance of the method. Single cell genome coverage was on average 81 % even with a moderate sequencing effort and by combining the 10 single cell genomes, the full genome was accounted for. By a comparison to the original sample, biological variation could be distinguished and separated from noise introduced in the amplification. As a proof of principle, we have demonstrated the power of applying single cell genomics to dissect infectious disease caused by closely related parasite species or subtypes. The workflow can easily be expanded and adapted to target other protozoans, and potential applications include mapping genome-encoded traits, virulence, pathogenicity, host specificity and resistance at the level of cells as truly meaningful biological units.

Two-dimensional single-cell patterning with one cell per well driven by surface acoustic waves

PubMed Central

Collins, David J.; Morahan, Belinda; Garcia-Bustos, Jose; Doerig, Christian; Plebanski, Magdalena; Neild, Adrian

2015-01-01

In single-cell analysis, cellular activity and parameters are assayed on an individual, rather than population-average basis. Essential to observing the activity of these cells over time is the ability to trap, pattern and retain them, for which previous single-cell-patterning work has principally made use of mechanical methods. While successful as a long-term cell-patterning strategy, these devices remain essentially single use. Here we introduce a new method for the patterning of multiple spatially separated single particles and cells using high-frequency acoustic fields with one cell per acoustic well. We characterize and demonstrate patterning for both a range of particle sizes and the capture and patterning of cells, including human lymphocytes and red blood cells infected by the malarial parasite Plasmodium falciparum. This ability is made possible by a hitherto unexplored regime where the acoustic wavelength is on the same order as the cell dimensions. PMID:26522429

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

Robust measurement of telomere length in single cells

PubMed Central

Wang, Fang; Pan, Xinghua; Kalmbach, Keri; Seth-Smith, Michelle L.; Ye, Xiaoying; Antumes, Danielle M. F.; Yin, Yu; Liu, Lin; Keefe, David L.; Weissman, Sherman M.

2013-01-01

Measurement of telomere length currently requires a large population of cells, which masks telomere length heterogeneity in single cells, or requires FISH in metaphase arrested cells, posing technical challenges. A practical method for measuring telomere length in single cells has been lacking. We established a simple and robust approach for single-cell telomere length measurement (SCT-pqPCR). We first optimized a multiplex preamplification specific for telomeres and reference genes from individual cells, such that the amplicon provides a consistent ratio (T/R) of telomeres (T) to the reference genes (R) by quantitative PCR (qPCR). The average T/R ratio of multiple single cells corresponded closely to that of a given cell population measured by regular qPCR, and correlated with those of telomere restriction fragments (TRF) and quantitative FISH measurements. Furthermore, SCT-pqPCR detected the telomere length for quiescent cells that are inaccessible by quantitative FISH. The reliability of SCT-pqPCR also was confirmed using sister cells from two cell embryos. Telomere length heterogeneity was identified by SCT-pqPCR among cells of various human and mouse cell types. We found that the T/R values of human fibroblasts at later passages and from old donors were lower and more heterogeneous than those of early passages and from young donors, that cancer cell lines show heterogeneous telomere lengths, that human oocytes and polar bodies have nearly identical telomere lengths, and that the telomere lengths progressively increase from the zygote, two-cell to four-cell embryo. This method will facilitate understanding of telomere heterogeneity and its role in tumorigenesis, aging, and associated diseases. PMID:23661059

Epigenetics reloaded: the single-cell revolution.

PubMed

Bheda, Poonam; Schneider, Robert

2014-11-01

Mechanistically, how epigenetic states are inherited through cellular divisions remains an important open question in the chromatin field and beyond. Defining the heritability of epigenetic states and the underlying chromatin-based mechanisms within a population of cells is complicated due to cell heterogeneity combined with varying levels of stability of these states; thus, efforts must be focused toward single-cell analyses. The approaches presented here constitute the forefront of epigenetics research at the single-cell level using classic and innovative methods to dissect epigenetics mechanisms from the limited material available in a single cell. This review further outlines exciting future avenues of research to address the significance of epigenetic heterogeneity and the contributions of microfluidics technologies to single-cell isolation and analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mapping heterogeneity in patient-derived melanoma cultures by single-cell RNA-seq

PubMed Central

Loeffler-Wirth, Henry; Hopp, Lydia; Schadendorf, Dirk; Schartl, Manfred; Anderegg, Ulf; Camp, Gray; Treutlein, Barbara; Binder, Hans; Kunz, Manfred

2017-01-01

Recent technological advances in single-cell genomics make it possible to analyze cellular heterogeneity of tumor samples. Here, we applied single-cell RNA-seq to measure the transcriptomes of 307 single cells cultured from three biopsies of three different patients with a BRAF/NRAS wild type, BRAF mutant/NRAS wild type and BRAF wild type/NRAS mutant melanoma metastasis, respectively. Analysis based on self-organizing maps identified sub-populations defined by multiple gene expression modules involved in proliferation, oxidative phosphorylation, pigmentation and cellular stroma. Gene expression modules had prognostic relevance when compared with gene expression data from published melanoma samples and patient survival data. We surveyed kinome expression patterns across sub-populations of the BRAF/NRAS wild type sample and found that CDK4 and CDK2 were consistently highly expressed in the majority of cells, suggesting that these kinases might be involved in melanoma progression. Treatment of cells with the CDK4 inhibitor palbociclib restricted cell proliferation to a similar, and in some cases greater, extent than MAPK inhibitors. Finally, we identified a low abundant sub-population in this sample that highly expressed a module containing ABC transporter ABCB5, surface markers CD271 and CD133, and multiple aldehyde dehydrogenases (ALDHs). Patient-derived cultures of the BRAF mutant/NRAS wild type and BRAF wild type/NRAS mutant metastases showed more homogeneous single-cell gene expression patterns with gene expression modules for proliferation and ABC transporters. Taken together, our results describe an intertumor and intratumor heterogeneity in melanoma short-term cultures which might be relevant for patient survival, and suggest promising targets for new treatment approaches in melanoma therapy. PMID:27903987

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

NASA Astrophysics Data System (ADS)

Teschendorff, Andrew E.; Enver, Tariq

2017-06-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes.

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

PubMed Central

Teschendorff, Andrew E.; Enver, Tariq

2017-01-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes. PMID:28569836

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

Single Cell Analysis: From Technology to Biology and Medicine.

PubMed

Pan, Xinghua

2014-01-01

Single-cell analysis heralds a new era that allows "omics" analysis, notably genomics, transcriptomics, epigenomics and proteomics at the single-cell level. It enables the identification of the minor subpopulations that may play a critical role in a biological process of a population of cells, which conventionally are regarded as homogeneous. It provides an ultra-sensitive tool to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. It also facilitates the clinical investigation of patients when a very low quantity or a single cell is available for analysis, such as noninvasive prenatal diagnosis and cancer screening, and genetic evaluation for in vitro fertilization. Within a few short years, single-cell analysis, especially whole genomic sequencing and transcriptomic sequencing, is becoming robust and broadly accessible, although not yet a routine practice. Here, with single cell RNA-seq emphasized, an overview of the discipline, progresses, and prospects of single-cell analysis and its applications in biology and medicine are given with a series of logic and theoretical considerations.

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.

The Effect of Single Pyramidal Neuron Firing Within Layer 2/3 and Layer 4 in Mouse V1.

PubMed

Meyer, Jochen F; Golshani, Peyman; Smirnakis, Stelios M

2018-01-01

The influence of cortical cell spiking activity on nearby cells has been studied extensively in vitro . Less is known, however, about the impact of single cell firing on local cortical networks in vivo . In a pioneering study, Kwan and Dan (Kwan and Dan, 2012) reported that in mouse layer 2/3 (L2/3), under anesthesia , stimulating a single pyramidal cell recruits ~2.1% of neighboring units. Here we employ two-photon calcium imaging in layer 2/3 of mouse V1, in conjunction with single-cell patch clamp stimulation in layer 2/3 or layer 4, to probe, in both the awake and lightly anesthetized states , how (i) activating single L2/3 pyramidal neurons recruits neighboring units within L2/3 and from layer 4 (L4) to L2/3, and whether (ii) activating single pyramidal neurons changes population activity in local circuit. To do this, it was essential to develop an algorithm capable of quantifying how sensitive the calcium signal is at detecting effectively recruited units ("followers"). This algorithm allowed us to estimate the chance of detecting a follower as a function of the probability that an epoch of stimulation elicits one extra action potential (AP) in the follower cell. Using this approach, we found only a small fraction (<0.75%) of L2/3 cells to be significantly activated within a radius of ~200 μm from a stimulated neighboring L2/3 pyramidal cell. This fraction did not change significantly in the awake vs. the lightly anesthetized state, nor when stimulating L2/3 vs. underlying L4 pyramidal neurons. These numbers are in general agreement with, though lower than, the percentage of neighboring cells (2.1% pyramidal cells and interneurons combined) reported by Kwan and Dan to be activated upon stimulating single L2/3 pyramidal neurons under anesthesia (Kwan and Dan, 2012). Interestingly, despite the small number of individual units found to be reliably driven, we did observe a modest but significant elevation in aggregate population responses compared to sham stimulation. This underscores the distributed impact that single cell stimulation has on neighboring microcircuit responses, revealing only a small minority of relatively strongly connected partners. Patch-clamp stimulation in conjunction with 2-photon imaging shows that activating single layer-2/3 or layer-4 pyramidal neurons produces few (<1% of local units) reliable single-cell followers in L2/3 of mouse area V1, either under light anesthesia or in quiet wakefulness: instead, single cell stimulation was found to elevate aggregate population activity in a weak but highly distributed fashion.

New Frontiers and Challenges for Single-Cell Electrochemical Analysis.

PubMed

Zhang, Jingjing; Zhou, Junyu; Pan, Rongrong; Jiang, Dechen; Burgess, James D; Chen, Hong-Yuan

2018-02-23

Previous measurements of cell populations might obscure many important cellular differences, and new strategies for single-cell analyses are urgently needed to re-examine these fundamental biological principles for better diagnosis and treatment of diseases. Electrochemistry is a robust technique for the analysis of single living cells that has the advantages of minor interruption of cellular activity and provides the capability of high spatiotemporal resolution. The achievements of the past 30 years have revealed significant information about the exocytotic events of single cells to elucidate the mechanisms of cellular activity. Currently, the rapid developments of micro/nanofabrication and optoelectronic technologies drive the development of multifunctional electrodes and novel electrochemical approaches with higher resolution for single cells. In this Perspective, three new frontiers in this field, namely, electrochemical microscopy, intracellular analysis, and single-cell analysis in a biological system (i.e., neocortex and retina), are reviewed. The unique features and remaining challenges of these techniques are discussed.

Single-cell transcriptome analysis of fish immune cells provides insight into the evolution of vertebrate immune cell types.

PubMed

Carmona, Santiago J; Teichmann, Sarah A; Ferreira, Lauren; Macaulay, Iain C; Stubbington, Michael J T; Cvejic, Ana; Gfeller, David

2017-03-01

The immune system of vertebrate species consists of many different cell types that have distinct functional roles and are subject to different evolutionary pressures. Here, we first analyzed conservation of genes specific for all major immune cell types in human and mouse. Our results revealed higher gene turnover and faster evolution of trans -membrane proteins in NK cells compared with other immune cell types, and especially T cells, but similar conservation of nuclear and cytoplasmic protein coding genes. To validate these findings in a distant vertebrate species, we used single-cell RNA sequencing of lck:GFP cells in zebrafish and obtained the first transcriptome of specific immune cell types in a nonmammalian species. Unsupervised clustering and single-cell TCR locus reconstruction identified three cell populations, T cells, a novel type of NK-like cells, and a smaller population of myeloid-like cells. Differential expression analysis uncovered new immune-cell-specific genes, including novel immunoglobulin-like receptors, and neofunctionalization of recently duplicated paralogs. Evolutionary analyses confirmed the higher gene turnover of trans -membrane proteins in NK cells compared with T cells in fish species, suggesting that this is a general property of immune cell types across all vertebrates. © 2017 Carmona et al.; Published by Cold Spring Harbor Laboratory Press.

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

Single-cell printer: automated, on demand, and label free.

PubMed

Gross, Andre; Schöndube, Jonas; Niekrawitz, Sonja; Streule, Wolfgang; Riegger, Lutz; Zengerle, Roland; Koltay, Peter

2013-12-01

Within the past years, single-cell analysis has developed into a key topic in cell biology to study cellular functions that are not accessible by investigation of larger cell populations. Engineering approaches aiming to access single cells to extract information about their physiology, phenotype, and genotype at the single-cell level are going manifold ways, meanwhile allowing separation, sorting, culturing, and analysis of individual cells. Based on our earlier research toward inkjet-like printing of single cells, this article presents further characterization results obtained with a fully automated prototype instrument for printing of single living cells in a noncontact inkjet-like manner. The presented technology is based on a transparent microfluidic drop-on-demand dispenser chip coupled with a camera-assisted automatic detection system. Cells inside the chip are detected and classified with this detection system before they are expelled from the nozzle confined in microdroplets, thus enabling a "one cell per droplet" printing mode. To demonstrate the prototype instrument's suitability for biological and biomedical applications, basic experiments such as printing of single-bead and cell arrays as well as deposition and culture of single cells in microwell plates are presented. Printing efficiencies greater than 80% and viability rates about 90% were achieved.

Individual motile CD4+ T cells can participate in efficient multi-killing through conjugation to multiple tumor cells

PubMed Central

Liadi, Ivan; Singh, Harjeet; Romain, Gabrielle; Rey-Villamizar, Nicolas; Merouane, Amine; Adolacion, Jay R T.; Kebriaei, Partow; Huls, Helen; Qiu, Peng; Roysam, Badrinath; Cooper, Laurence J.N.; Varadarajan, Navin

2015-01-01

T cells genetically modified to express a CD19-specific chimeric antigen receptor (CAR) for the investigational treatment of B-cell malignancies comprise a heterogeneous population, and their ability to persist and participate in serial killing of tumor cells is a predictor of therapeutic success. We implemented Timelapse Imaging Microscopy In Nanowell Grids (TIMING) to provide direct evidence that CD4+CAR+ T cells (CAR4 cells) can engage in multi-killing via simultaneous conjugation to multiple tumor cells. Comparisons of the CAR4 cells and CD8+CAR+ T cells (CAR8 cells) demonstrate that while CAR4 cells can participate in killing and multi-killing, they do so at slower rates, likely due to the lower Granzyme B content. Significantly, in both sets of T cells, a minor sub-population of individual T cells identified by their high motility, demonstrated efficient killing of single tumor cells. By comparing both the multi-killer and single killer CAR+ T cells it appears that the propensity and kinetics of T-cell apoptosis was modulated by the number of functional conjugations. T cells underwent rapid apoptosis, and at higher frequencies, when conjugated to single tumor cells in isolation and this effect was more pronounced on CAR8 cells. Our results suggest that the ability of CAR+ T cells to participate in multi-killing should be evaluated in the context of their ability to resist activation induced cell death (AICD). We anticipate that TIMING may be utilized to rapidly determine the potency of T-cell populations and may facilitate the design and manufacture of next-generation CAR+ T cells with improved efficacy. PMID:25711538

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

PubMed

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

2015-03-03

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

Single-cell transcriptome analysis of fish immune cells provides insight into the evolution of vertebrate immune cell types

PubMed Central

Ferreira, Lauren; Macaulay, Iain C.; Stubbington, Michael J.T.

2017-01-01

The immune system of vertebrate species consists of many different cell types that have distinct functional roles and are subject to different evolutionary pressures. Here, we first analyzed conservation of genes specific for all major immune cell types in human and mouse. Our results revealed higher gene turnover and faster evolution of trans-membrane proteins in NK cells compared with other immune cell types, and especially T cells, but similar conservation of nuclear and cytoplasmic protein coding genes. To validate these findings in a distant vertebrate species, we used single-cell RNA sequencing of lck:GFP cells in zebrafish and obtained the first transcriptome of specific immune cell types in a nonmammalian species. Unsupervised clustering and single-cell TCR locus reconstruction identified three cell populations, T cells, a novel type of NK-like cells, and a smaller population of myeloid-like cells. Differential expression analysis uncovered new immune-cell–specific genes, including novel immunoglobulin-like receptors, and neofunctionalization of recently duplicated paralogs. Evolutionary analyses confirmed the higher gene turnover of trans-membrane proteins in NK cells compared with T cells in fish species, suggesting that this is a general property of immune cell types across all vertebrates. PMID:28087841

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

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Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-28

... cell regeneration in damaged tissue, and examine the regulatory mechanisms for metabolic activity in... monitor how large populations of cells develop into a coherent circuit that capably detects directional... from the dendrites of a single neuron or large numbers of cells in a neuronal population. The...

High throughput single cell counting in droplet-based microfluidics.

PubMed

Lu, Heng; Caen, Ouriel; Vrignon, Jeremy; Zonta, Eleonora; El Harrak, Zakaria; Nizard, Philippe; Baret, Jean-Christophe; Taly, Valérie

2017-05-02

Droplet-based microfluidics is extensively and increasingly used for high-throughput single-cell studies. However, the accuracy of the cell counting method directly impacts the robustness of such studies. We describe here a simple and precise method to accurately count a large number of adherent and non-adherent human cells as well as bacteria. Our microfluidic hemocytometer provides statistically relevant data on large populations of cells at a high-throughput, used to characterize cell encapsulation and cell viability during incubation in droplets.

Tracking single hematopoietic stem cells in vivo using high-throughput sequencing in conjunction with viral genetic barcoding

PubMed Central

Lu, Rong; Neff, Norma F.; Quake, Stephen R.; Weissman, Irving L.

2011-01-01

Disentangling cellular heterogeneity is a challenge in many fields, particularly in the stem cell and cancer biology fields. Here, we demonstrate how to combine viral genetic barcoding with high-throughput sequencing to track single cells in a heterogeneous population. We use this technique to track the in vivo differentiation of unitary hematopoietic stem cells (HSCs). The results are consistent with single cell transplantation studies, but require two orders of magnitude fewer mice. In addition to its high throughput, the high sensitivity of the technique allows for a direct examination of the clonality of sparse cell populations such as HSCs. We show how these capabilities offer a clonal perspective of the HSC differentiation process. In particular, our data suggests that HSCs do not equally contribute to blood cells after irradiation-mediated transplantation, and that two distinct HSC differentiation patterns co-exist in the same recipient mouse post irradiation. This technique can be applied to any viral accessible cell type for both in vitro and in vivo processes. PMID:21964413

High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy.

PubMed

Guo, Baoshan; Lei, Cheng; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke

2017-05-01

The development of reliable, sustainable, and economical sources of alternative fuels to petroleum is required to tackle the global energy crisis. One such alternative is microalgal biofuel, which is expected to play a key role in reducing the detrimental effects of global warming as microalgae absorb atmospheric CO 2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid amounts and fail to characterize a diverse population of microalgal cells with single-cell resolution in a non-invasive and interference-free manner. Here high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy was demonstrated. In particular, Euglena gracilis, an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement), within lipid droplets was investigated. The optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch quantitative phase microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase maps of every single cell at a high throughput of 10,000 cells/s, enabling accurate cell classification without the need for fluorescent staining. Specifically, the dataset was used to characterize heterogeneous populations of E. gracilis cells under two different culture conditions (nitrogen-sufficient and nitrogen-deficient) and achieve the cell classification with an error rate of only 2.15%. The method holds promise as an effective analytical tool for microalgae-based biofuel production. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Cell lineage patterns in the shoot meristem of the sunflower embryo in the dry seed

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

Jegla, D.E.; Sussex, I.M.

1989-01-01

We mapped the fate of cells in the shoot meristem of the dry-seed embryo of sunflower, Helianthus annuus L. cv. Peredovic, using irradiation-induced somatic sectors. We analyzed 249 chlorophyll-deficient or glabrous (hairless) sectors generated in 236 plants. Most sectors observed in the inflorescence extended into vegetative nodes. Thus cell lineages that ultimately gave rise to reproductive structures also contributed to vegetative structures. No single sector extended the entire length of the shoot. Thus the shoot is not derived from one or a few apical initials. Rather, the position, vertical extent, and width of the sectors at different levels of themore » shoot suggest that the shoot is derived from three to four circumferential populations of cells in each of three cell layers of the embryo meristem. Sectors had no common boundaries even in plants with two or three independent sectors, but varied in extent and overlapped along the length of the shoot. Thus individual cells in a single circumferential population behaved independently to contribute lineages of different vertical extents to the growing shoot. The predicted number of circumferential populations of cells as well as the apparent cell number in each population was consistent with the actual number of cells in the embryo meristem observed in histological sections.« less

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

PubMed

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

2014-11-01

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

Nanopipettes as Monitoring Probes for the Single Living Cell: State of the Art and Future Directions in Molecular Biology.

PubMed

Bulbul, Gonca; Chaves, Gepoliano; Olivier, Joseph; Ozel, Rifat Emrah; Pourmand, Nader

2018-06-06

Examining the behavior of a single cell within its natural environment is valuable for understanding both the biological processes that control the function of cells and how injury or disease lead to pathological change of their function. Single-cell analysis can reveal information regarding the causes of genetic changes, and it can contribute to studies on the molecular basis of cell transformation and proliferation. By contrast, whole tissue biopsies can only yield information on a statistical average of several processes occurring in a population of different cells. Electrowetting within a nanopipette provides a nanobiopsy platform for the extraction of cellular material from single living cells. Additionally, functionalized nanopipette sensing probes can differentiate analytes based on their size, shape or charge density, making the technology uniquely suited to sensing changes in single-cell dynamics. In this review, we highlight the potential of nanopipette technology as a non-destructive analytical tool to monitor single living cells, with particular attention to integration into applications in molecular biology.

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

PubMed

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

2017-02-10

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

Capturing Three-Dimensional Genome Organization in Individual Cells by Single-Cell Hi-C.

PubMed

Nagano, Takashi; Wingett, Steven W; Fraser, Peter

2017-01-01

Hi-C is a powerful method to investigate genome-wide, higher-order chromatin and chromosome conformations averaged from a population of cells. To expand the potential of Hi-C for single-cell analysis, we developed single-cell Hi-C. Similar to the existing "ensemble" Hi-C method, single-cell Hi-C detects proximity-dependent ligation events between cross-linked and restriction-digested chromatin fragments in cells. A major difference between the single-cell Hi-C and ensemble Hi-C protocol is that the proximity-dependent ligation is carried out in the nucleus. This allows the isolation of individual cells in which nearly the entire Hi-C procedure has been carried out, enabling the production of a Hi-C library and data from individual cells. With this new method, we studied genome conformations and found evidence for conserved topological domain organization from cell to cell, but highly variable interdomain contacts and chromosome folding genome wide. In addition, we found that the single-cell Hi-C protocol provided cleaner results with less technical noise suggesting it could be used to improve the ensemble Hi-C technique.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Single-cell mass cytometry and transcriptome profiling reveal the impact of graphene on human immune cells.

PubMed

Orecchioni, Marco; Bedognetti, Davide; Newman, Leon; Fuoco, Claudia; Spada, Filomena; Hendrickx, Wouter; Marincola, Francesco M; Sgarrella, Francesco; Rodrigues, Artur Filipe; Ménard-Moyon, Cécilia; Cesareni, Gianni; Kostarelos, Kostas; Bianco, Alberto; Delogu, Lucia G

2017-10-24

Understanding the biomolecular interactions between graphene and human immune cells is a prerequisite for its utilization as a diagnostic or therapeutic tool. To characterize the complex interactions between graphene and immune cells, we propose an integrative analytical pipeline encompassing the evaluation of molecular and cellular parameters. Herein, we use single-cell mass cytometry to dissect the effects of graphene oxide (GO) and GO functionalized with amino groups (GONH 2 ) on 15 immune cell populations, interrogating 30 markers at the single-cell level. Next, the integration of single-cell mass cytometry with genome-wide transcriptome analysis shows that the amine groups reduce the perturbations caused by GO on cell metabolism and increase biocompatibility. Moreover, GONH 2 polarizes T-cell and monocyte activation toward a T helper-1/M1 immune response. This study describes an innovative approach for the analysis of the effects of nanomaterials on distinct immune cells, laying the foundation for the incorporation of single-cell mass cytometry on the experimental pipeline.

Characterizing polymorphic inversions in human genomes by single-cell sequencing

PubMed Central

Sanders, Ashley D.; Hills, Mark; Porubský, David; Guryev, Victor; Falconer, Ester; Lansdorp, Peter M.

2016-01-01

Identifying genomic features that differ between individuals and cells can help uncover the functional variants that drive phenotypes and disease susceptibilities. For this, single-cell studies are paramount, as it becomes increasingly clear that the contribution of rare but functional cellular subpopulations is important for disease prognosis, management, and progression. Until now, studying these associations has been challenged by our inability to map structural rearrangements accurately and comprehensively. To overcome this, we coupled single-cell sequencing of DNA template strands (Strand-seq) with custom analysis software to rapidly discover, map, and genotype genomic rearrangements at high resolution. This allowed us to explore the distribution and frequency of inversions in a heterogeneous cell population, identify several polymorphic domains in complex regions of the genome, and locate rare alleles in the reference assembly. We then mapped the entire genomic complement of inversions within two unrelated individuals to characterize their distinct inversion profiles and built a nonredundant global reference of structural rearrangements in the human genome. The work described here provides a powerful new framework to study structural variation and genomic heterogeneity in single-cell samples, whether from individuals for population studies or tissue types for biomarker discovery. PMID:27472961

Cloning of Plasmodium falciparum by single-cell sorting

PubMed Central

Miao, Jun; Li, Xiaolian; Cui, Liwang

2010-01-01

Malaria parasite cloning is traditionally carried out mainly by using the limiting dilution method, which is laborious, imprecise, and unable to distinguish multiply-infected RBCs. In this study, we used a parasite engineered to express green fluorescent protein (GFP) to evaluate a single-cell sorting method for rapidly cloning Plasmodium falciparum. By dividing a two dimensional scattergram from a cell sorter into 17 gates, we determined the parameters for isolating singly-infected erythrocytes and sorted them into individual cultures. Pre-gating of the engineered parasites for GFP allowed the isolation of almost 100% GFP-positive clones. Compared with the limiting dilution method, the number of parasite clones obtained by single-cell sorting was much higher. Molecular analyses showed that parasite isolates obtained by single-cell sorting were highly homogenous. This highly efficient single-cell sorting method should prove very useful for cloning both P. falciparum laboratory populations from genetic manipulation experiments and clinical samples. PMID:20435038

Self-identity reprogrammed by a single residue switch in a cell surface receptor of a social bacterium.

PubMed

Cao, Pengbo; Wall, Daniel

2017-04-04

The ability to recognize close kin confers survival benefits on single-celled microbes that live in complex and changing environments. Microbial kinship detection relies on perceptible cues that reflect relatedness between individuals, although the mechanisms underlying recognition in natural populations remain poorly understood. In myxobacteria, cells identify related individuals through a polymorphic cell surface receptor, TraA. Recognition of compatible receptors leads to outer membrane exchange among clonemates and fitness consequences. Here, we investigated how a single receptor creates a diversity in recognition across myxobacterial populations. We first show that TraA requires its partner protein TraB to function in cell-cell adhesion. Recognition is shown to be traA allele-specific, where polymorphisms within TraA dictate binding selectivity. We reveal the malleability of TraA recognition, and seemingly minor changes to its variable region reprogram recognition outcomes. Strikingly, we identify a single residue (A/P205) as a molecular switch for TraA recognition. Substitutions at this position change the specificity of a diverse panel of environmental TraA receptors. In addition, we engineered a receptor with unique specificity by simply creating an A205P substitution, suggesting that modest changes in TraA can lead to diversification of new recognition groups in nature. We hypothesize that the malleable property of TraA has allowed it to evolve and create social barriers between myxobacterial populations and in turn avoid adverse interactions with relatives.

Advances in single-cell RNA sequencing and its applications in cancer research.

PubMed

Zhu, Sibo; Qing, Tao; Zheng, Yuanting; Jin, Li; Shi, Leming

2017-08-08

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years' development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects: 1. Methodologies of single-cell RNA-seq 2. Single-cell isolation techniques 3. Single-cell RNA-seq in solid tumor research 4. Single-cell RNA-seq in circulating tumor cell research 5.

Advances in single-cell RNA sequencing and its applications in cancer research

PubMed Central

Zhu, Sibo; Qing, Tao; Zheng, Yuanting; Jin, Li; Shi, Leming

2017-01-01

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years’ development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects: 1. Methodologies of single-cell RNA-seq 2. Single-cell isolation techniques 3. Single-cell RNA-seq in solid tumor research 4. Single-cell RNA-seq in circulating tumor cell research 5. Perspectives PMID:28881849

SCPortalen: human and mouse single-cell centric database

PubMed Central

Noguchi, Shuhei; Böttcher, Michael; Hasegawa, Akira; Kouno, Tsukasa; Kato, Sachi; Tada, Yuhki; Ura, Hiroki; Abe, Kuniya; Shin, Jay W; Plessy, Charles; Carninci, Piero

2018-01-01

Abstract Published single-cell datasets are rich resources for investigators who want to address questions not originally asked by the creators of the datasets. The single-cell datasets might be obtained by different protocols and diverse analysis strategies. The main challenge in utilizing such single-cell data is how we can make the various large-scale datasets to be comparable and reusable in a different context. To challenge this issue, we developed the single-cell centric database ‘SCPortalen’ (http://single-cell.clst.riken.jp/). The current version of the database covers human and mouse single-cell transcriptomics datasets that are publicly available from the INSDC sites. The original metadata was manually curated and single-cell samples were annotated with standard ontology terms. Following that, common quality assessment procedures were conducted to check the quality of the raw sequence. Furthermore, primary data processing of the raw data followed by advanced analyses and interpretation have been performed from scratch using our pipeline. In addition to the transcriptomics data, SCPortalen provides access to single-cell image files whenever available. The target users of SCPortalen are all researchers interested in specific cell types or population heterogeneity. Through the web interface of SCPortalen users are easily able to search, explore and download the single-cell datasets of their interests. PMID:29045713

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.

PubMed

Haghverdi, Laleh; Lun, Aaron T L; Morgan, Michael D; Marioni, John C

2018-06-01

Large-scale single-cell RNA sequencing (scRNA-seq) data sets that are produced in different laboratories and at different times contain batch effects that may compromise the integration and interpretation of the data. Existing scRNA-seq analysis methods incorrectly assume that the composition of cell populations is either known or identical across batches. We present a strategy for batch correction based on the detection of mutual nearest neighbors (MNNs) in the high-dimensional expression space. Our approach does not rely on predefined or equal population compositions across batches; instead, it requires only that a subset of the population be shared between batches. We demonstrate the superiority of our approach compared with existing methods by using both simulated and real scRNA-seq data sets. Using multiple droplet-based scRNA-seq data sets, we demonstrate that our MNN batch-effect-correction method can be scaled to large numbers of cells.

Metabolic heterogeneity in clonal microbial populations.

PubMed

Takhaveev, Vakil; Heinemann, Matthias

2018-02-21

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

An automated image processing routine for segmentation of cell cytoplasms in high-resolution autofluorescence images

NASA Astrophysics Data System (ADS)

Walsh, Alex J.; Skala, Melissa C.

2014-02-01

The heterogeneity of genotypes and phenotypes within cancers is correlated with disease progression and drug-resistant cellular sub-populations. Therefore, robust techniques capable of probing majority and minority cell populations are important both for cancer diagnostics and therapy monitoring. Herein, we present a modified CellProfiler routine to isolate cytoplasmic fluorescence signal on a single cell level from high resolution auto-fluorescence microscopic images.

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

PubMed

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

2007-10-01

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

Single cell magnetic imaging using a quantum diamond microscope

PubMed Central

Park, H.; Weissleder, R.; Yacoby, A.; Lukin, M. D.; Lee, H.; Walsworth, R. L.; Connolly, C. B.

2015-01-01

We apply a quantum diamond microscope to detection and imaging of immunomagnetically labeled cells. This instrument uses nitrogen-vacancy (NV) centers in diamond for correlated magnetic and fluorescence imaging. Our device provides single-cell resolution and two orders of magnitude larger field of view (~1 mm2) than previous NV imaging technologies, enabling practical applications. To illustrate, we quantify cancer biomarkers expressed by rare tumor cells in a large population of healthy cells. PMID:26098019

Probing cellular heterogeneity in cytokine-secreting immune cells using droplet-based microfluidics.

PubMed

Chokkalingam, Venkatachalam; Tel, Jurjen; Wimmers, Florian; Liu, Xin; Semenov, Sergey; Thiele, Julian; Figdor, Carl G; Huck, Wilhelm T S

2013-12-21

Here, we present a platform to detect cytokine (IL-2, IFN-γ, TNF-α) secretion of single, activated T-cells in droplets over time. We use a novel droplet-based microfluidic approach to encapsulate cells in monodisperse agarose droplets together with functionalized cytokine-capture beads for subsequent binding and detection of secreted cytokines from single cells. This method allows high-throughput detection of cellular heterogeneity and maps subsets within cell populations with specific functions.

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.

Linking macroscopic with microscopic neuroanatomy using synthetic neuronal populations.

PubMed

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

2014-10-01

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

Linking Macroscopic with Microscopic Neuroanatomy Using Synthetic Neuronal Populations

PubMed Central

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

2014-01-01

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

Single-Cell RNA-Sequencing Reveals a Continuous Spectrum of Differentiation in Hematopoietic Cells.

PubMed

Macaulay, Iain C; Svensson, Valentine; Labalette, Charlotte; Ferreira, Lauren; Hamey, Fiona; Voet, Thierry; Teichmann, Sarah A; Cvejic, Ana

2016-02-02

The transcriptional programs that govern hematopoiesis have been investigated primarily by population-level analysis of hematopoietic stem and progenitor cells, which cannot reveal the continuous nature of the differentiation process. Here we applied single-cell RNA-sequencing to a population of hematopoietic cells in zebrafish as they undergo thrombocyte lineage commitment. By reconstructing their developmental chronology computationally, we were able to place each cell along a continuum from stem cell to mature cell, refining the traditional lineage tree. The progression of cells along this continuum is characterized by a highly coordinated transcriptional program, displaying simultaneous suppression of genes involved in cell proliferation and ribosomal biogenesis as the expression of lineage specific genes increases. Within this program, there is substantial heterogeneity in the expression of the key lineage regulators. Overall, the total number of genes expressed, as well as the total mRNA content of the cell, decreases as the cells undergo lineage commitment. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

High-throughput single-cell PCR using microfluidic emulsions

NASA Astrophysics Data System (ADS)

Guo, Mira; Mazutis, Linas; Agresti, Jeremy; Sommer, Morten; Dantas, Gautam; Church, George; Turnbaugh, Peter; Weitz, David

2012-02-01

The human gut and other environmental samples contain large populations of diverse bacteria that are poorly characterized and unculturable, yet have many functions relevant to human health. Our goal is to identify exactly which species carry some gene of interest, such as a carbohydrate metabolism gene. Conventional metagenomic assays sequence DNA extracted in bulk from populations of mixed cell types, and are therefore unable to associate a gene of interest with a species-identifying 16S gene, to determine that the two genes originated from the same cell. We solve this problem by microfluidically encapsulating single bacteria cells in drops, using PCR to amplify the two genes inside any drop whose encapsulated cell contains both genes, and sequencing the DNA from those drops that contain both amplification products.

The technology and biology of single-cell RNA sequencing.

PubMed

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

2015-05-21

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

Digital signaling decouples activation probability and population heterogeneity.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Lipniacki, Tomasz; Quake, Stephen R; Tay, Savaş

2015-10-21

Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.

High-throughput label-free screening of euglena gracilis with optofluidic time-stretch quantitative phase microscopy

NASA Astrophysics Data System (ADS)

Guo, Baoshan; Lei, Cheng; Ito, Takuro; Yaxiaer, Yalikun; Kobayashi, Hirofumi; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke

2017-02-01

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, microalgal biofuel is expected to play a key role in reducing the detrimental effects of global warming since microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid contents and fail to characterize a diverse population of microalgal cells with single-cell resolution in a noninvasive and interference-free manner. Here we demonstrate high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy. In particular, we use Euglena gracilis - an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement) within lipid droplets. Our optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch phase-contrast microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase contents of every single cell at a high throughput of 10,000 cells/s. We characterize heterogeneous populations of E. gracilis cells under two different culture conditions to evaluate their lipid production efficiency. Our method holds promise as an effective analytical tool for microalgaebased biofuel production.

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

Local cellular neighborhood controls proliferation in cell competition

PubMed Central

Bove, Anna; Gradeci, Daniel; Fujita, Yasuyuki; Banerjee, Shiladitya; Charras, Guillaume; Lowe, Alan R.

2017-01-01

Cell competition is a quality-control mechanism through which tissues eliminate unfit cells. Cell competition can result from short-range biochemical inductions or long-range mechanical cues. However, little is known about how cell-scale interactions give rise to population shifts in tissues, due to the lack of experimental and computational tools to efficiently characterize interactions at the single-cell level. Here, we address these challenges by combining long-term automated microscopy with deep-learning image analysis to decipher how single-cell behavior determines tissue makeup during competition. Using our high-throughput analysis pipeline, we show that competitive interactions between MDCK wild-type cells and cells depleted of the polarity protein scribble are governed by differential sensitivity to local density and the cell type of each cell’s neighbors. We find that local density has a dramatic effect on the rate of division and apoptosis under competitive conditions. Strikingly, our analysis reveals that proliferation of the winner cells is up-regulated in neighborhoods mostly populated by loser cells. These data suggest that tissue-scale population shifts are strongly affected by cellular-scale tissue organization. We present a quantitative mathematical model that demonstrates the effect of neighbor cell–type dependence of apoptosis and division in determining the fitness of competing cell lines. PMID:28931601

Microchip-Based Single-Cell Functional Proteomics for Biomedical Applications

PubMed Central

Lu, Yao; Yang, Liu; Wei, Wei; Shi, Qihui

2017-01-01

Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that fail to be addressed by traditional population-based methods. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical framework to extract new biology. In this review article, we highlight a few biological and clinical applications in which the microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating well-contolled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies. PMID:28280819

Detecting Antigen-Specific T Cell Responses: From Bulk Populations to Single Cells.

PubMed

Phetsouphanh, Chansavath; Zaunders, John James; Kelleher, Anthony Dominic

2015-08-12

A new generation of sensitive T cell-based assays facilitates the direct quantitation and characterization of antigen-specific T cell responses. Single-cell analyses have focused on measuring the quality and breadth of a response. Accumulating data from these studies demonstrate that there is considerable, previously-unrecognized, heterogeneity. Standard assays, such as the ICS, are often insufficient for characterization of rare subsets of cells. Enhanced flow cytometry with imaging capabilities enables the determination of cell morphology, as well as the spatial localization of the protein molecules within a single cell. Advances in both microfluidics and digital PCR have improved the efficiency of single-cell sorting and allowed multiplexed gene detection at the single-cell level. Delving further into the transcriptome of single-cells using RNA-seq is likely to reveal the fine-specificity of cellular events such as alternative splicing (i.e., splice variants) and allele-specific expression, and will also define the roles of new genes. Finally, detailed analysis of clonally related antigen-specific T cells using single-cell TCR RNA-seq will provide information on pathways of differentiation of memory T cells. With these state of the art technologies the transcriptomics and genomics of Ag-specific T cells can be more definitively elucidated.

Detecting Antigen-Specific T Cell Responses: From Bulk Populations to Single Cells

PubMed Central

Phetsouphanh, Chansavath; Zaunders, John James; Kelleher, Anthony Dominic

2015-01-01

A new generation of sensitive T cell-based assays facilitates the direct quantitation and characterization of antigen-specific T cell responses. Single-cell analyses have focused on measuring the quality and breadth of a response. Accumulating data from these studies demonstrate that there is considerable, previously-unrecognized, heterogeneity. Standard assays, such as the ICS, are often insufficient for characterization of rare subsets of cells. Enhanced flow cytometry with imaging capabilities enables the determination of cell morphology, as well as the spatial localization of the protein molecules within a single cell. Advances in both microfluidics and digital PCR have improved the efficiency of single-cell sorting and allowed multiplexed gene detection at the single-cell level. Delving further into the transcriptome of single-cells using RNA-seq is likely to reveal the fine-specificity of cellular events such as alternative splicing (i.e., splice variants) and allele-specific expression, and will also define the roles of new genes. Finally, detailed analysis of clonally related antigen-specific T cells using single-cell TCR RNA-seq will provide information on pathways of differentiation of memory T cells. With these state of the art technologies the transcriptomics and genomics of Ag-specific T cells can be more definitively elucidated. PMID:26274954

Evidence of drug-response heterogeneity rapidly generated from a single cancer cell.

PubMed

Wang, Rong; Jin, Chengmeng; Hu, Xun

2017-06-20

One cancer cell line is believed to be composed of numerous clones with different drug sensitivity. We sought to investigate the difference of drug-response pattern in clones from a cell line or from a single cell. We showed that 22 clones derived from 4T1 cells were drastically different from each other with respect to drug-response pattern against 11 anticancer drugs and expression profile of 19 genes associated with drug resistance or sensitivity. Similar results were obtained using daughter clones derived from a single 4T1 cell. Each daughter clone showed distinct drug-response pattern and gene expression profile. Similar results were also obtained using Bcap37 cells. We conclude that a single cancer cell can rapidly produce a population of cells with high heterogeneity of drug response and the acquisition of drug-response heterogeneity is random.

Critical high-dimensional state transitions in cell populations or why cancers follow the principle ``What does not kill me makes me stronger''

NASA Astrophysics Data System (ADS)

Huang, Sui

Transitions between high-dimensional attractor states in the quasi-potential landscape of the gene regulatory network, induced by environmental perturbations and/or facilitated by mutational rewiring of the network, underlie cell phenotype switching in development as well as in cancer progression, including acquisition of drug-resistant phenotypes. Considering heterogeneous cell populations as statistical ensembles of cells, and single-cell resolution gene expression profiling of cell populations undergoing a cell phenotype shift allow us now to map the topography of the landscape and its distortion. From snapshots of single-cell expression patterns of a cell population measured during major transitions we compute a quantity that identifies symmetry-breaking destabilization of attractors (bifurcation) and concomitant dimension-reduction of the state space manifold (landscape distortion) which precede critical transitions to new attractor states. The model predicts, and we show experimentally, the almost inevitable generation of aberrant cells associated with such critical transitions in multi-attractor landscapes: therapeutic perturbations which seek to push cancer cells to the apoptotic state, almost always produce ``rebellious'' cells which move in the ``opposite direction'': instead of dying they become more stem-cell-like and malignant. We show experimentally that the inadvertent generation of more malignant cancer cells by therapy indeed results from transition of surviving (but stressed) cells into unforeseen attractor states and not simply from selection of inherently more resistant cells. Thus, cancer cells follow not so much Darwin, as generally thought (survival of the fittest), but rather Nietzsche (What does not kill me makes me stronger). Supported by NIH (NCI, NIGMS), Alberta Innovates.

Visualizing Intrapopulation Hematopoietic Cell Heterogeneity with Self-Organizing Maps of SIMS Data.

PubMed

Mirshafiee, Vahid; Harley, Brendan A C; Kraft, Mary L

2018-05-07

Characterization of the heterogeneity within stem cell populations, which affects their differentiation potential, is necessary for the design of artificial cultures for stem cell expansion. In this study, we assessed whether self-organizing maps (SOMs) of single-cell time-of-flight secondary ion mass spectrometry (TOF-SIMS) data provide insight into the spectral, and thus the related functional heterogeneity between and within three hematopoietic cell populations. SOMs were created of TOF-SIMS data from individual hematopoietic stem and progenitor cells (HSPCs), lineage-committed common lymphoid progenitors (CLPs), and fully differentiated B cells that had been isolated from murine bone marrow via conventional flow cytometry. The positions of these cells on the SOMs and the spectral variation between adjacent map units, shown on the corresponding unified distance matrix (U-matrix), indicated the CLPs exhibited the highest intrapopulation spectral variation, regardless of the age of the donor mice. SOMs of HSPCs, CLPs, and B cells isolated from young and old mice using the same surface antigen profiles revealed the HSPCs exhibited the most age-related spectral variation, whereas B cells exhibited the least. These results demonstrate that SOMs of single-cell spectra enable characterizing the heterogeneity between and within cell populations that lie along distinct differentiation pathways.

Single-Cell Sequencing for Precise Cancer Research: Progress and Prospects.

PubMed

Zhang, Xiaoyan; Marjani, Sadie L; Hu, Zhaoyang; Weissman, Sherman M; Pan, Xinghua; Wu, Shixiu

2016-03-15

Advances in genomic technology have enabled the faithful detection and measurement of mutations and the gene expression profile of cancer cells at the single-cell level. Recently, several single-cell sequencing methods have been developed that permit the comprehensive and precise analysis of the cancer-cell genome, transcriptome, and epigenome. The use of these methods to analyze cancer cells has led to a series of unanticipated discoveries, such as the high heterogeneity and stochastic changes in cancer-cell populations, the new driver mutations and the complicated clonal evolution mechanisms, and the novel identification of biomarkers of variant tumors. These methods and the knowledge gained from their utilization could potentially improve the early detection and monitoring of rare cancer cells, such as circulating tumor cells and disseminated tumor cells, and promote the development of personalized and highly precise cancer therapy. Here, we discuss the current methods for single cancer-cell sequencing, with a strong focus on those practically used or potentially valuable in cancer research, including single-cell isolation, whole genome and transcriptome amplification, epigenome profiling, multi-dimensional sequencing, and next-generation sequencing and analysis. We also examine the current applications, challenges, and prospects of single cancer-cell sequencing. ©2016 American Association for Cancer Research.

Magnetic-Activated Cell Sorting for the Fast and Efficient Separation of Human and Rodent Schwann Cells from Mixed Cell Populations.

PubMed

Ravelo, Kristine M; Andersen, Natalia D; Monje, Paula V

2018-01-01

To date, magnetic-activated cell sorting (MACS) remains a powerful method to isolate distinct cell populations based on differential cell surface labeling. Optimized direct and indirect MACS protocols for cell immunolabeling are presented here as methods to divest Schwann cell (SC) cultures of contaminating cells (specifically, fibroblast cells) and isolate SC populations at different stages of differentiation. This chapter describes (1) the preparation of single-cell suspensions from established human and rat SC cultures, (2) the design and application of cell selection strategies using SC-specific (p75 NGFR , O4, and O1) and fibroblast-specific (Thy-1) markers, and (3) the characterization of both the pre- and post-sorting cell populations. A simple protocol for the growth of hybridoma cell cultures as a source of monoclonal antibodies for cell surface immunolabeling of SCs and fibroblasts is provided as a cost-effective alternative for commercially available products. These steps allow for the timely and efficient recovery of purified SC populations without compromising the viability and biological activity of the cells.

Development of a Prognostic Marker for Lung Cancer Using Analysis of Tumor Evolution

DTIC Science & Technology

2017-08-01

SUPPLEMENTARY NOTES 14. ABSTRACT The goal of this project is to sequence the exomes of single tumor cells from tumors in order to construct evolutionary trees...dissociation, tumor cell isolation, whole genome amplification, and exome sequencing. We have begun to sequence the exomes of single cells and to...of populations, the evolution of tumor cells within a tumor can be diagrammed on a phylogenetic tree. The more diverse a tumor’s phylogenetic tree

High-Throughput Single-Cell RNA Sequencing and Data Analysis.

PubMed

Sagar; Herman, Josip Stefan; Pospisilik, John Andrew; Grün, Dominic

2018-01-01

Understanding biological systems at a single cell resolution may reveal several novel insights which remain masked by the conventional population-based techniques providing an average readout of the behavior of cells. Single-cell transcriptome sequencing holds the potential to identify novel cell types and characterize the cellular composition of any organ or tissue in health and disease. Here, we describe a customized high-throughput protocol for single-cell RNA-sequencing (scRNA-seq) combining flow cytometry and a nanoliter-scale robotic system. Since scRNA-seq requires amplification of a low amount of endogenous cellular RNA, leading to substantial technical noise in the dataset, downstream data filtering and analysis require special care. Therefore, we also briefly describe in-house state-of-the-art data analysis algorithms developed to identify cellular subpopulations including rare cell types as well as to derive lineage trees by ordering the identified subpopulations of cells along the inferred differentiation trajectories.

Droplet microfluidics--a tool for single-cell analysis.

PubMed

Joensson, Haakan N; Andersson Svahn, Helene

2012-12-03

Droplet microfluidics allows the isolation of single cells and reagents in monodisperse picoliter liquid capsules and manipulations at a throughput of thousands of droplets per second. These qualities allow many of the challenges in single-cell analysis to be overcome. Monodispersity enables quantitative control of solute concentrations, while encapsulation in droplets provides an isolated compartment for the single cell and its immediate environment. The high throughput allows the processing and analysis of the tens of thousands to millions of cells that must be analyzed to accurately describe a heterogeneous cell population so as to find rare cell types or access sufficient biological space to find hits in a directed evolution experiment. The low volumes of the droplets make very large screens economically viable. This Review gives an overview of the current state of single-cell analysis involving droplet microfluidics and offers examples where droplet microfluidics can further biological understanding. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study

PubMed Central

Yan, Benedict; Hu, Yongli; Ban, Kenneth H.K.; Tiang, Zenia; Ng, Christopher; Lee, Joanne; Tan, Wilson; Chiu, Lily; Tan, Tin Wee; Seah, Elaine; Ng, Chin Hin; Chng, Wee-Joo; Foo, Roger

2017-01-01

Although bulk high-throughput genomic profiling studies have led to a significant increase in the understanding of cancer biology, there is increasing awareness that bulk profiling approaches do not completely elucidate tumor heterogeneity. Single-cell genomic profiling enables the distinction of tumor heterogeneity, and may improve clinical diagnosis through the identification and characterization of putative subclonal populations. In the present study, the challenges associated with a single-cell genomics profiling workflow for clinical diagnostics were investigated. Single-cell RNA-sequencing (RNA-seq) was performed on 20 cells from an acute myeloid leukemia bone marrow sample. Putative blasts were identified based on their gene expression profiles and principal component analysis was performed to identify outlier cells. Variant calling was performed on the single-cell RNA-seq data. The present pilot study demonstrates a proof of concept for clinical single-cell genomic profiling. The recognized limitations include significant stochastic RNA loss and the relatively low throughput of the current proposed platform. Although the results of the present study are promising, further technological advances and protocol optimization are necessary for single-cell genomic profiling to be clinically viable. PMID:28454300

Droplet Microfluidic Platform for the Determination of Single-Cell Lactate Release.

PubMed

Mongersun, Amy; Smeenk, Ian; Pratx, Guillem; Asuri, Prashanth; Abbyad, Paul

2016-03-15

Cancer cells release high levels of lactate that has been correlated to increased metastasis and tumor recurrence. Single-cell measurements of lactate release can identify malignant cells and help decipher metabolic cancer pathways. We present here a novel droplet microfluidic method that allows the fast and quantitative determination of lactate release in many single cells. Using passive forces, droplets encapsulated cells are positioned in an array. The single-cell lactate release rate is determined from the increase in droplet fluorescence as the lactate is enzymatically converted to a fluorescent product. The method is used to measure the cell-to-cell variance of lactate release in K562 leukemia and U87 glioblastoma cancer cell lines and under the chemical inhibition of lactate efflux. The technique can be used in the study of cancer biology, but more broadly in cell biology, to capture the full range of stochastic variations in glycolysis activity in heterogeneous cell populations in a repeatable and high-throughput manner.

Cloning of Plasmodium falciparum by single-cell sorting.

PubMed

Miao, Jun; Li, Xiaolian; Cui, Liwang

2010-10-01

Malaria parasite cloning is traditionally carried out mainly by using the limiting dilution method, which is laborious, imprecise, and unable to distinguish multiply-infected RBCs. In this study, we used a parasite engineered to express green fluorescent protein (GFP) to evaluate a single-cell sorting method for rapidly cloning Plasmodium falciparum. By dividing a two-dimensional scattergram from a cell sorter into 17 gates, we determined the parameters for isolating singly-infected erythrocytes and sorted them into individual cultures. Pre-gating of the engineered parasites for GFP allowed the isolation of almost 100% GFP-positive clones. Compared with the limiting dilution method, the number of parasite clones obtained by single-cell sorting was much higher. Molecular analyses showed that parasite isolates obtained by single-cell sorting were highly homogenous. This highly efficient single-cell sorting method should prove very useful for cloning both P. falciparum laboratory populations from genetic manipulation experiments and clinical samples. Copyright 2010 Elsevier Inc. All rights reserved.

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.

Response of single bacterial cells to stress gives rise to complex history dependence at the population level

PubMed Central

Mathis, Roland; Ackermann, Martin

2016-01-01

Most bacteria live in ever-changing environments where periods of stress are common. One fundamental question is whether individual bacterial cells have an increased tolerance to stress if they recently have been exposed to lower levels of the same stressor. To address this question, we worked with the bacterium Caulobacter crescentus and asked whether exposure to a moderate concentration of sodium chloride would affect survival during later exposure to a higher concentration. We found that the effects measured at the population level depended in a surprising and complex way on the time interval between the two exposure events: The effect of the first exposure on survival of the second exposure was positive for some time intervals but negative for others. We hypothesized that the complex pattern of history dependence at the population level was a consequence of the responses of individual cells to sodium chloride that we observed: (i) exposure to moderate concentrations of sodium chloride caused delays in cell division and led to cell-cycle synchronization, and (ii) whether a bacterium would survive subsequent exposure to higher concentrations was dependent on the cell-cycle state. Using computational modeling, we demonstrated that indeed the combination of these two effects could explain the complex patterns of history dependence observed at the population level. Our insight into how the behavior of single cells scales up to processes at the population level provides a perspective on how organisms operate in dynamic environments with fluctuating stress exposure. PMID:26960998

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Genome-wide mapping of DNase I hypersensitive sites in rare cell populations using single-cell DNase sequencing.

PubMed

Cooper, James; Ding, Yi; Song, Jiuzhou; Zhao, Keji

2017-11-01

Increased chromatin accessibility is a feature of cell-type-specific cis-regulatory elements; therefore, mapping of DNase I hypersensitive sites (DHSs) enables the detection of active regulatory elements of transcription, including promoters, enhancers, insulators and locus-control regions. Single-cell DNase sequencing (scDNase-seq) is a method of detecting genome-wide DHSs when starting with either single cells or <1,000 cells from primary cell sources. This technique enables genome-wide mapping of hypersensitive sites in a wide range of cell populations that cannot be analyzed using conventional DNase I sequencing because of the requirement for millions of starting cells. Fresh cells, formaldehyde-cross-linked cells or cells recovered from formalin-fixed paraffin-embedded (FFPE) tissue slides are suitable for scDNase-seq assays. To generate scDNase-seq libraries, cells are lysed and then digested with DNase I. Circular carrier plasmid DNA is included during subsequent DNA purification and library preparation steps to prevent loss of the small quantity of DHS DNA. Libraries are generated for high-throughput sequencing on the Illumina platform using standard methods. Preparation of scDNase-seq libraries requires only 2 d. The materials and molecular biology techniques described in this protocol should be accessible to any general molecular biology laboratory. Processing of high-throughput sequencing data requires basic bioinformatics skills and uses publicly available bioinformatics software.

Study of radiation effects on mammalian cells in vitro

NASA Technical Reports Server (NTRS)

Sinclair, W. K.

1968-01-01

Radiation effect on single cells and cell populations of Chinese hamster lung tissue is studied in vitro. The rate and position as the cell progresses through the generation cycle shows division delay, changes in some biochemical processes in the cell, chromosomal changes, colony size changes, and loss of reproductive capacity.

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.

Identifying States along the Hematopoietic Stem Cell Differentiation Hierarchy with Single Cell Specificity via Raman Spectroscopy.

PubMed

Ilin, Yelena; Choi, Ji Sun; Harley, Brendan A C; Kraft, Mary L

2015-11-17

A major challenge for expanding specific types of hematopoietic cells ex vivo for the treatment of blood cell pathologies is identifying the combinations of cellular and matrix cues that direct hematopoietic stem cells (HSC) to self-renew or differentiate into cell populations ex vivo. Microscale screening platforms enable minimizing the number of rare HSCs required to screen the effects of numerous cues on HSC fate decisions. These platforms create a strong demand for label-free methods that accurately identify the fate decisions of individual hematopoietic cells at specific locations on the platform. We demonstrate the capacity to identify discrete cells along the HSC differentiation hierarchy via multivariate analysis of Raman spectra. Notably, cell state identification is accurate for individual cells and independent of the biophysical properties of the functionalized polyacrylamide gels upon which these cells are cultured. We report partial least-squares discriminant analysis (PLS-DA) models of single cell Raman spectra enable identifying four dissimilar hematopoietic cell populations across the HSC lineage specification. Successful discrimination was obtained for a population enriched for long-term repopulating HSCs (LT-HSCs) versus their more differentiated progeny, including closely related short-term repopulating HSCs (ST-HSCs) and fully differentiated lymphoid (B cells) and myeloid (granulocytes) cells. The lineage-specific differentiation states of cells from these four subpopulations were accurately identified independent of the stiffness of the underlying biomaterial substrate, indicating subtle spectral variations that discriminated these populations were not masked by features from the culture substrate. This approach enables identifying the lineage-specific differentiation stages of hematopoietic cells on biomaterial substrates of differing composition and may facilitate correlating hematopoietic cell fate decisions with the extrinsic cues that elicited them.

Transcriptome Analysis at the Single-Cell Level Using SMART Technology.

PubMed

Fish, Rachel N; Bostick, Magnolia; Lehman, Alisa; Farmer, Andrew

2016-10-10

RNA sequencing (RNA-seq) is a powerful method for analyzing cell state, with minimal bias, and has broad applications within the biological sciences. However, transcriptome analysis of seemingly homogenous cell populations may in fact overlook significant heterogeneity that can be uncovered at the single-cell level. The ultra-low amount of RNA contained in a single cell requires extraordinarily sensitive and reproducible transcriptome analysis methods. As next-generation sequencing (NGS) technologies mature, transcriptome profiling by RNA-seq is increasingly being used to decipher the molecular signature of individual cells. This unit describes an ultra-sensitive and reproducible protocol to generate cDNA and sequencing libraries directly from single cells or RNA inputs ranging from 10 pg to 10 ng. Important considerations for working with minute RNA inputs are given. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

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

PubMed Central

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

2016-01-01

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

Application of single-cell sequencing in human cancer.

PubMed

Rantalainen, Mattias

2017-11-02

Precision medicine is emerging as a cornerstone of future cancer care with the objective of providing targeted therapies based on the molecular phenotype of each individual patient. Traditional bulk-level molecular phenotyping of tumours leads to significant information loss, as the molecular profile represents an average phenotype over large numbers of cells, while cancer is a disease with inherent intra-tumour heterogeneity at the cellular level caused by several factors, including clonal evolution, tissue hierarchies, rare cells and dynamic cell states. Single-cell sequencing provides means to characterize heterogeneity in a large population of cells and opens up opportunity to determine key molecular properties that influence clinical outcomes, including prognosis and probability of treatment response. Single-cell sequencing methods are now reliable enough to be used in many research laboratories, and we are starting to see applications of these technologies for characterization of human primary cancer cells. In this review, we provide an overview of studies that have applied single-cell sequencing to characterize human cancers at the single-cell level, and we discuss some of the current challenges in the field. © The Author 2017. Published by Oxford University Press.

Report of the Microbial Development Working Group

NASA Technical Reports Server (NTRS)

Nelson, G.

1985-01-01

In formulating ideas on the relationship of gravity to the development, growth, and reproduction of microorganisms, a rather liberal definition of microorganisms is used which includes bacteria, yeasts, protists, filamentous fungi, and single cells in culture. A principal advantage of microorganisms as experimental subjects is the rigor with which they can be defined and controlled. As single cells, each cell may be regarded as identical to the others in the population. This property applies to the morphology, physiology, and genetic parameters of the cells. The growth and development of the population is subject to precise manipulation as the nutritional requirements are known and minimal media formulations have been developed. Growth and differentiation can be manipulated in a variety of ways, such as alteration of the culture temperature and food supply, or by use of mutants. Finally, the short generation times of microorganisms provide the opportunity to conduct multigenerational studies within practical time limits and, in a similar vein, cellular responses to various stimuli or stresses are conveniently monitored because of the rapid response times of single cells.

Single-cell measurement of red blood cell oxygen affinity.

PubMed

Di Caprio, Giuseppe; Stokes, Chris; Higgins, John M; Schonbrun, Ethan

2015-08-11

Oxygen is transported throughout the body by hemoglobin (Hb) in red blood cells (RBCs). Although the oxygen affinity of blood is well-understood and routinely assessed in patients by pulse oximetry, variability at the single-cell level has not been previously measured. In contrast, single-cell measurements of RBC volume and Hb concentration are taken millions of times per day by clinical hematology analyzers, and they are important factors in determining the health of the hematologic system. To better understand the variability and determinants of oxygen affinity on a cellular level, we have developed a system that quantifies the oxygen saturation, cell volume, and Hb concentration for individual RBCs in high throughput. We find that the variability in single-cell saturation peaks at an oxygen partial pressure of 2.9%, which corresponds to the maximum slope of the oxygen-Hb dissociation curve. In addition, single-cell oxygen affinity is positively correlated with Hb concentration but independent of osmolarity, which suggests variation in the Hb to 2,3-diphosphoglycerate (2-3 DPG) ratio on a cellular level. By quantifying the functional behavior of a cellular population, our system adds a dimension to blood cell analysis and other measurements of single-cell variability.

Single-cell measurement of red blood cell oxygen affinity

PubMed Central

Di Caprio, Giuseppe; Stokes, Chris; Higgins, John M.; Schonbrun, Ethan

2015-01-01

Oxygen is transported throughout the body by hemoglobin (Hb) in red blood cells (RBCs). Although the oxygen affinity of blood is well-understood and routinely assessed in patients by pulse oximetry, variability at the single-cell level has not been previously measured. In contrast, single-cell measurements of RBC volume and Hb concentration are taken millions of times per day by clinical hematology analyzers, and they are important factors in determining the health of the hematologic system. To better understand the variability and determinants of oxygen affinity on a cellular level, we have developed a system that quantifies the oxygen saturation, cell volume, and Hb concentration for individual RBCs in high throughput. We find that the variability in single-cell saturation peaks at an oxygen partial pressure of 2.9%, which corresponds to the maximum slope of the oxygen–Hb dissociation curve. In addition, single-cell oxygen affinity is positively correlated with Hb concentration but independent of osmolarity, which suggests variation in the Hb to 2,3-diphosphoglycerate (2–3 DPG) ratio on a cellular level. By quantifying the functional behavior of a cellular population, our system adds a dimension to blood cell analysis and other measurements of single-cell variability. PMID:26216973

Single-cell RNA-sequencing reveals a distinct population of proglucagon-expressing cells specific to the mouse upper small intestine.

PubMed

Glass, Leslie L; Calero-Nieto, Fernando J; Jawaid, Wajid; Larraufie, Pierre; Kay, Richard G; Göttgens, Berthold; Reimann, Frank; Gribble, Fiona M

2017-10-01

To identify sub-populations of intestinal preproglucagon-expressing (PPG) cells producing Glucagon-like Peptide-1, and their associated expression profiles of sensory receptors, thereby enabling the discovery of therapeutic strategies that target these cell populations for the treatment of diabetes and obesity. We performed single cell RNA sequencing of PPG-cells purified by flow cytometry from the upper small intestine of 3 GLU-Venus mice. Cells from 2 mice were sequenced at low depth, and from the third mouse at high depth. High quality sequencing data from 234 PPG-cells were used to identify clusters by tSNE analysis. qPCR was performed to compare the longitudinal and crypt/villus locations of cluster-specific genes. Immunofluorescence and mass spectrometry were used to confirm protein expression. PPG-cells formed 3 major clusters: a group with typical characteristics of classical L-cells, including high expression of Gcg and Pyy (comprising 51% of all PPG-cells); a cell type overlapping with Gip-expressing K-cells (14%); and a unique cluster expressing Tph1 and Pzp that was predominantly located in proximal small intestine villi and co-produced 5-HT (35%). Expression of G-protein coupled receptors differed between clusters, suggesting the cell types are differentially regulated and would be differentially targetable. Our findings support the emerging concept that many enteroendocrine cell populations are highly overlapping, with individual cells producing a range of peptides previously assigned to distinct cell types. Different receptor expression profiles across the clusters highlight potential drug targets to increase gut hormone secretion for the treatment of diabetes and obesity. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.

Single-cell Hi-C bridges microscopy and genome-wide sequencing approaches to study 3D chromatin organization.

PubMed

Ulianov, Sergey V; Tachibana-Konwalski, Kikue; Razin, Sergey V

2017-10-01

Recent years have witnessed an explosion of the single-cell biochemical toolbox including chromosome conformation capture (3C)-based methods that provide novel insights into chromatin spatial organization in individual cells. The observations made with these techniques revealed that topologically associating domains emerge from cell population averages and do not exist as static structures in individual cells. Stochastic nature of the genome folding is likely to be biologically relevant and may reflect the ability of chromatin fibers to adopt a number of alternative configurations, some of which could be transiently stabilized and serve regulatory purposes. Single-cell Hi-C approaches provide an opportunity to analyze chromatin folding in rare cell types such as stem cells, tumor progenitors, oocytes, and totipotent cells, contributing to a deeper understanding of basic mechanisms in development and disease. Here, we review key findings of single-cell Hi-C and discuss possible biological reasons and consequences of the inferred dynamic chromatin spatial organization. © 2017 WILEY Periodicals, Inc.

The finite state projection approach to analyze dynamics of heterogeneous populations

NASA Astrophysics Data System (ADS)

Johnson, Rob; Munsky, Brian

2017-06-01

Population modeling aims to capture and predict the dynamics of cell populations in constant or fluctuating environments. At the elementary level, population growth proceeds through sequential divisions of individual cells. Due to stochastic effects, populations of cells are inherently heterogeneous in phenotype, and some phenotypic variables have an effect on division or survival rates, as can be seen in partial drug resistance. Therefore, when modeling population dynamics where the control of growth and division is phenotype dependent, the corresponding model must take account of the underlying cellular heterogeneity. The finite state projection (FSP) approach has often been used to analyze the statistics of independent cells. Here, we extend the FSP analysis to explore the coupling of cell dynamics and biomolecule dynamics within a population. This extension allows a general framework with which to model the state occupations of a heterogeneous, isogenic population of dividing and expiring cells. The method is demonstrated with a simple model of cell-cycle progression, which we use to explore possible dynamics of drug resistance phenotypes in dividing cells. We use this method to show how stochastic single-cell behaviors affect population level efficacy of drug treatments, and we illustrate how slight modifications to treatment regimens may have dramatic effects on drug efficacy.

Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas

PubMed Central

Hou, Yu; Guo, Huahu; Cao, Chen; Li, Xianlong; Hu, Boqiang; Zhu, Ping; Wu, Xinglong; Wen, Lu; Tang, Fuchou; Huang, Yanyi; Peng, Jirun

2016-01-01

Single-cell genome, DNA methylome, and transcriptome sequencing methods have been separately developed. However, to accurately analyze the mechanism by which transcriptome, genome and DNA methylome regulate each other, these omic methods need to be performed in the same single cell. Here we demonstrate a single-cell triple omics sequencing technique, scTrio-seq, that can be used to simultaneously analyze the genomic copy-number variations (CNVs), DNA methylome, and transcriptome of an individual mammalian cell. We show that large-scale CNVs cause proportional changes in RNA expression of genes within the gained or lost genomic regions, whereas these CNVs generally do not affect DNA methylation in these regions. Furthermore, we applied scTrio-seq to 25 single cancer cells derived from a human hepatocellular carcinoma tissue sample. We identified two subpopulations within these cells based on CNVs, DNA methylome, or transcriptome of individual cells. Our work offers a new avenue of dissecting the complex contribution of genomic and epigenomic heterogeneities to the transcriptomic heterogeneity within a population of cells. PMID:26902283

Discrete innervation of murine taste buds by peripheral taste neurons.

PubMed

Zaidi, Faisal N; Whitehead, Mark C

2006-08-09

The peripheral taste system likely maintains a specific relationship between ganglion cells that signal a particular taste quality and taste bud cells responsive to that quality. We have explored a measure of the receptoneural relationship in the mouse. By injecting single fungiform taste buds with lipophilic retrograde neuroanatomical markers, the number of labeled geniculate ganglion cells innervating single buds on the tongue were identified. We found that three to five ganglion cells innervate a single bud. Injecting neighboring buds with different color markers showed that the buds are primarily innervated by separate populations of geniculate cells (i.e., multiply labeled ganglion cells are rare). In other words, each taste bud is innervated by a population of neurons that only connects with that bud. Palate bud injections revealed a similar, relatively exclusive receptoneural relationship. Injecting buds in different regions of the tongue did not reveal a topographic representation of buds in the geniculate ganglion, despite a stereotyped patterned arrangement of fungiform buds as rows and columns on the tongue. However, ganglion cells innervating the tongue and palate were differentially concentrated in lateral and rostral regions of the ganglion, respectively. The principal finding that small groups of ganglion cells send sensory fibers that converge selectively on a single bud is a new-found measure of specific matching between the two principal cellular elements of the mouse peripheral taste system. Repetition of the experiments in the hamster showed a more divergent innervation of buds in this species. The results indicate that whatever taste quality is signaled by a murine geniculate ganglion neuron, that signal reflects the activity of cells in a single taste bud.

Self-renewal of a purified Tie2+ hematopoietic stem cell population relies on mitochondrial clearance.

PubMed

Ito, Kyoko; Turcotte, Raphaël; Cui, Jinhua; Zimmerman, Samuel E; Pinho, Sandra; Mizoguchi, Toshihide; Arai, Fumio; Runnels, Judith M; Alt, Clemens; Teruya-Feldstein, Julie; Mar, Jessica C; Singh, Rajat; Suda, Toshio; Lin, Charles P; Frenette, Paul S; Ito, Keisuke

2016-12-02

A single hematopoietic stem cell (HSC) is capable of reconstituting hematopoiesis and maintaining homeostasis by balancing self-renewal and cell differentiation. The mechanisms of HSC division balance, however, are not yet defined. Here we demonstrate, by characterizing at the single-cell level a purified and minimally heterogeneous murine Tie2 + HSC population, that these top hierarchical HSCs preferentially undergo symmetric divisions. The induction of mitophagy, a quality control process in mitochondria, plays an essential role in self-renewing expansion of Tie2 + HSCs. Activation of the PPAR (peroxisome proliferator-activated receptor)-fatty acid oxidation pathway promotes expansion of Tie2 + HSCs through enhanced Parkin recruitment in mitochondria. These metabolic pathways are conserved in human TIE2 + HSCs. Our data thus identify mitophagy as a key mechanism of HSC expansion and suggest potential methods of cell-fate manipulation through metabolic pathways. Copyright © 2016, American Association for the Advancement of Science.

Self-renewal of a purified Tie2+ hematopoietic stem cell population relies on mitochondrial clearance

PubMed Central

Ito, Kyoko; Turcotte, Raphaël; Cui, Jinhua; Zimmerman, Samuel E.; Pinho, Sandra; Mizoguchi, Toshihide; Arai, Fumio; Runnels, Judith M.; Alt, Clemens; Teruya-Feldstein, Julie; Mar, Jessica C.; Singh, Rajat; Suda, Toshio; Lin, Charles P.; Frenette, Paul S.; Ito, Keisuke

2016-01-01

A single hematopoietic stem cell (HSC) is capable of reconstituting hematopoiesis and maintaining homeostasis by balancing self-renewal and cell differentiation. The mechanisms of HSC division balance, however, are not yet defined. Here we demonstrate, by characterizing at the single-cell level a purified and minimally heterogeneous murine Tie2+ HSC population, that these top hierarchical HSCs preferentially undergo symmetric divisions. The induction of mitophagy, a quality control process in mitochondria, plays an essential role in self-renewing expansion of Tie2+ HSCs. Activation of the PPAR (peroxisome proliferator–activated receptor)–fatty acid oxidation pathway promotes expansion of Tie2+ HSCs through enhanced Parkin recruitment in mitochondria. These metabolic pathways are conserved in human TIE2+ HSCs. Our data thus identify mitophagy as a key mechanism of HSC expansion and suggest potential methods of cell-fate manipulation through metabolic pathways. PMID:27738012

Analysis of individual cells identifies cell-to-cell variability following induction of cellular senescence.

PubMed

Wiley, Christopher D; Flynn, James M; Morrissey, Christapher; Lebofsky, Ronald; Shuga, Joe; Dong, Xiao; Unger, Marc A; Vijg, Jan; Melov, Simon; Campisi, Judith

2017-10-01

Senescent cells play important roles in both physiological and pathological processes, including cancer and aging. In all cases, however, senescent cells comprise only a small fraction of tissues. Senescent phenotypes have been studied largely in relatively homogeneous populations of cultured cells. In vivo, senescent cells are generally identified by a small number of markers, but whether and how these markers vary among individual cells is unknown. We therefore utilized a combination of single-cell isolation and a nanofluidic PCR platform to determine the contributions of individual cells to the overall gene expression profile of senescent human fibroblast populations. Individual senescent cells were surprisingly heterogeneous in their gene expression signatures. This cell-to-cell variability resulted in a loss of correlation among the expression of several senescence-associated genes. Many genes encoding senescence-associated secretory phenotype (SASP) factors, a major contributor to the effects of senescent cells in vivo, showed marked variability with a subset of highly induced genes accounting for the increases observed at the population level. Inflammatory genes in clustered genomic loci showed a greater correlation with senescence compared to nonclustered loci, suggesting that these genes are coregulated by genomic location. Together, these data offer new insights into how genes are regulated in senescent cells and suggest that single markers are inadequate to identify senescent cells in vivo. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons 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.

Tumor Heterogeneity, Single-Cell Sequencing, and Drug Resistance.

PubMed

Schmidt, Felix; Efferth, Thomas

2016-06-16

Tumor heterogeneity has been compared with Darwinian evolution and survival of the fittest. The evolutionary ecosystem of tumors consisting of heterogeneous tumor cell populations represents a considerable challenge to tumor therapy, since all genetically and phenotypically different subpopulations have to be efficiently killed by therapy. Otherwise, even small surviving subpopulations may cause repopulation and refractory tumors. Single-cell sequencing allows for a better understanding of the genomic principles of tumor heterogeneity and represents the basis for more successful tumor treatments. The isolation and sequencing of single tumor cells still represents a considerable technical challenge and consists of three major steps: (1) single cell isolation (e.g., by laser-capture microdissection), fluorescence-activated cell sorting, micromanipulation, whole genome amplification (e.g., with the help of Phi29 DNA polymerase), and transcriptome-wide next generation sequencing technologies (e.g., 454 pyrosequencing, Illumina sequencing, and other systems). Data demonstrating the feasibility of single-cell sequencing for monitoring the emergence of drug-resistant cell clones in patient samples are discussed herein. It is envisioned that single-cell sequencing will be a valuable asset to assist the design of regimens for personalized tumor therapies based on tumor subpopulation-specific genetic alterations in individual patients.

Transcriptional Networks in Single Perivascular Cells Sorted from Human Adipose Tissue Reveal a Hierarchy of Mesenchymal Stem Cells.

PubMed

Hardy, W Reef; Moldovan, Nicanor I; Moldovan, Leni; Livak, Kenneth J; Datta, Krishna; Goswami, Chirayu; Corselli, Mirko; Traktuev, Dmitry O; Murray, Iain R; Péault, Bruno; March, Keith

2017-05-01

Adipose tissue is a rich source of multipotent mesenchymal stem-like cells, located in the perivascular niche. Based on their surface markers, these have been assigned to two main categories: CD31 - /CD45 - /CD34 + /CD146 - cells (adventitial stromal/stem cells [ASCs]) and CD31 - /CD45 - /CD34 - /CD146 + cells (pericytes [PCs]). These populations display heterogeneity of unknown significance. We hypothesized that aldehyde dehydrogenase (ALDH) activity, a functional marker of primitivity, could help to better define ASC and PC subclasses. To this end, the stromal vascular fraction from a human lipoaspirate was simultaneously stained with fluorescent antibodies to CD31, CD45, CD34, and CD146 antigens and the ALDH substrate Aldefluor, then sorted by fluorescence-activated cell sorting. Individual ASCs (n = 67) and PCs (n = 73) selected from the extremities of the ALDH-staining spectrum were transcriptionally profiled by Fluidigm single-cell quantitative polymerase chain reaction for a predefined set (n = 429) of marker genes. To these single-cell data, we applied differential expression and principal component and clustering analysis, as well as an original gene coexpression network reconstruction algorithm. Despite the stochasticity at the single-cell level, covariation of gene expression analysis yielded multiple network connectivity parameters suggesting that these perivascular progenitor cell subclasses possess the following order of maturity: (a) ALDH br ASC (most primitive); (b) ALDH dim ASC; (c) ALDH br PC; (d) ALDH dim PC (least primitive). This order was independently supported by specific combinations of class-specific expressed genes and further confirmed by the analysis of associated signaling pathways. In conclusion, single-cell transcriptional analysis of four populations isolated from fat by surface markers and enzyme activity suggests a developmental hierarchy among perivascular mesenchymal stem cells supported by markers and coexpression networks. Stem Cells 2017;35:1273-1289. © 2017 AlphaMed Press.

Whole Genome Amplification of Labeled Viable Single Cells Suited for Array-Comparative Genomic Hybridization.

PubMed

Kroneis, Thomas; El-Heliebi, Amin

2015-01-01

Understanding details of a complex biological system makes it necessary to dismantle it down to its components. Immunostaining techniques allow identification of several distinct cell types thereby giving an inside view of intercellular heterogeneity. Often staining reveals that the most remarkable cells are the rarest. To further characterize the target cells on a molecular level, single cell techniques are necessary. Here, we describe the immunostaining, micromanipulation, and whole genome amplification of single cells for the purpose of genomic characterization. First, we exemplify the preparation of cell suspensions from cultured cells as well as the isolation of peripheral mononucleated cells from blood. The target cell population is then subjected to immunostaining. After cytocentrifugation target cells are isolated by micromanipulation and forwarded to whole genome amplification. For whole genome amplification, we use GenomePlex(®) technology allowing downstream genomic analysis such as array-comparative genomic hybridization.

Winnowing DNA for rare sequences: highly specific sequence and methylation based enrichment.

PubMed

Thompson, Jason D; Shibahara, Gosuke; Rajan, Sweta; Pel, Joel; Marziali, Andre

2012-01-01

Rare mutations in cell populations are known to be hallmarks of many diseases and cancers. Similarly, differential DNA methylation patterns arise in rare cell populations with diagnostic potential such as fetal cells circulating in maternal blood. Unfortunately, the frequency of alleles with diagnostic potential, relative to wild-type background sequence, is often well below the frequency of errors in currently available methods for sequence analysis, including very high throughput DNA sequencing. We demonstrate a DNA preparation and purification method that through non-linear electrophoretic separation in media containing oligonucleotide probes, achieves 10,000 fold enrichment of target DNA with single nucleotide specificity, and 100 fold enrichment of unmodified methylated DNA differing from the background by the methylation of a single cytosine residue.

FACS-based Isolation of Neural and Glioma Stem Cell Populations from Fresh Human Tissues Utilizing EGF Ligand

PubMed Central

Tome-Garcia, Jessica; Doetsch, Fiona; Tsankova, Nadejda M.

2018-01-01

Direct isolation of human neural and glioma stem cells from fresh tissues permits their biological study without prior culture and may capture novel aspects of their molecular phenotype in their native state. Recently, we demonstrated the ability to prospectively isolate stem cell populations from fresh human germinal matrix and glioblastoma samples, exploiting the ability of cells to bind the Epidermal Growth Factor (EGF) ligand in fluorescence-activated cell sorting (FACS). We demonstrated that FACS-isolated EGF-bound neural and glioblastoma populations encompass the sphere-forming colonies in vitro, and are capable of both self-renewal and multilineage differentiation. Here we describe in detail the purification methodology of EGF-bound (i.e., EGFR+) human neural and glioma cells with stem cell properties from fresh postmortem and surgical tissues. The ability to prospectively isolate stem cell populations using native ligand-binding ability opens new doors for understanding both normal and tumor cell biology in uncultured conditions, and is applicable for various downstream molecular sequencing studies at both population and single-cell resolution. PMID:29516026

Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip.

PubMed

Heo, Young Jin; Lee, Donghyeon; Kang, Junsu; Lee, Keondo; Chung, Wan Kyun

2017-09-14

Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.

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

PubMed

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

2018-02-01

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

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

Ergodicity, hidden bias and the growth rate gain

NASA Astrophysics Data System (ADS)

Rochman, Nash D.; Popescu, Dan M.; Sun, Sean X.

2018-05-01

Many single-cell observables are highly heterogeneous. A part of this heterogeneity stems from age-related phenomena: the fact that there is a nonuniform distribution of cells with different ages. This has led to a renewed interest in analytic methodologies including use of the ‘von Foerster equation’ for predicting population growth and cell age distributions. Here we discuss how some of the most popular implementations of this machinery assume a strong condition on the ergodicity of the cell cycle duration ensemble. We show that one common definition for the term ergodicity, ‘a single individual observed over many generations recapitulates the behavior of the entire ensemble’ is implied by the other, ‘the probability of observing any state is conserved across time and over all individuals’ in an ensemble with a fixed number of individuals but that this is not true when the ensemble is growing. We further explore the impact of generational correlations between cell cycle durations on the population growth rate. Finally, we explore the ‘growth rate gain’—the phenomenon that variations in the cell cycle duration leads to an improved population-level growth rate—in this context. We highlight that, fundamentally, this effect is due to asymmetric division.

Mechanisms of fate decision and lineage commitment during haematopoiesis.

PubMed

Cvejic, Ana

2016-03-01

Blood stem cells need to both perpetuate themselves (self-renew) and differentiate into all mature blood cells to maintain blood formation throughout life. However, it is unclear how the underlying gene regulatory network maintains this population of self-renewing and differentiating stem cells and how it accommodates the transition from a stem cell to a mature blood cell. Our current knowledge of transcriptomes of various blood cell types has mainly been advanced by population-level analysis. However, a population of seemingly homogenous blood cells may include many distinct cell types with substantially different transcriptomes and abilities to make diverse fate decisions. Therefore, understanding the cell-intrinsic differences between individual cells is necessary for a deeper understanding of the molecular basis of their behaviour. Here we review recent single-cell studies in the haematopoietic system and their contribution to our understanding of the mechanisms governing cell fate choices and lineage commitment.

A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data

PubMed Central

Barron, Martin; Zhang, Siyuan

2018-01-01

Abstract Cell types in cell populations change as the condition changes: some cell types die out, new cell types may emerge and surviving cell types evolve to adapt to the new condition. Using single-cell RNA-sequencing data that measure the gene expression of cells before and after the condition change, we propose an algorithm, SparseDC, which identifies cell types, traces their changes across conditions and identifies genes which are marker genes for these changes. By solving a unified optimization problem, SparseDC completes all three tasks simultaneously. SparseDC is highly computationally efficient and demonstrates its accuracy on both simulated and real data. PMID:29140455

Large scale spontaneous synchronization of cell cycles in amoebae

NASA Astrophysics Data System (ADS)

Segota, Igor; Boulet, Laurent; Franck, Carl

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

A Single-Cell View of the BtsSR/YpdAB Pyruvate Sensing Network in Escherichia coli and Its Biological Relevance.

PubMed

Vilhena, Cláudia; Kaganovitch, Eugen; Shin, Jae Yen; Grünberger, Alexander; Behr, Stefan; Kristoficova, Ivica; Brameyer, Sophie; Kohlheyer, Dietrich; Jung, Kirsten

2018-01-01

Fluctuating environments and individual physiological diversity force bacteria to constantly adapt and optimize the uptake of substrates. We focus here on two very similar two-component systems (TCSs) of Escherichia coli belonging to the LytS/LytTR family: BtsS/BtsR (formerly YehU/YehT) and YpdA/YpdB. Both TCSs respond to extracellular pyruvate, albeit with different affinities, typically during postexponential growth, and each system regulates expression of a single transporter gene, yjiY and yhjX , respectively. To obtain insights into the biological significance of these TCSs, we analyzed the activation of the target promoters at the single-cell level. We found unimodal cell-to-cell variability; however, the degree of variance was strongly influenced by the available nutrients and differed between the two TCSs. We hypothesized that activation of either of the TCSs helps individual cells to replenish carbon resources. To test this hypothesis, we compared wild-type cells with the btsSR ypdAB mutant under two metabolically modulated conditions: protein overproduction and persister formation. Although all wild-type cells were able to overproduce green fluorescent protein (GFP), about half of the btsSR ypdAB population was unable to overexpress GFP. Moreover, the percentage of persister cells, which tolerate antibiotic stress, was significantly lower in the wild-type cells than in the btsSR ypdAB population. Hence, we suggest that the BtsS/BtsR and YpdA/YpdB network contributes to a balancing of the physiological state of all cells within a population. IMPORTANCE Histidine kinase/response regulator (HK/RR) systems enable bacteria to respond to environmental and physiological fluctuations. Escherichia coli and other members of the Enterobacteriaceae possess two similar LytS/LytTR-type HK/RRs, BtsS/BtsR (formerly YehU/YehT) and YpdA/YpdB, which form a functional network. Both systems are activated in response to external pyruvate, typically when cells face overflow metabolism during post-exponential growth. Single-cell analysis of the activation of their respective target genes yjiY and yhjX revealed cell-to-cell variability, and the range of variation was strongly influenced by externally available nutrients. Based on the phenotypic characterization of a btsSR ypdAB mutant compared to the parental strain, we suggest that this TCS network supports an optimization of the physiological state of the individuals within the population. Copyright © 2017 American Society for Microbiology.

Gene expression profiling of single cells on large-scale oligonucleotide arrays

PubMed Central

Hartmann, Claudia H.; Klein, Christoph A.

2006-01-01

Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells. PMID:17071717

Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell.

PubMed

Nagano, Takashi; Lubling, Yaniv; Yaffe, Eitan; Wingett, Steven W; Dean, Wendy; Tanay, Amos; Fraser, Peter

2015-12-01

Hi-C is a powerful method that provides pairwise information on genomic regions in spatial proximity in the nucleus. Hi-C requires millions of cells as input and, as genome organization varies from cell to cell, a limitation of Hi-C is that it only provides a population average of genome conformations. We developed single-cell Hi-C to create snapshots of thousands of chromatin interactions that occur simultaneously in a single cell. To adapt Hi-C to single-cell analysis, we modified the protocol to include in-nucleus ligation. This enables the isolation of single nuclei carrying Hi-C-ligated DNA into separate tubes, followed by reversal of cross-links, capture of biotinylated ligation junctions on streptavidin-coated magnetic beads and PCR amplification of single-cell Hi-C libraries. The entire laboratory protocol can be carried out in 1 week, and although we have demonstrated its use in mouse T helper (TH1) cells, it should be applicable to any cell type or species for which standard Hi-C has been successful. We also developed an analysis pipeline to filter noise and assess the quality of data sets in a few hours. Although the interactome maps produced by single-cell Hi-C are sparse, the data provide useful information to understand cellular variability in nuclear genome organization and chromosome structure. Standard wet and dry laboratory skills in molecular biology and computational analysis are required.

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

Microfluidic single-cell whole-transcriptome sequencing.

PubMed

Streets, Aaron M; Zhang, Xiannian; Cao, Chen; Pang, Yuhong; Wu, Xinglong; Xiong, Liang; Yang, Lu; Fu, Yusi; Zhao, Liang; Tang, Fuchou; Huang, Yanyi

2014-05-13

Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole-transcriptome analysis. In this approach, single cells are captured and lysed in a microfluidic device, where mRNAs with poly(A) tails are reverse-transcribed into cDNA. Double-stranded cDNA is then collected and sequenced using a next generation sequencing platform. We prepared 94 libraries consisting of single mouse embryonic cells and technical replicates of extracted RNA and thoroughly characterized the performance of this technology. Microfluidic implementation increased mRNA detection sensitivity as well as improved measurement precision compared with tube-based protocols. With 0.2 M reads per cell, we were able to reconstruct a majority of the bulk transcriptome with 10 single cells. We also quantified variation between and within different types of mouse embryonic cells and found that enhanced measurement precision, detection sensitivity, and experimental throughput aided the distinction between biological variability and technical noise. With this work, we validated the advantages of an early approach to single-cell RNA-Seq and showed that the benefits of combining microfluidic technology with high-throughput sequencing will be valuable for large-scale efforts in single-cell transcriptome analysis.

Rapid learning in visual cortical networks.

PubMed

Wang, Ye; Dragoi, Valentin

2015-08-26

Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

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.

PCNA appears in two populations of slow and fast diffusion with a constant ratio throughout S-phase in replicating mammalian cells.

PubMed

Zessin, Patrick J M; Sporbert, Anje; Heilemann, Mike

2016-01-13

DNA replication is a fundamental cellular process that precedes cell division. Proliferating cell nuclear antigen (PCNA) is a central scaffold protein that orchestrates DNA replication by recruiting many factors essential for the replication machinery. We studied the mobility of PCNA in live mammalian cells using single-particle tracking in combination with photoactivated-localization microscopy (sptPALM) and found two populations. The first population which is only present in cells with active DNA replication, showed slow diffusion and was found to be located in replication foci. The second population showed fast diffusion, and represents the nucleoplasmic pool of unbound PCNA not involved in DNA replication. The ratio of these two populations remained constant throughout different stages of S-phase. A fraction of molecules in both populations showed spatially constrained mobility. We determined an exploration radius of ~100 nm for 13% of the slow-diffusing PCNA molecules, and of ~600 nm for 46% of the fast-diffusing PCNA molecules.

A statistical framework for multiparameter analysis at the single-cell level.

PubMed

Torres-García, Wandaliz; Ashili, Shashanka; Kelbauskas, Laimonas; Johnson, Roger H; Zhang, Weiwen; Runger, George C; Meldrum, Deirdre R

2012-03-01

Phenotypic characterization of individual cells provides crucial insights into intercellular heterogeneity and enables access to information that is unavailable from ensemble averaged, bulk cell analyses. Single-cell studies have attracted significant interest in recent years and spurred the development of a variety of commercially available and research-grade technologies. To quantify cell-to-cell variability of cell populations, we have developed an experimental platform for real-time measurements of oxygen consumption (OC) kinetics at the single-cell level. Unique challenges inherent to these single-cell measurements arise, and no existing data analysis methodology is available to address them. Here we present a data processing and analysis method that addresses challenges encountered with this unique type of data in order to extract biologically relevant information. We applied the method to analyze OC profiles obtained with single cells of two different cell lines derived from metaplastic and dysplastic human Barrett's esophageal epithelium. In terms of method development, three main challenges were considered for this heterogeneous dynamic system: (i) high levels of noise, (ii) the lack of a priori knowledge of single-cell dynamics, and (iii) the role of intercellular variability within and across cell types. Several strategies and solutions to address each of these three challenges are presented. The features such as slopes, intercepts, breakpoint or change-point were extracted for every OC profile and compared across individual cells and cell types. The results demonstrated that the extracted features facilitated exposition of subtle differences between individual cells and their responses to cell-cell interactions. With minor modifications, this method can be used to process and analyze data from other acquisition and experimental modalities at the single-cell level, providing a valuable statistical framework for single-cell analysis.

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

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

PubMed

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

2018-04-19

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

The effects of nongenetic memory on population level sensitivity to stress

NASA Astrophysics Data System (ADS)

Adams, Rhys; Nevozhay, Dmitry; van Itallie, Elizabeth; Bennett, Matthew; Balazsi, Gabor

2011-03-01

While gene expression is often thought of as a unidirectional determinant of cellular fitness, recent studies have shown how growth retardation due to protein expression can affect gene expression levels in single cells. We developed two yeast strains carrying a drug resistance protein under the control of different synthetic gene constructs, one of which was monostable, while the other was bistable. The gene expression of these cell populations was tuned using a molecular inducer so that their respective means and noises were identical, while their nongenetic memory properties were different. We tested the sensitivity of these two cell population distributions to the antibiotic zeocin. We found that the gene expression distributions of bistable cell populations were sensitive to stressful environments, while the gene expression distribution of monostable cells were nearly unchanged by stress. We conclude that cell populations with high nongenetic memory are more adaptable to their environment. This work was funded by the National Institutes of Health through the NIH Director's New Innovator Award Program, 1-DP2- OD006481-01.

Tracking single mRNA molecules in live cells

NASA Astrophysics Data System (ADS)

Moon, Hyungseok C.; Lee, Byung Hun; Lim, Kiseong; Son, Jae Seok; Song, Minho S.; Park, Hye Yoon

2016-06-01

mRNAs inside cells interact with numerous RNA-binding proteins, microRNAs, and ribosomes that together compose a highly heterogeneous population of messenger ribonucleoprotein (mRNP) particles. Perhaps one of the best ways to investigate the complex regulation of mRNA is to observe individual molecules. Single molecule imaging allows the collection of quantitative and statistical data on subpopulations and transient states that are otherwise obscured by ensemble averaging. In addition, single particle tracking reveals the sequence of events that occur in the formation and remodeling of mRNPs in real time. Here, we review the current state-of-the-art techniques in tagging, delivery, and imaging to track single mRNAs in live cells. We also discuss how these techniques are applied to extract dynamic information on the transcription, transport, localization, and translation of mRNAs. These studies demonstrate how single molecule tracking is transforming the understanding of mRNA regulation in live cells.

In Vivo Single-Cell Fluorescence and Size Scaling of Phytoplankton Chlorophyll Content.

PubMed

Álvarez, Eva; Nogueira, Enrique; López-Urrutia, Ángel

2017-04-01

In unicellular phytoplankton, the size scaling exponent of chlorophyll content per cell decreases with increasing light limitation. Empirical studies have explored this allometry by combining data from several species, using average values of pigment content and cell size for each species. The resulting allometry thus includes phylogenetic and size scaling effects. The possibility of measuring single-cell fluorescence with imaging-in-flow cytometry devices allows the study of the size scaling of chlorophyll content at both the inter- and intraspecific levels. In this work, the changing allometry of chlorophyll content was estimated for the first time for single phytoplankton populations by using data from a series of incubations with monocultures exposed to different light levels. Interspecifically, our experiments confirm previous modeling and experimental results of increasing size scaling exponents with increasing irradiance. A similar pattern was observed intraspecifically but with a larger variability in size scaling exponents. Our results show that size-based processes and geometrical approaches explain variations in chlorophyll content. We also show that the single-cell fluorescence measurements provided by imaging-in-flow devices can be applied to field samples to understand the changes in the size dependence of chlorophyll content in response to environmental variables affecting primary production. IMPORTANCE The chlorophyll concentrations in phytoplankton register physiological adjustments in cellular pigmentation arising mainly from changes in light conditions. The extent of these adjustments is constrained by the size of the phytoplankton cells, even within single populations. Hence, variations in community chlorophyll derived from photoacclimation are also dependent on the phytoplankton size distribution. Copyright © 2017 American Society for Microbiology.

In Vivo Single-Cell Fluorescence and Size Scaling of Phytoplankton Chlorophyll Content

PubMed Central

Nogueira, Enrique; López-Urrutia, Ángel

2017-01-01

ABSTRACT In unicellular phytoplankton, the size scaling exponent of chlorophyll content per cell decreases with increasing light limitation. Empirical studies have explored this allometry by combining data from several species, using average values of pigment content and cell size for each species. The resulting allometry thus includes phylogenetic and size scaling effects. The possibility of measuring single-cell fluorescence with imaging-in-flow cytometry devices allows the study of the size scaling of chlorophyll content at both the inter- and intraspecific levels. In this work, the changing allometry of chlorophyll content was estimated for the first time for single phytoplankton populations by using data from a series of incubations with monocultures exposed to different light levels. Interspecifically, our experiments confirm previous modeling and experimental results of increasing size scaling exponents with increasing irradiance. A similar pattern was observed intraspecifically but with a larger variability in size scaling exponents. Our results show that size-based processes and geometrical approaches explain variations in chlorophyll content. We also show that the single-cell fluorescence measurements provided by imaging-in-flow devices can be applied to field samples to understand the changes in the size dependence of chlorophyll content in response to environmental variables affecting primary production. IMPORTANCE The chlorophyll concentrations in phytoplankton register physiological adjustments in cellular pigmentation arising mainly from changes in light conditions. The extent of these adjustments is constrained by the size of the phytoplankton cells, even within single populations. Hence, variations in community chlorophyll derived from photoacclimation are also dependent on the phytoplankton size distribution. PMID:28115378

Quantification of rat retinal growth and vascular population changes after single and split doses of proton irradiation: translational study using stereology methods

NASA Technical Reports Server (NTRS)

Mao, Xiao W.; Archambeau, John O.; Kubinova, Lucie; Boyle, Soames; Petersen, Georgia; Grove, Roger; Nelson, G. A. (Principal Investigator)

2003-01-01

This study quantified architectural and population changes in the rat retinal vasculature after proton irradiation using stereology. A 100 MeV conformal proton beam delivered 8, 14, 20 and 28 Gy as single and split doses to the whole eye. The vascular networks were prepared from retinal digests. Stereological methods were used to obtain the area of the retina and unbiased estimates of microvessel/artery/vein endothelial, pericyte and smooth muscle population, and vessel length. The retinal area increased progressively in the unirradiated, age-matched controls and in the retinas irradiated with 8 and 14 Gy, indicating uniform progressive retinal growth. No growth occurred after 20 and 28 Gy. Regression analysis of total endothelial cell number in all vessels (arteries, veins and capillaries) after irradiation documented a progressive time- and dose-dependent cell loss occurring over 15 to 24 months. The difference from controls was significant (P<0.01) after 28 Gy given in single and split doses and after 20 Gy given as a split dose (P<0.05). Total vessel length in microvessel was significantly shortened at 20 and 28 Gy compared to that of controls (P<0.05). No evident dose recovery was observed in the endothelial populations after split doses. At 10 Gy, the rate of endothelial cell loss, a dose parameter used to characterize the time- and dose-dependent loss of the endothelial population, was doubled.

PyClone: statistical inference of clonal population structure in cancer.

PubMed

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

2014-04-01

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

Each cell counts: Hematopoiesis and immunity research in the era of single cell genomics.

PubMed

Jaitin, Diego Adhemar; Keren-Shaul, Hadas; Elefant, Naama; Amit, Ido

2015-02-01

Hematopoiesis and immunity are mediated through complex interactions between multiple cell types and states. This complexity is currently addressed following a reductionist approach of characterizing cell types by a small number of cell surface molecular features and gross functions. While the introduction of global transcriptional profiling technologies enabled a more comprehensive view, heterogeneity within sampled populations remained unaddressed, obscuring the true picture of hematopoiesis and immune system function. A critical mass of technological advances in molecular biology and genomics has enabled genome-wide measurements of single cells - the fundamental unit of immunity. These new advances are expected to boost detection of less frequent cell types and fuzzy intermediate cell states, greatly expanding the resolution of current available classifications. This new era of single-cell genomics in immunology research holds great promise for further understanding of the mechanisms and circuits regulating hematopoiesis and immunity in both health and disease. In the near future, the accuracy of single-cell genomics will ultimately enable precise diagnostics and treatment of multiple hematopoietic and immune related diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Winnowing DNA for Rare Sequences: Highly Specific Sequence and Methylation Based Enrichment

PubMed Central

Thompson, Jason D.; Shibahara, Gosuke; Rajan, Sweta; Pel, Joel; Marziali, Andre

2012-01-01

Rare mutations in cell populations are known to be hallmarks of many diseases and cancers. Similarly, differential DNA methylation patterns arise in rare cell populations with diagnostic potential such as fetal cells circulating in maternal blood. Unfortunately, the frequency of alleles with diagnostic potential, relative to wild-type background sequence, is often well below the frequency of errors in currently available methods for sequence analysis, including very high throughput DNA sequencing. We demonstrate a DNA preparation and purification method that through non-linear electrophoretic separation in media containing oligonucleotide probes, achieves 10,000 fold enrichment of target DNA with single nucleotide specificity, and 100 fold enrichment of unmodified methylated DNA differing from the background by the methylation of a single cytosine residue. PMID:22355378

Single Cell Mass Cytometry for Analysis of Immune System Functional States

PubMed Central

Bjornson, Zach B.; Nolan, Garry P.; Fantl, Wendy J.

2013-01-01

Single cell mass cytometry facilitates high-dimensional, quantitative analysis of the effects of bioactive molecules on cell populations at single-cell resolution. Datasets are generated with antibody panels (upwards of 40) in which each antibody is conjugated to a polymer chelated with a stable metal isotope, usually in the Lanthanide series of the periodic table. Isotope labelled antibodies recognize surface markers to delineate cell types and intracellular signaling molecules to provide a measure of the network state—and thereby demarcating multiple cell state functions such as apoptosis, DNA damage and cell cycle. By measuring all these parameters simultaneously, the signaling state of an individual cell can be measured at its network state. This review will cover the basics of mass cytometry as well as outline steps already taken to allow it to stand aside traditional fluorescence based cytometry in the immunologist’s analytical arsenal in their study of immune states during infection. PMID:23999316

Bacterial computing with engineered populations.

PubMed

Amos, Martyn; Axmann, Ilka Maria; Blüthgen, Nils; de la Cruz, Fernando; Jaramillo, Alfonso; Rodriguez-Paton, Alfonso; Simmel, Friedrich

2015-07-28

We describe strategies for the construction of bacterial computing platforms by describing a number of results from the recently completed bacterial computing with engineered populations project. In general, the implementation of such systems requires a framework containing various components such as intracellular circuits, single cell input/output and cell-cell interfacing, as well as extensive analysis. In this overview paper, we describe our approach to each of these, and suggest possible areas for future research. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Magnetic levitation of single cells

PubMed Central

Durmus, Naside Gozde; Tekin, H. Cumhur; Guven, Sinan; Sridhar, Kaushik; Arslan Yildiz, Ahu; Calibasi, Gizem; Davis, Ronald W.; Steinmetz, Lars M.; Demirci, Utkan

2015-01-01

Several cellular events cause permanent or transient changes in inherent magnetic and density properties of cells. Characterizing these changes in cell populations is crucial to understand cellular heterogeneity in cancer, immune response, infectious diseases, drug resistance, and evolution. Although magnetic levitation has previously been used for macroscale objects, its use in life sciences has been hindered by the inability to levitate microscale objects and by the toxicity of metal salts previously applied for levitation. Here, we use magnetic levitation principles for biological characterization and monitoring of cells and cellular events. We demonstrate that each cell type (i.e., cancer, blood, bacteria, and yeast) has a characteristic levitation profile, which we distinguish at an unprecedented resolution of 1 × 10−4 g⋅mL−1. We have identified unique differences in levitation and density blueprints between breast, esophageal, colorectal, and nonsmall cell lung cancer cell lines, as well as heterogeneity within these seemingly homogenous cell populations. Furthermore, we demonstrate that changes in cellular density and levitation profiles can be monitored in real time at single-cell resolution, allowing quantification of heterogeneous temporal responses of each cell to environmental stressors. These data establish density as a powerful biomarker for investigating living systems and their responses. Thereby, our method enables rapid, density-based imaging and profiling of single cells with intriguing applications, such as label-free identification and monitoring of heterogeneous biological changes under various physiological conditions, including antibiotic or cancer treatment in personalized medicine. PMID:26124131

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

PubMed

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

2008-08-15

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

Subpopulation-proteomics in prokaryotic populations.

PubMed

Jahn, Michael; Seifert, Jana; von Bergen, Martin; Schmid, Andreas; Bühler, Bruno; Müller, Susann

2013-02-01

Clonal microbial cells do not behave in an identical manner and form subpopulations during cultivation. Besides varying micro-environmental conditions, cell inherent features like cell cycle dependent localization and concentration of regulatory proteins as well as epigenetic properties are well accepted mechanisms creating cell heterogeneity. Another suspected reason is molecular noise on the transcriptional and translational level. A promising tool to unravel reasons for cell heterogeneity is the combination of cell sorting and subpopulation proteomics. This review summarizes recent developments in prokaryotic single-cell analytics and provides a workflow for selection of single cells, low cell number mass spectrometry, and proteomics evaluation. This approach is useful for understanding the dependency of individual cell decisions on inherent protein profiles. Copyright © 2012 Elsevier Ltd. All rights reserved.

Single-cell forensic short tandem repeat typing within microfluidic droplets.

PubMed

Geng, Tao; Novak, Richard; Mathies, Richard A

2014-01-07

A short tandem repeat (STR) typing method is developed for forensic identification of individual cells. In our strategy, monodisperse 1.5 nL agarose-in-oil droplets are produced with a high frequency using a microfluidic droplet generator. Statistically dilute single cells, along with primer-functionalized microbeads, are randomly compartmentalized in the droplets. Massively parallel single-cell droplet polymerase chain reaction (PCR) is performed to transfer replicas of desired STR targets from the single-cell genomic DNA onto the coencapsulated microbeads. These DNA-conjugated beads are subsequently harvested and reamplified under statistically dilute conditions for conventional capillary electrophoresis (CE) STR fragment size analysis. The 9-plex STR profiles of single cells from both pure and mixed populations of GM09947 and GM09948 human lymphoid cells show that all alleles are correctly called and allelic drop-in/drop-out is not observed. The cell mixture study exhibits a good linear relationship between the observed and input cell ratios in the range of 1:1 to 10:1. Additionally, the STR profile of GM09947 cells could be deduced even in the presence of a high concentration of cell-free contaminating 9948 genomic DNA. Our method will be valuable for the STR analysis of samples containing mixtures of cells/DNA from multiple contributors and for low-concentration samples.

Lineage Tracking for Probing Heritable Phenotypes at Single-Cell Resolution

PubMed Central

Cottinet, Denis; Condamine, Florence; Bremond, Nicolas; Griffiths, Andrew D.; Rainey, Paul B.; de Visser, J. Arjan G. M.; Baudry, Jean; Bibette, Jérôme

2016-01-01

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes–via growth–over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology. PMID:27077662

Lineage Tracking for Probing Heritable Phenotypes at Single-Cell Resolution.

PubMed

Cottinet, Denis; Condamine, Florence; Bremond, Nicolas; Griffiths, Andrew D; Rainey, Paul B; de Visser, J Arjan G M; Baudry, Jean; Bibette, Jérôme

2016-01-01

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes-via growth-over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology.

Testicular histology and germ cell cytology during spermatogenesis in the Mississippi map turtle, Graptemys pseudogeographica kohnii, from Northeast Arkansas.

PubMed

Lancaster, Kelsey; Trauth, Stanley E; Gribbins, Kevin M

2014-01-01

The testicular histology and cytology of spermatogenesis in Graptemys pseudogeographica kohnii were examined using specimens collected between July 1996 and May 2004 from counties in northeastern Arkansas. A histological examination of the testes and germ cell cytology indicates a postnuptial testicular cycle of spermatogenesis and a major fall spermiation event. The majority of the germ cell populations in May and June specimens are represented by resting spermatogonia, type A spermatogonia, type B spermatogonia, pre-leptotene spermatocytes, and numerous Sertoli cell nuclei near the basement membrane. The start of proliferation is evident as spermatogonia in metaphase are present near the basal lamina and many of these germ cells have entered meiosis in June seminiferous tubules. Major spermatogenic events occur in the June and July specimens and result in an increased height of the seminiferous epithelium and increased diameter of the seminiferous tubules. The germ cell population during this time is represented by spermatogonia (type A, B, and resting), hypertrophic cells, large populations of early primary spermatocytes, and early round spermatids. By September, the major germ cell population has progressed past meiosis with abundant round and early elongating spermatids dominating the seminiferous epithelium. October seminiferous epithelia are marked by a decreas in height and mature spermatozoa fill the luminal space. Round and elongating spermatids constitute the largest portion of the germ cell population. Following the spermiation event, the testes enter a period of quiescence that lasts till the next spermatogenic cycle, which begins in the subsequent spring. Based on the cytological development of the seminiferous tubules revealed by our study, Graptemys pseudogeographica kohnii demonstrates a temporal germ cell development strategy similar to other temperate reptiles. A single major generation of germ cells progresses through spermatogenesis each year resulting in a single spermiation event with sperm stored within the epididymis until the next spring mating season.

Testicular histology and germ cell cytology during spermatogenesis in the Mississippi map turtle, Graptemys pseudogeographica kohnii, from Northeast Arkansas

PubMed Central

Lancaster, Kelsey; Trauth, Stanley E; Gribbins, Kevin M

2014-01-01

The testicular histology and cytology of spermatogenesis in Graptemys pseudogeographica kohnii were examined using specimens collected between July 1996 and May 2004 from counties in northeastern Arkansas. A histological examination of the testes and germ cell cytology indicates a postnuptial testicular cycle of spermatogenesis and a major fall spermiation event. The majority of the germ cell populations in May and June specimens are represented by resting spermatogonia, type A spermatogonia, type B spermatogonia, pre-leptotene spermatocytes, and numerous Sertoli cell nuclei near the basement membrane. The start of proliferation is evident as spermatogonia in metaphase are present near the basal lamina and many of these germ cells have entered meiosis in June seminiferous tubules. Major spermatogenic events occur in the June and July specimens and result in an increased height of the seminiferous epithelium and increased diameter of the seminiferous tubules. The germ cell population during this time is represented by spermatogonia (type A, B, and resting), hypertrophic cells, large populations of early primary spermatocytes, and early round spermatids. By September, the major germ cell population has progressed past meiosis with abundant round and early elongating spermatids dominating the seminiferous epithelium. October seminiferous epithelia are marked by a decreas in height and mature spermatozoa fill the luminal space. Round and elongating spermatids constitute the largest portion of the germ cell population. Following the spermiation event, the testes enter a period of quiescence that lasts till the next spermatogenic cycle, which begins in the subsequent spring. Based on the cytological development of the seminiferous tubules revealed by our study, Graptemys pseudogeographica kohnii demonstrates a temporal germ cell development strategy similar to other temperate reptiles. A single major generation of germ cells progresses through spermatogenesis each year resulting in a single spermiation event with sperm stored within the epididymis until the next spring mating season. PMID:26413408

Single-Cell Western Blotting after Whole-Cell Imaging to Assess Cancer Chemotherapeutic Response

PubMed Central

2015-01-01

Intratumor heterogeneity remains a major obstacle to effective cancer therapy and personalized medicine. Current understanding points to differential therapeutic response among subpopulations of tumor cells as a key challenge to successful treatment. To advance our understanding of how this heterogeneity is reflected in cell-to-cell variations in chemosensitivity and expression of drug-resistance proteins, we optimize and apply a new targeted proteomics modality, single-cell western blotting (scWestern), to a human glioblastoma cell line. To acquire both phenotypic and proteomic data on the same, single glioblastoma cells, we integrate high-content imaging prior to the scWestern assays. The scWestern technique supports thousands of concurrent single-cell western blots, with each assay comprised of chemical lysis of single cells seated in microwells, protein electrophoresis from those microwells into a supporting polyacrylamide (PA) gel layer, and in-gel antibody probing. We systematically optimize chemical lysis and subsequent polyacrylamide gel electrophoresis (PAGE) of the single-cell lysate. The scWestern slides are stored for months then reprobed, thus allowing archiving and later analysis as relevant to sparingly limited, longitudinal cell specimens. Imaging and scWestern analysis of single glioblastoma cells dosed with the chemotherapeutic daunomycin showed both apoptotic (cleaved caspase 8- and annexin V-positive) and living cells. Intriguingly, living glioblastoma subpopulations show up-regulation of a multidrug resistant protein, P-glycoprotein (P-gp), suggesting an active drug efflux pump as a potential mechanism of drug resistance. Accordingly, linking of phenotype with targeted protein analysis with single-cell resolution may advance our understanding of drug response in inherently heterogeneous cell populations, such as those anticipated in tumors. PMID:25226230

Phenotypic heterogeneity in metabolic traits among single cells of a rare bacterial species in its natural environment quantified with a combination of flow cell sorting and NanoSIMS

PubMed Central

Zimmermann, Matthias; Escrig, Stéphane; Hübschmann, Thomas; Kirf, Mathias K.; Brand, Andreas; Inglis, R. Fredrik; Musat, Niculina; Müller, Susann; Meibom, Anders; Ackermann, Martin; Schreiber, Frank

2015-01-01

Populations of genetically identical microorganisms residing in the same environment can display marked variability in their phenotypic traits; this phenomenon is termed phenotypic heterogeneity. The relevance of such heterogeneity in natural habitats is unknown, because phenotypic characterization of a sufficient number of single cells of the same species in complex microbial communities is technically difficult. We report a procedure that allows to measure phenotypic heterogeneity in bacterial populations from natural environments, and use it to analyze N2 and CO2 fixation of single cells of the green sulfur bacterium Chlorobium phaeobacteroides from the meromictic lake Lago di Cadagno. We incubated lake water with 15N2 and 13CO2 under in situ conditions with and without NH4+. Subsequently, we used flow cell sorting with auto-fluorescence gating based on a pure culture isolate to concentrate C. phaeobacteroides from its natural abundance of 0.2% to now 26.5% of total bacteria. C. phaeobacteroides cells were identified using catalyzed-reporter deposition fluorescence in situ hybridization (CARD-FISH) targeting the 16S rRNA in the sorted population with a species-specific probe. In a last step, we used nanometer-scale secondary ion mass spectrometry to measure the incorporation 15N and 13C stable isotopes in more than 252 cells. We found that C. phaeobacteroides fixes N2 in the absence of NH4+, but not in the presence of NH4+ as has previously been suggested. N2 and CO2 fixation were heterogeneous among cells and positively correlated indicating that N2 and CO2 fixation activity interact and positively facilitate each other in individual cells. However, because CARD-FISH identification cannot detect genetic variability among cells of the same species, we cannot exclude genetic variability as a source for phenotypic heterogeneity in this natural population. Our study demonstrates the technical feasibility of measuring phenotypic heterogeneity in a rare bacterial species in its natural habitat, thus opening the door to study the occurrence and relevance of phenotypic heterogeneity in nature. PMID:25932020

Liquid scintillation counting for /sup 14/C uptake of single algal cells isolated from natural samples

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

Rivkin, R.B.; Seliger, H.H.

1981-07-01

Short term rates of /sup 14/C uptake for single cells and small numbers of isolated algal cells of five phytoplankton species from natural populations were measured by liquid scintillation counting. Regression analysis of uptake rates per cell for cells isolated from unialgal cultures of seven species of dinoflagellates, ranging in volume from ca. 10/sup 3/ to 10/sup 7/ ..mu..m/sup 3/, gave results identical to uptake rates per cell measured by conventional /sup 14/C techniques. Relative standard errors or regression coefficients ranged between 3 and 10%, indicating that for any species there was little variation in photosynthesis per cell.

Shape-Dependent Optoelectronic Cell Lysis**

PubMed Central

Kremer, Clemens; Witte, Christian; Neale, Steven L; Reboud, Julien; Barrett, Michael P; Cooper, Jonathan M

2014-01-01

We show an electrical method to break open living cells amongst a population of different cell types, where cell selection is based upon their shape. We implement the technique on an optoelectronic platform, where light, focused onto a semiconductor surface from a video projector creates a reconfigurable pattern of electrodes. One can choose the area of cells to be lysed in real-time, from single cells to large areas, simply by redrawing the projected pattern. We show that the method, based on the “electrical shadow” that the cell casts, allows the detection of rare cell types in blood (including sleeping sickness parasites), and has the potential to enable single cell studies for advanced molecular diagnostics, as well as wider applications in analytical chemistry. PMID:24402800

Taste Receptor Cells That Discriminate Between Bitter Stimuli

PubMed Central

Caicedo, Alejandro; Roper, Stephen D.

2013-01-01

Recent studies showing that single taste bud cells express multiple bitter taste receptors have reignited a long-standing controversy over whether single gustatory receptor cells respond selectively or broadly to tastants. We examined calcium responses of rat taste receptor cells in situ to a panel of bitter compounds to determine whether individual cells distinguish between bitter stimuli. Most bitter-responsive taste cells were activated by only one out of five compounds tested. In taste cells that responded to multiple stimuli, there were no significant associations between any two stimuli. Bitter sensation does not appear to occur through the activation of a homogeneous population of broadly tuned bitter-sensitive taste cells. Instead, different bitter stimuli may activate different subpopulations of bitter-sensitive taste cells. PMID:11222863

Comparison of reverse transcription-quantitative polymerase chain reaction methods and platforms for single cell gene expression analysis.

PubMed

Fox, Bridget C; Devonshire, Alison S; Baradez, Marc-Olivier; Marshall, Damian; Foy, Carole A

2012-08-15

Single cell gene expression analysis can provide insights into development and disease progression by profiling individual cellular responses as opposed to reporting the global average of a population. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the "gold standard" for the quantification of gene expression levels; however, the technical performance of kits and platforms aimed at single cell analysis has not been fully defined in terms of sensitivity and assay comparability. We compared three kits using purification columns (PicoPure) or direct lysis (CellsDirect and Cells-to-CT) combined with a one- or two-step RT-qPCR approach using dilutions of cells and RNA standards to the single cell level. Single cell-level messenger RNA (mRNA) analysis was possible using all three methods, although the precision, linearity, and effect of lysis buffer and cell background differed depending on the approach used. The impact of using a microfluidic qPCR platform versus a standard instrument was investigated for potential variability introduced by preamplification of template or scaling down of the qPCR to nanoliter volumes using laser-dissected single cell samples. The two approaches were found to be comparable. These studies show that accurate gene expression analysis is achievable at the single cell level and highlight the importance of well-validated experimental procedures for low-level mRNA analysis. Copyright © 2012 Elsevier Inc. All rights reserved.

Induced Pluripotent Stem Cells: Generation, Characterization, and Differentiation--Methods and Protocols.

PubMed

Graversen, Veronica Kon; Chavala, Sai H

2016-01-01

Reprogramming fibroblasts into induced pluripotent stem cells (iPSC) remains a promising technique for cell replacement therapy. Diverse populations of somatic cells have been examined for their reprogramming potential. Recently, ocular ciliary body epithelial cells (CECs) have been reprogrammed with high reprogramming efficiency and single transcription factor reprogramming, making them an exciting candidate for cellular reprogramming strategies.

Highly sensitive and quantitative detection of rare pathogens through agarose droplet microfluidic emulsion PCR at the single-cell level.

PubMed

Zhu, Zhi; Zhang, Wenhua; Leng, Xuefei; Zhang, Mingxia; Guan, Zhichao; Lu, Jiangquan; Yang, Chaoyong James

2012-10-21

Genetic alternations can serve as highly specific biomarkers to distinguish fatal bacteria or cancer cells from their normal counterparts. However, these mutations normally exist in very rare amount in the presence of a large excess of non-mutated analogs. Taking the notorious pathogen E. coli O157:H7 as the target analyte, we have developed an agarose droplet-based microfluidic ePCR method for highly sensitive, specific and quantitative detection of rare pathogens in the high background of normal bacteria. Massively parallel singleplex and multiplex PCR at the single-cell level in agarose droplets have been successfully established. Moreover, we challenged the system with rare pathogen detection and realized the sensitive and quantitative analysis of a single E. coli O157:H7 cell in the high background of 100,000 excess normal K12 cells. For the first time, we demonstrated rare pathogen detection through agarose droplet microfluidic ePCR. Such a multiplex single-cell agarose droplet amplification method enables ultra-high throughput and multi-parameter genetic analysis of large population of cells at the single-cell level to uncover the stochastic variations in biological systems.

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.

Bioinformatics approaches to single-cell analysis in developmental biology.

PubMed

Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H

2016-03-01

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Single-cell analysis of radiotracers' uptake by fluorescence microscopy: direct and droplet approach

NASA Astrophysics Data System (ADS)

Gallina, M. E.; Kim, T. J.; Vasquez, J.; Tuerkcan, S.; Abbyad, P.; Pratx, G.

2017-02-01

Radionuclides are used for sensitive and specific detection of small molecules in vivo and in vitro. Recently, radioluminescence microscopy extended their use to single-cell studies. Here we propose a new single-cell radioisotopic assay that improves throughput while adding sorting capabilities. The new method uses fluorescence-based sensor for revealing single-cell interactions with radioactive molecular markers. This study focuses on comparing two different experimental approaches. Several probes were tested and Dihydrorhodamine 123 was selected as the best compromise between sensitivity, brightness and stability. The sensor was incorporated either directly within the cell cytoplasm (direct approach), or it was coencapsulated with radiolabeled single-cells in oil-dispersed water droplets (droplet approach). Both approaches successfully activated the fluorescence signal following cellular uptake of 18F-fluorodeoxyglucose (FDG) and external Xrays exposure. The direct approach offered single-cell resolution and longtime stability ( > 20 hours), moreover it could discriminate FDG uptake at labelling concentration as low as 300 μCi/ml. In cells incubated with Dihydrorhodamine 123 after exposure to high radiation doses (8-16 Gy), the fluorescence signal was found to increase with the depletion of ROS quenchers. On the other side, the droplet approach required higher labelling concentrations (1.00 mCi/ml), and, at the current state of art, three cells per droplet are necessary to produce a fluorescent signal. This approach, however, is independent on cellular oxidative stress and, with further improvements, will be more suitable for studying heterogeneous populations. We anticipate this technology to pave the way for the analysis of single-cell interactions with radiomarkers by radiofluorogenic-activated single-cell sorting.

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.

Review of methods to probe single cell metabolism and bioenergetics

DOE PAGES

Vasdekis, Andreas E.; Stephanopoulos, Gregory

2014-10-31

The sampling and manipulation of cells down to the individual has been of substantial interest since the very beginning of Life Sciences. Herein, our objective is to highlight the most recent developments in single cell manipulation, as well as pioneering ones. First, flow-through methods will be discussed, namely methods in which the single cells flow continuously in an ordered manner during their analysis. This section will be followed by confinement techniques that enable cell isolation and confinement in one, two- or three-dimensions. Flow cytometry and droplet microfluidics are the two most common methods of flow-through analysis. While both are high-throughputmore » techniques, their difference lays in the fact that the droplet encapsulated cells experience a restricted and personal microenvironment, while in flow cytometry cells experience similar nutrient and stimuli initial concentrations. These methods are rather well established; however, they recently enabled immense strides in single cell phenotypic analysis, namely the identification and analysis of metabolically distinct individuals from an isogenic population using both droplet microfluidics and flow cytometry.« less

A system and methodology for high-content visual screening of individual intact living cells in suspension

NASA Astrophysics Data System (ADS)

Renaud, Olivier; Heintzmann, Rainer; Sáez-Cirión, Asier; Schnelle, Thomas; Mueller, Torsten; Shorte, Spencer

2007-02-01

Three dimensional imaging provides high-content information from living intact biology, and can serve as a visual screening cue. In the case of single cell imaging the current state of the art uses so-called "axial through-stacking". However, three-dimensional axial through-stacking requires that the object (i.e. a living cell) be adherently stabilized on an optically transparent surface, usually glass; evidently precluding use of cells in suspension. Aiming to overcome this limitation we present here the utility of dielectric field trapping of single cells in three-dimensional electrode cages. Our approach allows gentle and precise spatial orientation and vectored rotation of living, non-adherent cells in fluid suspension. Using various modes of widefield, and confocal microscope imaging we show how so-called "microrotation" can provide a unique and powerful method for multiple point-of-view (three-dimensional) interrogation of intact living biological micro-objects (e.g. single-cells, cell aggregates, and embryos). Further, we show how visual screening by micro-rotation imaging can be combined with micro-fluidic sorting, allowing selection of rare phenotype targets from small populations of cells in suspension, and subsequent one-step single cell cloning (with high-viability). Our methodology combining high-content 3D visual screening with one-step single cell cloning, will impact diverse paradigms, for example cytological and cytogenetic analysis on haematopoietic stem cells, blood cells including lymphocytes, and cancer cells.

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.

Beating the odds: The poisson distribution of all input cells during limiting dilution grossly underestimates whether a cell line is clonally-derived or not.

PubMed

Zhou, Yizhou; Shaw, David; Lam, Cynthia; Tsukuda, Joni; Yim, Mandy; Tang, Danming; Louie, Salina; Laird, Michael W; Snedecor, Brad; Misaghi, Shahram

2017-09-23

Establishing that a cell line was derived from a single cell progenitor and defined as clonally-derived for the production of clinical and commercial therapeutic protein drugs has been the subject of increased emphasis in cell line development (CLD). Several regulatory agencies have expressed that the prospective probability of clonality for CHO cell lines is assumed to follow the Poisson distribution based on the input cell count. The probability of obtaining monoclonal progenitors based on the Poisson distribution of all cells suggests that one round of limiting dilution may not be sufficient to assure the resulting cell lines are clonally-derived. We experimentally analyzed clonal derivatives originating from single cell cloning (SCC) via one round of limiting dilution, following our standard legacy cell line development practice. Two cell populations with stably integrated DNA spacers were mixed and subjected to SCC via limiting dilution. Cells were cultured in the presence of selection agent, screened, and ranked based on product titer. Post-SCC, the growing cell lines were screened by PCR analysis for the presence of identifying spacers. We observed that the percentage of nonclonal populations was below 9%, which is considerably lower than the determined probability based on the Poisson distribution of all cells. These results were further confirmed using fluorescence imaging of clonal derivatives originating from SCC via limiting dilution of mixed cell populations expressing GFP or RFP. Our results demonstrate that in the presence of selection agent, the Poisson distribution of all cells clearly underestimates the probability of obtaining clonally-derived cell lines. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 2017. © 2017 American Institute of Chemical Engineers.

Use of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells.

PubMed

Xin, Yurong; Kim, Jinrang; Ni, Min; Wei, Yi; Okamoto, Haruka; Lee, Joseph; Adler, Christina; Cavino, Katie; Murphy, Andrew J; Yancopoulos, George D; Lin, Hsin Chieh; Gromada, Jesper

2016-03-22

This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells, allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of α-cells (5%), β-cells (92%), δ-cells (1%), and pancreatic polypeptide cells (2%). We identified cell-type-specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability, low sequencing quality, or contamination resulting in the detection of more than one islet hormone. Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system.

Cooperative synchronized assemblies enhance orientation discrimination.

PubMed

Samonds, Jason M; Allison, John D; Brown, Heather A; Bonds, A B

2004-04-27

There is no clear link between the broad tuning of single neurons and the fine behavioral capabilities of orientation discrimination. We recorded from populations of cells in the cat visual cortex (area 17) to examine whether the joint activity of cells can support finer discrimination than found in individual responses. Analysis of joint firing yields a substantial advantage (i.e., cooperation) in fine-angle discrimination. This cooperation increases to more considerable levels as the population of an assembly is increased. The cooperation in a population of six cells provides encoding of orientation with an information advantage that is at least 2-fold in terms of requiring either fewer cells or less time than independent coding. This cooperation suggests that correlated or synchronized activity can increase information.

Hydrogel Droplet Microfluidics for High-Throughput Single Molecule/Cell Analysis.

PubMed

Zhu, Zhi; Yang, Chaoyong James

2017-01-17

Heterogeneity among individual molecules and cells has posed significant challenges to traditional bulk assays, due to the assumption of average behavior, which would lose important biological information in heterogeneity and result in a misleading interpretation. Single molecule/cell analysis has become an important and emerging field in biological and biomedical research for insights into heterogeneity between large populations at high resolution. Compared with the ensemble bulk method, single molecule/cell analysis explores the information on time trajectories, conformational states, and interactions of individual molecules/cells, all key factors in the study of chemical and biological reaction pathways. Various powerful techniques have been developed for single molecule/cell analysis, including flow cytometry, atomic force microscopy, optical and magnetic tweezers, single-molecule fluorescence spectroscopy, and so forth. However, some of them have the low-throughput issue that has to analyze single molecules/cells one by one. Flow cytometry is a widely used high-throughput technique for single cell analysis but lacks the ability for intercellular interaction study and local environment control. Droplet microfluidics becomes attractive for single molecule/cell manipulation because single molecules/cells can be individually encased in monodisperse microdroplets, allowing high-throughput analysis and manipulation with precise control of the local environment. Moreover, hydrogels, cross-linked polymer networks that swell in the presence of water, have been introduced into droplet microfluidic systems as hydrogel droplet microfluidics. By replacing an aqueous phase with a monomer or polymer solution, hydrogel droplets can be generated on microfluidic chips for encapsulation of single molecules/cells according to the Poisson distribution. The sol-gel transition property endows the hydrogel droplets with new functionalities and diversified applications in single molecule/cell analysis. The hydrogel can act as a 3D cell culture matrix to mimic the extracellular environment for long-term single cell culture, which allows further heterogeneity study in proliferation, drug screening, and metastasis at the single-cell level. The sol-gel transition allows reactions in solution to be performed rapidly and efficiently with product storage in the gel for flexible downstream manipulation and analysis. More importantly, controllable sol-gel regulation provides a new way to maintain phenotype-genotype linkages in the hydrogel matrix for high throughput molecular evolution. In this Account, we will review the hydrogel droplet generation on microfluidics, single molecule/cell encapsulation in hydrogel droplets, as well as the progress made by our group and others in the application of hydrogel droplet microfluidics for single molecule/cell analysis, including single cell culture, single molecule/cell detection, single cell sequencing, and molecular evolution.

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.

Circadian Clock Synchronization of the Cell Cycle in Zebrafish Occurs through a Gating Mechanism Rather Than a Period-phase Locking Process.

PubMed

Laranjeiro, Ricardo; Tamai, T Katherine; Letton, William; Hamilton, Noémie; Whitmore, David

2018-04-01

Studies from a number of model systems have shown that the circadian clock controls expression of key cell cycle checkpoints, thus providing permissive or inhibitory windows in which specific cell cycle events can occur. However, a major question remains: Is the clock actually regulating the cell cycle through such a gating mechanism or, alternatively, is there a coupling process that controls the speed of cell cycle progression? Using our light-responsive zebrafish cell lines, we address this issue directly by synchronizing the cell cycle in culture simply by changing the entraining light-dark (LD) cycle in the incubator without the need for pharmacological intervention. Our results show that the cell cycle rapidly reentrains to a shifted LD cycle within 36 h, with changes in p21 expression and subsequent S phase timing occurring within the first few hours of resetting. Reentrainment of mitosis appears to lag S phase resetting by 1 circadian cycle. The range of entrainment of the zebrafish clock to differing LD cycles is large, from 16 to 32 hour periods. We exploited this feature to explore cell cycle entrainment at both the population and single cell levels. At the population level, cell cycle length is shortened or lengthened under corresponding T-cycles, suggesting that a 1:1 coupling mechanism is capable of either speeding up or slowing down the cell cycle. However, analysis at the single cell level reveals that this, in fact, is not true and that a gating mechanism is the fundamental method of timed cell cycle regulation in zebrafish. Cell cycle length at the single cell level is virtually unaltered with varying T-cycles.

Circadian Clock Synchronization of the Cell Cycle in Zebrafish Occurs through a Gating Mechanism Rather Than a Period-phase Locking Process

PubMed Central

Tamai, T. Katherine; Letton, William; Hamilton, Noémie; Whitmore, David

2018-01-01

Studies from a number of model systems have shown that the circadian clock controls expression of key cell cycle checkpoints, thus providing permissive or inhibitory windows in which specific cell cycle events can occur. However, a major question remains: Is the clock actually regulating the cell cycle through such a gating mechanism or, alternatively, is there a coupling process that controls the speed of cell cycle progression? Using our light-responsive zebrafish cell lines, we address this issue directly by synchronizing the cell cycle in culture simply by changing the entraining light-dark (LD) cycle in the incubator without the need for pharmacological intervention. Our results show that the cell cycle rapidly reentrains to a shifted LD cycle within 36 h, with changes in p21 expression and subsequent S phase timing occurring within the first few hours of resetting. Reentrainment of mitosis appears to lag S phase resetting by 1 circadian cycle. The range of entrainment of the zebrafish clock to differing LD cycles is large, from 16 to 32 hour periods. We exploited this feature to explore cell cycle entrainment at both the population and single cell levels. At the population level, cell cycle length is shortened or lengthened under corresponding T-cycles, suggesting that a 1:1 coupling mechanism is capable of either speeding up or slowing down the cell cycle. However, analysis at the single cell level reveals that this, in fact, is not true and that a gating mechanism is the fundamental method of timed cell cycle regulation in zebrafish. Cell cycle length at the single cell level is virtually unaltered with varying T-cycles. PMID:29444612

Single-Cell RNA Sequencing of Human T Cells.

PubMed

Villani, Alexandra-Chloé; Shekhar, Karthik

2017-01-01

Understanding how populations of human T cells leverage cellular heterogeneity, plasticity, and diversity to achieve a wide range of functional flexibility, particularly during dynamic processes such as development, differentiation, and antigenic response, is a core challenge that is well suited for single-cell analysis. Hypothesis-free evaluation of cellular states and subpopulations by transcriptional profiling of single T cells can identify relationships that may be obscured by targeted approaches such as FACS sorting on cell-surface antigens, or bulk expression analysis. While this approach is relevant to all cell types, it is of particular interest in the study of T cells for which classical phenotypic criteria are now viewed as insufficient for distinguishing different T cell subtypes and transitional states, and defining the changes associated with dysfunctional T cell states in autoimmunity and tumor-related exhaustion. This unit describes a protocol to generate single-cell transcriptomic libraries of human blood CD4 + and CD8 + T cells, and also introduces the basic bioinformatic steps to process the resulting sequence data for further computational analysis. We show how cellular subpopulations can be identified from transcriptional data, and derive characteristic gene expression signatures that distinguish these states. We believe single-cell RNA-seq is a powerful technique to study the cellular heterogeneity in complex tissues, a paradigm that will be of great value for the immune system.

Intracellular pH Response to Weak Acid Stress in Individual Vegetative Bacillus subtilis Cells

PubMed Central

Pandey, Rachna; Vischer, Norbert O. E.; Smelt, Jan P. P. M.; van Beilen, Johan W. A.; Ter Beek, Alexander; De Vos, Winnok H.; Manders, Erik M. M.

2016-01-01

ABSTRACT Intracellular pH (pHi) critically affects bacterial cell physiology. Hence, a variety of food preservation strategies are aimed at perturbing pHi homeostasis. Unfortunately, accurate pHi quantification with existing methods is suboptimal, since measurements are averages across populations of cells, not taking into account interindividual heterogeneity. Yet, physiological heterogeneity in isogenic populations is well known to be responsible for differences in growth and division kinetics of cells in response to external stressors. To assess in this context the behavior of intracellular acidity, we have developed a robust method to quantify pHi at single-cell levels in Bacillus subtilis. Bacilli spoil food, cause disease, and are well known for their ability to form highly stress-resistant spores. Using an improved version of the genetically encoded ratiometric pHluorin (IpHluorin), we have quantified pHi in individual B. subtilis cells, cultured at an external pH of 6.4, in the absence or presence of weak acid stresses. In the presence of 3 mM potassium sorbate, a decrease in pHi and an increase in the generation time of growing cells were observed. Similar effects were observed when cells were stressed with 25 mM potassium acetate. Time-resolved analysis of individual bacteria in growing colonies shows that after a transient pH decrease, long-term pH evolution is highly cell dependent. The heterogeneity at the single-cell level shows the existence of subpopulations that might be more resistant and contribute to population survival. Our approach contributes to an understanding of pHi regulation in individual bacteria and may help scrutinizing effects of existing and novel food preservation strategies. IMPORTANCE This study shows how the physiological response to commonly used weak organic acid food preservatives, such as sorbic and acetic acids, can be measured at the single-cell level. These data are key to coupling often-observed single-cell heterogeneous growth behavior upon the addition of weak organic acid food preservatives. Generally, these data are gathered in the form of plate counting of samples incubated with the acids. Here, we visualize the underlying heterogeneity in cellular pH homeostasis, opening up avenues for mechanistic analyses of the heterogeneity in the weak acid stress response. Thus, microbial risk assessment can become more robust, widening the scope of use of these well-known weak organic acid food preservatives. PMID:27565617

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-12-01

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

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

PubMed Central

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

2017-01-01

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

A robust and tunable mitotic oscillator in artificial cells

PubMed Central

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

2018-01-01

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

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.

Singlet oxygen and ROS in a new light: low-dose subcellular photodynamic treatment enhances proliferation at the single cell level.

PubMed

Blázquez-Castro, Alfonso; Breitenbach, Thomas; Ogilby, Peter R

2014-09-01

Two-photon excitation of a sensitizer with a focused laser beam was used to create a spatially-localized subcellular population of reactive oxygen species, ROS, in single HeLa cells. The sensitizer used was protoporphyrin IX, PpIX, endogenously derived from 5-aminolevulinic acid delivered to the cells. Although we infer that singlet oxygen, O2(a(1)Δg), is one ROS produced upon irradiation of PpIX under these conditions, it is possible that the superoxide ion, O2(-˙), may also play a role in this system. With a "high" dose of PpIX-sensitized ROS, the expected death of the cell was observed. However, under "low dose" conditions, clear signs of cell proliferation were observed. The present results facilitate studies of ROS-mediated signalling in imaging-based single cell experiments.

CalQuo: automated, simultaneous single-cell and population-level quantification of global intracellular Ca2+ responses.

PubMed

Fritzsche, Marco; Fernandes, Ricardo A; Colin-York, Huw; Santos, Ana M; Lee, Steven F; Lagerholm, B Christoffer; Davis, Simon J; Eggeling, Christian

2015-11-13

Detecting intracellular calcium signaling with fluorescent calcium indicator dyes is often coupled with microscopy techniques to follow the activation state of non-excitable cells, including lymphocytes. However, the analysis of global intracellular calcium responses both at the single-cell level and in large ensembles simultaneously has yet to be automated. Here, we present a new software package, CalQuo (Calcium Quantification), which allows the automated analysis and simultaneous monitoring of global fluorescent calcium reporter-based signaling responses in up to 1000 single cells per experiment, at temporal resolutions of sub-seconds to seconds. CalQuo quantifies the number and fraction of responding cells, the temporal dependence of calcium signaling and provides global and individual calcium-reporter fluorescence intensity profiles. We demonstrate the utility of the new method by comparing the calcium-based signaling responses of genetically manipulated human lymphocytic cell lines.

Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation.

PubMed

Preissl, Sebastian; Fang, Rongxin; Huang, Hui; Zhao, Yuan; Raviram, Ramya; Gorkin, David U; Zhang, Yanxiao; Sos, Brandon C; Afzal, Veena; Dickel, Diane E; Kuan, Samantha; Visel, Axel; Pennacchio, Len A; Zhang, Kun; Ren, Bing

2018-03-01

Analysis of chromatin accessibility can reveal transcriptional regulatory sequences, but heterogeneity of primary tissues poses a significant challenge in mapping the precise chromatin landscape in specific cell types. Here we report single-nucleus ATAC-seq, a combinatorial barcoding-assisted single-cell assay for transposase-accessible chromatin that is optimized for use on flash-frozen primary tissue samples. We apply this technique to the mouse forebrain through eight developmental stages. Through analysis of more than 15,000 nuclei, we identify 20 distinct cell populations corresponding to major neuronal and non-neuronal cell types. We further define cell-type-specific transcriptional regulatory sequences, infer potential master transcriptional regulators and delineate developmental changes in forebrain cellular composition. Our results provide insight into the molecular and cellular dynamics that underlie forebrain development in the mouse and establish technical and analytical frameworks that are broadly applicable to other heterogeneous tissues.

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.

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.

Single CA3 pyramidal cells trigger sharp waves in vitro by exciting interneurones.

PubMed

Bazelot, Michaël; Teleńczuk, Maria T; Miles, Richard

2016-05-15

The CA3 hippocampal region generates sharp waves (SPW), a population activity associated with neuronal representations. The synaptic mechanisms responsible for the generation of these events still require clarification. Using slices maintained in an interface chamber, we found that the firing of single CA3 pyramidal cells triggers SPW like events at short latencies, similar to those for the induction of firing in interneurons. Multi-electrode records from the CA3 stratum pyramidale showed that pyramidal cells triggered events consisting of putative interneuron spikes followed by field IPSPs. SPW fields consisted of a repetition of these events at intervals of 4-8 ms. Although many properties of induced and spontaneous SPWs were similar, the triggered events tended to be initiated close to the stimulated cell. These data show that the initiation of SPWs in vitro is mediated via pyramidal cell synapses that excite interneurons. They do not indicate why interneuron firing is repeated during a SPW. Sharp waves (SPWs) are a hippocampal population activity that has been linked to neuronal representations. We show that SPWs in the CA3 region of rat hippocampal slices can be triggered by the firing of single pyramidal cells. Single action potentials in almost one-third of pyramidal cells initiated SPWs at latencies of 2-5 ms with probabilities of 0.07-0.76. Initiating pyramidal cells evoked field IPSPs (fIPSPs) at similar latencies when SPWs were not initiated. Similar spatial profiles for fIPSPs and middle components of SPWs suggested that SPW fields reflect repeated fIPSPs. Multiple extracellular records showed that the initiated SPWs tended to start near the stimulated pyramidal cell, whereas spontaneous SPWs could emerge at multiple sites. Single pyramidal cells could initiate two to six field IPSPs with distinct amplitude distributions, typically preceeded by a short-duration extracellular action potential. Comparison of these initiated fields with spontaneously occurring inhibitory field motifs allowed us to identify firing in different interneurones during the spread of SPWs. Propagation away from an initiating pyramidal cell was typically associated with the recruitment of interneurones and field IPSPs that were not activated by the stimulated pyramidal cell. SPW fields initiated by single cells were less variable than spontaneous events, suggesting that more stereotyped neuronal ensembles were activated, although neither the spatial profiles of fields, nor the identities of interneurone firing were identical for initiated events. The effects of single pyramidal cell on network events are thus mediated by different sequences of interneurone firing. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

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.

Single-cell sequencing unveils the lifestyle and CRISPR-based population history of Hydrotalea sp. in acid mine drainage.

PubMed

Medeiros, J D; Leite, L R; Pylro, V S; Oliveira, F S; Almeida, V M; Fernandes, G R; Salim, A C M; Araújo, F M G; Volpini, A C; Oliveira, G; Cuadros-Orellana, S

2017-10-01

Acid mine drainage (AMD) is characterized by an acid and metal-rich run-off that originates from mining systems. Despite having been studied for many decades, much remains unknown about the microbial community dynamics in AMD sites, especially during their early development, when the acidity is moderate. Here, we describe draft genome assemblies from single cells retrieved from an early-stage AMD sample. These cells belong to the genus Hydrotalea and are closely related to Hydrotalea flava. The phylogeny and average nucleotide identity analysis suggest that all single amplified genomes (SAGs) form two clades that may represent different strains. These cells have the genomic potential for denitrification, copper and other metal resistance. Two coexisting CRISPR-Cas loci were recovered across SAGs, and we observed heterogeneity in the population with regard to the spacer sequences, together with the loss of trailer-end spacers. Our results suggest that the genomes of Hydrotalea sp. strains studied here are adjusting to a quickly changing selective pressure at the microhabitat scale, and an important form of this selective pressure is infection by foreign DNA. © 2017 John Wiley & Sons Ltd.

Cell fixation and preservation for droplet-based single-cell transcriptomics.

PubMed

Alles, Jonathan; Karaiskos, Nikos; Praktiknjo, Samantha D; Grosswendt, Stefanie; Wahle, Philipp; Ruffault, Pierre-Louis; Ayoub, Salah; Schreyer, Luisa; Boltengagen, Anastasiya; Birchmeier, Carmen; Zinzen, Robert; Kocks, Christine; Rajewsky, Nikolaus

2017-05-19

Recent developments in droplet-based microfluidics allow the transcriptional profiling of thousands of individual cells in a quantitative, highly parallel and cost-effective way. A critical, often limiting step is the preparation of cells in an unperturbed state, not altered by stress or ageing. Other challenges are rare cells that need to be collected over several days or samples prepared at different times or locations. Here, we used chemical fixation to address these problems. Methanol fixation allowed us to stabilise and preserve dissociated cells for weeks without compromising single-cell RNA sequencing data. By using mixtures of fixed, cultured human and mouse cells, we first showed that individual transcriptomes could be confidently assigned to one of the two species. Single-cell gene expression from live and fixed samples correlated well with bulk mRNA-seq data. We then applied methanol fixation to transcriptionally profile primary cells from dissociated, complex tissues. Low RNA content cells from Drosophila embryos, as well as mouse hindbrain and cerebellum cells prepared by fluorescence-activated cell sorting, were successfully analysed after fixation, storage and single-cell droplet RNA-seq. We were able to identify diverse cell populations, including neuronal subtypes. As an additional resource, we provide 'dropbead', an R package for exploratory data analysis, visualization and filtering of Drop-seq data. We expect that the availability of a simple cell fixation method will open up many new opportunities in diverse biological contexts to analyse transcriptional dynamics at single-cell resolution.

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.

PubMed

Onken, Arno; Liu, Jian K; Karunasekara, P P Chamanthi R; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

2016-11-01

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding.

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains

PubMed Central

Onken, Arno; Liu, Jian K.; Karunasekara, P. P. Chamanthi R.; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

2016-01-01

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding. PMID:27814363

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.

Single cell gene expression profiling in Alzheimer's disease.

PubMed

Ginsberg, Stephen D; Che, Shaoli; Counts, Scott E; Mufson, Elliott J

2006-07-01

Development and implementation of microarray techniques to quantify expression levels of dozens to hundreds to thousands of transcripts simultaneously within select tissue samples from normal control subjects and neurodegenerative diseased brains has enabled scientists to create molecular fingerprints of vulnerable neuronal populations in Alzheimer's disease (AD) and related disorders. A goal is to sample gene expression from homogeneous cell types within a defined region without potential contamination by expression profiles of adjacent neuronal subpopulations and nonneuronal cells. The precise resolution afforded by single cell and population cell RNA analysis in combination with microarrays and real-time quantitative polymerase chain reaction (qPCR)-based analyses allows for relative gene expression level comparisons across cell types under different experimental conditions and disease progression. The ability to analyze single cells is an important distinction from global and regional assessments of mRNA expression and can be applied to optimally prepared tissues from animal models of neurodegeneration as well as postmortem human brain tissues. Gene expression analysis in postmortem AD brain regions including the hippocampal formation and neocortex reveals selectively vulnerable cell types share putative pathogenetic alterations in common classes of transcripts, for example, markers of glutamatergic neurotransmission, synaptic-related markers, protein phosphatases and kinases, and neurotrophins/neurotrophin receptors. Expression profiles of vulnerable regions and neurons may reveal important clues toward the understanding of the molecular pathogenesis of various neurological diseases and aid in identifying rational targets toward pharmacotherapeutic interventions for progressive, late-onset neurodegenerative disorders such as mild cognitive impairment (MCI) and AD.

Intra-genomic variation in symbiotic dinoflagellates: recent divergence or recombination between lineages?

PubMed

Wilkinson, Shaun P; Fisher, Paul L; van Oppen, Madeleine J H; Davy, Simon K

2015-03-14

The symbiosis between corals and the dinoflagellate alga Symbiodinium is essential for the development and survival of coral reefs. Yet this fragile association is highly vulnerable to environmental disturbance. A coral's ability to tolerate temperature stress depends on the fitness of its resident symbionts, whose thermal optima vary extensively between lineages. However, the in hospite population genetic structure of Symbiodinium is poorly understood and mostly based on analysis of bulk DNA extracted from thousands to millions of cells. Using quantitative single-cell PCR, we enumerated DNA polymorphisms in the symbionts of the reef-building coral Pocillopora damicornis, and applied a model selection approach to explore the potential for recombination between coexisting Symbiodinium populations. Two distinct Symbiodinium ITS2 sequences (denoted C100 and C109) were retrieved from all P. damicornis colonies analysed. However, the symbiont assemblage consisted of three distinct Symbiodinium populations: cells featuring pure arrays of ITS2 type C109, near-homogeneous cells of type C100 (with trace ITS2 copies of type C109), and those with co-dominant C100 and C109 ITS2 repeats. The symbiont consortia of some colonies consisted almost entirely of these putative C100 × C109 recombinants. Our results are consistent with the occurrence of sexual recombination between Symbiodinium types C100 and C109. While the multiple-copy nature of the ITS2 dictates that the observed pattern of intra-genomic co-dominance may be a result of incomplete concerted evolution of intra-genomic polymorphisms, this is a less likely explanation given the occurrence of homogeneous cells of the C109 type. Conclusive evidence for inter-lineage recombination and introgression in this genus will require either direct observational evidence or a single-cell genotyping approach targeting multiple, single-copy loci.

Stable isotope phenotyping via cluster analysis of NanoSIMS data as a method for characterizing distinct microbial ecophysiologies and sulfur-cycling in the environment

NASA Astrophysics Data System (ADS)

Dawson, K.; Scheller, S.; Dillon, J. G.; Orphan, V. J.

2016-12-01

Stable isotope probing (SIP) is a valuable tool for gaining insights into ecophysiology and biogeochemical cycling of environmental microbial communities by tracking isotopically labeled compounds into cellular macromolecules as well as into byproducts of respiration. SIP, in conjunction with nanoscale secondary ion mass spectrometry (NanoSIMS), allows for the visualization of isotope incorporation at the single cell level. In this manner, both active cells within a diverse population as well as heterogeneity in metabolism within a homogeneous population can be observed. The ecophysiological implications of these single cell stable isotope measurements are often limited to the taxonomic resolution of paired fluorescence in situ hybridization (FISH) microscopy. Here we introduce a taxonomy-independent method using multi-isotope SIP and NanoSIMS for identifying and grouping phenotypically similar microbial cells by their chemical and isotopic fingerprint. This method was applied to SIP experiments in a sulfur-cycling biofilm collected from sulfidic intertidal vents amended with 13C-acetate, 15N-ammonium, and 33S-sulfate. Using a cluster analysis technique based on fuzzy c-means to group cells according to their isotope (13C/12C, 15N/14N, and 33S/32S) and elemental ratio (C/CN and S/CN) profiles, our analysis partitioned 2200 cellular regions of interest (ROIs) into 5 distinct groups. These isotope phenotype groupings are reflective of the variation in labeled substrate uptake by cells in a multispecies metabolic network dominated by Gamma- and Deltaproteobacteria. Populations independently grouped by isotope phenotype were subsequently compared with paired FISH data, demonstrating a single coherent deltaproteobacterial cluster and multiple gammaproteobacterial groups, highlighting the distinct ecophysiologies of spatially-associated microbes within the sulfur-cycling biofilm from White Point Beach, CA.

Stable Isotope Phenotyping via Cluster Analysis of NanoSIMS Data As a Method for Characterizing Distinct Microbial Ecophysiologies and Sulfur-Cycling in the Environment

PubMed Central

Dawson, Katherine S.; Scheller, Silvan; Dillon, Jesse G.; Orphan, Victoria J.

2016-01-01

Stable isotope probing (SIP) is a valuable tool for gaining insights into ecophysiology and biogeochemical cycling of environmental microbial communities by tracking isotopically labeled compounds into cellular macromolecules as well as into byproducts of respiration. SIP, in conjunction with nanoscale secondary ion mass spectrometry (NanoSIMS), allows for the visualization of isotope incorporation at the single cell level. In this manner, both active cells within a diverse population as well as heterogeneity in metabolism within a homogeneous population can be observed. The ecophysiological implications of these single cell stable isotope measurements are often limited to the taxonomic resolution of paired fluorescence in situ hybridization (FISH) microscopy. Here we introduce a taxonomy-independent method using multi-isotope SIP and NanoSIMS for identifying and grouping phenotypically similar microbial cells by their chemical and isotopic fingerprint. This method was applied to SIP experiments in a sulfur-cycling biofilm collected from sulfidic intertidal vents amended with 13C-acetate, 15N-ammonium, and 33S-sulfate. Using a cluster analysis technique based on fuzzy c-means to group cells according to their isotope (13C/12C, 15N/14N, and 33S/32S) and elemental ratio (C/CN and S/CN) profiles, our analysis partitioned ~2200 cellular regions of interest (ROIs) into five distinct groups. These isotope phenotype groupings are reflective of the variation in labeled substrate uptake by cells in a multispecies metabolic network dominated by Gamma- and Deltaproteobacteria. Populations independently grouped by isotope phenotype were subsequently compared with paired FISH data, demonstrating a single coherent deltaproteobacterial cluster and multiple gammaproteobacterial groups, highlighting the distinct ecophysiologies of spatially-associated microbes within the sulfur-cycling biofilm from White Point Beach, CA. PMID:27303371

Single gene-based distinction of individual microbial genomes from a mixed population of microbial cells.

PubMed

Tamminen, Manu V; Virta, Marko P J

2015-01-01

Recent progress in environmental microbiology has revealed vast populations of microbes in any given habitat that cannot be detected by conventional culturing strategies. The use of sensitive genetic detection methods such as CARD-FISH and in situ PCR have been limited by the cell wall permeabilization requirement that cannot be performed similarly on all cell types without lysing some and leaving some nonpermeabilized. Furthermore, the detection of low copy targets such as genes present in single copies in the microbial genomes, has remained problematic. We describe an emulsion-based procedure to trap individual microbial cells into picoliter-volume polyacrylamide droplets that provide a rigid support for genetic material and therefore allow complete degradation of cellular material to expose the individual genomes. The polyacrylamide droplets are subsequently converted into picoliter-scale reactors for genome amplification. The amplified genomes are labeled based on the presence of a target gene and differentiated from those that do not contain the gene by flow cytometry. Using the Escherichia coli strains XL1 and MC1061, which differ with respect to the presence (XL1), or absence (MC1061) of a single copy of a tetracycline resistance gene per genome, we demonstrate that XL1 genomes present at 0.1% of MC1061 genomes can be differentiated using this method. Using a spiked sediment microbial sample, we demonstrate that the method is applicable to highly complex environmental microbial communities as a target gene-based screen for individual microbes. The method provides a novel tool for enumerating functional cell populations in complex microbial communities. We envision that the method could be optimized for fluorescence-activated cell sorting to enrich genetic material of interest from complex environmental samples.

Negative Enrichment and Isolation of Circulating Tumor Cells for Whole Genome Amplification.

PubMed

Kanwar, Nisha; Done, Susan J

2017-01-01

Circulating tumor cells (CTCs) are a rare population of cells found in the peripheral blood of patients with many types of cancer such as breast, prostate, colon, and lung cancers. Higher numbers of these cells in blood are associated with a poorer prognosis of patients. Genomic profiling of CTCs would help characterize markers specific for the identification of these cells in blood, and also define genomic alterations that give these cells a metastatic advantage over other cells in the primary tumor. Here, we describe an immunomagnetic method to enrich CTCs from the blood of patients with breast cancer, followed by single-cell laser capture microdissection to isolate single CTCs. Whole genome amplification of isolated CTCs allows for many downstream applications to be performed to aide in their characterization, such as whole genome or exome sequencing, Single Nucleotide Polymorphism (SNP) and copy number analysis, and targeted sequencing or quantitative Polymerase Chain Reaction (qPCR) for genomic analyses.

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.

Single quantum dot tracking reveals the impact of nanoparticle surface on intracellular state.

PubMed

Zahid, Mohammad U; Ma, Liang; Lim, Sung Jun; Smith, Andrew M

2018-05-08

Inefficient delivery of macromolecules and nanoparticles to intracellular targets is a major bottleneck in drug delivery, genetic engineering, and molecular imaging. Here we apply live-cell single-quantum-dot imaging and tracking to analyze and classify nanoparticle states after intracellular delivery. By merging trajectory diffusion parameters with brightness measurements, multidimensional analysis reveals distinct and heterogeneous populations that are indistinguishable using single parameters alone. We derive new quantitative metrics of particle loading, cluster distribution, and vesicular release in single cells, and evaluate intracellular nanoparticles with diverse surfaces following osmotic delivery. Surface properties have a major impact on cell uptake, but little impact on the absolute cytoplasmic numbers. A key outcome is that stable zwitterionic surfaces yield uniform cytosolic behavior, ideal for imaging agents. We anticipate that this combination of quantum dots and single-particle tracking can be widely applied to design and optimize next-generation imaging probes, nanoparticle therapeutics, and biologics.

A planarian p53 homolog regulates proliferation and self-renewal in adult stem cell lineages.

PubMed

Pearson, Bret J; Sánchez Alvarado, Alejandro

2010-01-01

The functions of adult stem cells and tumor suppressor genes are known to intersect. However, when and how tumor suppressors function in the lineages produced by adult stem cells is unknown. With a large population of stem cells that can be manipulated and studied in vivo, the freshwater planarian is an ideal system with which to investigate these questions. Here, we focus on the tumor suppressor p53, homologs of which have no known role in stem cell biology in any invertebrate examined thus far. Planaria have a single p53 family member, Smed-p53, which is predominantly expressed in newly made stem cell progeny. When Smed-p53 is targeted by RNAi, the stem cell population increases at the expense of progeny, resulting in hyper-proliferation. However, ultimately the stem cell population fails to self-renew. Our results suggest that prior to the vertebrates, an ancestral p53-like molecule already had functions in stem cell proliferation control and self-renewal.

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 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.

Analysis of tumoral spheres growing in a multichamber microfluidic device.

PubMed

Belgorosky, Denise; Fernández-Cabada, Tamara; Peñaherrera-Pazmiño, Ana Belén; Langle, Yanina; Booth, Ross; Bhansali, Shekhar; Pérez, Maximiliano S; Eiján, Ana María; Lerner, Betiana

2018-09-01

Lab on a Chip (LOC) farming systems have emerged as a powerful tool for single cell studies combined with a non-adherent cell culture substrate and single cell capture chips for the study of single cell derived tumor spheres. Cancer is characterized by its cellular heterogeneity where only a small population of cancer stem cells (CSCs) are responsible for tumor metastases and recurrences. Thus, the in vitro strategy to the formation of a single cell-derived sphere is an attractive alternative to identify CSCs. In this study, we test the effectiveness of microdevices for analysis of heterogeneity within CSC populations and its interaction with different components of the extracellular matrix. CSC could be identify using specific markers related to its pluripotency and self-renewal characteristics such as the transcription factor Oct-4 or the surface protein CD44. The results confirm the usefulness of LOC as an effective method for quantification of CSC, through the formation of spheres under conditions of low adhesion or growing on components of the extracellular matrix. The device used is also a good alternative for evaluating the individual growth of each sphere and further identification of these CSC markers by immunofluorescence. In conclusion, LOC devices have not only the already known advantages, but they are also a promising tool since they use small amounts of reagents and are under specific culture parameters. LOC devices could be considered as a novel technology to be used as a complement or replacement of traditional studies on culture plates. © 2018 Wiley Periodicals, Inc.

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

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

Characterization of the Population of the Sulfur-Oxidizing Symbiont of Codakia orbicularis (Bivalvia, Lucinidae) by Single-Cell Analyses▿ †

PubMed Central

Caro, Audrey; Gros, Olivier; Got, Patrice; De Wit, Rutger; Troussellier, Marc

2007-01-01

We investigated the characteristics of the sulfur-oxidizing symbiont hosted in the gills of Codakia orbicularis, a bivalve living in shallow marine tropical environments. Special attention was paid to describing the heterogeneity of the population by using single-cell approaches including flow cytometry (FCM) and different microscopic techniques and by analyzing a cell size fractionation experiment. Up to seven different subpopulations were distinguished by FCM based on nucleic acid content and light side scattering of the cells. The cell size analysis of symbionts showed that the symbiotic population was very heterogeneous in size, i.e., ranging from 0.5 to 5 μm in length, with variable amounts of intracellular sulfur. The side-scatter signal analyzed by FCM, which is often taken as a proxy of cell size, was greatly influenced by the sulfur content of the symbionts. FCM revealed an important heterogeneity in the relative nucleic acid content among the subclasses. The larger cells contained exceptionally high levels of nucleic acids, suggesting that these cells contained multiple copies of their genome, i.e., ranging from one copy for the smaller cells to more than four copies for the larger cells. The proportion of respiring symbionts (5-cyano-2,3-ditolyl-terazolium chloride positive) in the bacteriocytes of Codakia revealed that around 80% of the symbionts hosted by Codakia maintain respiratory activity throughout the year. These data allowed us to gain insight into the functioning of the symbionts within the host and to propose some hypotheses on how the growth of the symbionts is controlled by the host. PMID:17259363

Comparison of diagnostic capability of macular ganglion cell complex and retinal nerve fiber layer among primary open angle glaucoma, ocular hypertension, and normal population using Fourier-domain optical coherence tomography and determining their functional correlation in Indian population

PubMed Central

Barua, Nabanita; Sitaraman, Chitra; Goel, Sonu; Chakraborti, Chandana; Mukherjee, Sonai; Parashar, Hemandra

2016-01-01

Context: Analysis of diagnostic ability of macular ganglionic cell complex and retinal nerve fiber layer (RNFL) in glaucoma. Aim: To correlate functional and structural parameters and comparing predictive value of each of the structural parameters using Fourier-domain (FD) optical coherence tomography (OCT) among primary open angle glaucoma (POAG) and ocular hypertension (OHT) versus normal population. Setting and Design: Single centric, cross-sectional study done in 234 eyes. Materials and Methods: Patients were enrolled in three groups: POAG, ocular hypertensive and normal (40 patients in each group). After comprehensive ophthalmological examination, patients underwent standard automated perimetry and FD-OCT scan in optic nerve head and ganglion cell mode. The relationship was assessed by correlating ganglion cell complex (GCC) parameters with mean deviation. Results were compared with RNFL parameters. Statistical Analysis: Data were analyzed with SPSS, analysis of variance, t-test, Pearson's coefficient, and receiver operating curve. Results: All parameters showed strong correlation with visual field (P < 0.001). Inferior GCC had highest area under curve (AUC) for detecting glaucoma (0.827) in POAG from normal population. However, the difference was not statistically significant (P > 0.5) when compared with other parameters. None of the parameters showed significant diagnostic capability to detect OHT from normal population. In diagnosing early glaucoma from OHT and normal population, only inferior GCC had statistically significant AUC value (0.715). Conclusion: In this study, GCC and RNFL parameters showed equal predictive capability in perimetric versus normal group. In early stage, inferior GCC was the best parameter. In OHT population, single day cross-sectional imaging was not valuable. PMID:27221682

Population Distribution Analyses Reveal a Hierarchy of Molecular Players Underlying Parallel Endocytic Pathways

PubMed Central

Gupta, Gagan D.; Howes, Mark T.; Chandran, Ruma; Das, Anupam; Menon, Sindhu; Parton, Robert G.; Sowdhamini, R.; Thattai, Mukund; Mayor, Satyajit

2014-01-01

Single-cell-resolved measurements reveal heterogeneous distributions of clathrin-dependent (CD) and -independent (CLIC/GEEC: CG) endocytic activity in Drosophila cell populations. dsRNA-mediated knockdown of core versus peripheral endocytic machinery induces strong changes in the mean, or subtle changes in the shapes of these distributions, respectively. By quantifying these subtle shape changes for 27 single-cell features which report on endocytic activity and cell morphology, we organize 1072 Drosophila genes into a tree-like hierarchy. We find that tree nodes contain gene sets enriched in functional classes and protein complexes, providing a portrait of core and peripheral control of CD and CG endocytosis. For 470 genes we obtain additional features from separate assays and classify them into early- or late-acting genes of the endocytic pathways. Detailed analyses of specific genes at intermediate levels of the tree suggest that Vacuolar ATPase and lysosomal genes involved in vacuolar biogenesis play an evolutionarily conserved role in CG endocytosis. PMID:24971745

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

PubMed Central

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

2014-01-01

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

Inertial-ordering-assisted droplet microfluidics for high-throughput single-cell RNA-sequencing.

PubMed

Moon, Hui-Sung; Je, Kwanghwi; Min, Jae-Woong; Park, Donghyun; Han, Kyung-Yeon; Shin, Seung-Ho; Park, Woong-Yang; Yoo, Chang Eun; Kim, Shin-Hyun

2018-02-27

Single-cell RNA-seq reveals the cellular heterogeneity inherent in the population of cells, which is very important in many clinical and research applications. Recent advances in droplet microfluidics have achieved the automatic isolation, lysis, and labeling of single cells in droplet compartments without complex instrumentation. However, barcoding errors occurring in the cell encapsulation process because of the multiple-beads-in-droplet and insufficient throughput because of the low concentration of beads for avoiding multiple-beads-in-a-droplet remain important challenges for precise and efficient expression profiling of single cells. In this study, we developed a new droplet-based microfluidic platform that significantly improved the throughput while reducing barcoding errors through deterministic encapsulation of inertially ordered beads. Highly concentrated beads containing oligonucleotide barcodes were spontaneously ordered in a spiral channel by an inertial effect, which were in turn encapsulated in droplets one-by-one, while cells were simultaneously encapsulated in the droplets. The deterministic encapsulation of beads resulted in a high fraction of single-bead-in-a-droplet and rare multiple-beads-in-a-droplet although the bead concentration increased to 1000 μl -1 , which diminished barcoding errors and enabled accurate high-throughput barcoding. We successfully validated our device with single-cell RNA-seq. In addition, we found that multiple-beads-in-a-droplet, generated using a normal Drop-Seq device with a high concentration of beads, underestimated transcript numbers and overestimated cell numbers. This accurate high-throughput platform can expand the capability and practicality of Drop-Seq in single-cell analysis.

Single-cell analysis of HIV-1 transcriptional activity reveals expression of proviruses in expanded clones during ART.

PubMed

Wiegand, Ann; Spindler, Jonathan; Hong, Feiyu F; Shao, Wei; Cyktor, Joshua C; Cillo, Anthony R; Halvas, Elias K; Coffin, John M; Mellors, John W; Kearney, Mary F

2017-05-02

Little is known about the fraction of human immunodeficiency virus type 1 (HIV-1) proviruses that express unspliced viral RNA in vivo or about the levels of HIV RNA expression within single infected cells. We developed a sensitive cell-associated HIV RNA and DNA single-genome sequencing (CARD-SGS) method to investigate fractional proviral expression of HIV RNA (1.3-kb fragment of p6, protease, and reverse transcriptase) and the levels of HIV RNA in single HIV-infected cells from blood samples obtained from individuals with viremia or individuals on long-term suppressive antiretroviral therapy (ART). Spiking experiments show that the CARD-SGS method can detect a single cell expressing HIV RNA. Applying CARD-SGS to blood mononuclear cells in six samples from four HIV-infected donors (one with viremia and not on ART and three with viremia suppressed on ART) revealed that an average of 7% of proviruses (range: 2-18%) expressed HIV RNA. Levels of expression varied from one to 62 HIV RNA molecules per cell (median of 1). CARD-SGS also revealed the frequent expression of identical HIV RNA sequences across multiple single cells and across multiple time points in donors on suppressive ART consistent with constitutive expression of HIV RNA in infected cell clones. Defective proviruses were found to express HIV RNA at levels similar to those proviruses that had no obvious defects. CARD-SGS is a useful tool to characterize fractional proviral expression in single infected cells that persist despite ART and to assess the impact of experimental interventions on proviral populations and their expression.

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

Single-cell analysis of the transcriptome and its application in the characterization of stem cells and early embryos.

PubMed

Liu, Na; Liu, Lin; Pan, Xinghua

2014-07-01

Cellular heterogeneity within a cell population is a common phenomenon in multicellular organisms, tissues, cultured cells, and even FACS-sorted subpopulations. Important information may be masked if the cells are studied as a mass. Transcriptome profiling is a parameter that has been intensively studied, and relatively easier to address than protein composition. To understand the basis and importance of heterogeneity and stochastic aspects of the cell function and its mechanisms, it is essential to examine transcriptomes of a panel of single cells. High-throughput technologies, starting from microarrays and now RNA-seq, provide a full view of the expression of transcriptomes but are limited by the amount of RNA for analysis. Recently, several new approaches for amplification and sequencing the transcriptome of single cells or a limited low number of cells have been developed and applied. In this review, we summarize these major strategies, such as PCR-based methods, IVT-based methods, phi29-DNA polymerase-based methods, and several other methods, including their principles, characteristics, advantages, and limitations, with representative applications in cancer stem cells, early development, and embryonic stem cells. The prospects for development of future technology and application of transcriptome analysis in a single cell are also discussed.

Mex3a Marks a Slowly Dividing Subpopulation of Lgr5+ Intestinal Stem Cells.

PubMed

Barriga, Francisco M; Montagni, Elisa; Mana, Miyeko; Mendez-Lago, Maria; Hernando-Momblona, Xavier; Sevillano, Marta; Guillaumet-Adkins, Amy; Rodriguez-Esteban, Gustavo; Buczacki, Simon J A; Gut, Marta; Heyn, Holger; Winton, Douglas J; Yilmaz, Omer H; Attolini, Camille Stephan-Otto; Gut, Ivo; Batlle, Eduard

2017-06-01

Highly proliferative Lgr5+ stem cells maintain the intestinal epithelium and are thought to be largely homogeneous. Although quiescent intestinal stem cell (ISC) populations have been described, the identity and features of such a population remain controversial. Here we report unanticipated heterogeneity within the Lgr5+ ISC pool. We found that expression of the RNA-binding protein Mex3a labels a slowly cycling subpopulation of Lgr5+ ISCs that contribute to all intestinal lineages with distinct kinetics. Single-cell transcriptome profiling revealed that Lgr5+ cells adopt two discrete states, one of which is defined by a Mex3a expression program and relatively low levels of proliferation genes. During homeostasis, Mex3a+ cells continually shift into the rapidly dividing, self-renewing ISC pool. Chemotherapy and radiation preferentially target rapidly dividing Lgr5+ cells but spare the Mex3a-high/Lgr5+ population, helping to promote regeneration of the intestinal epithelium following toxic insults. Thus, Mex3a defines a reserve-like ISC population within the Lgr5+ compartment. Copyright © 2017 Elsevier Inc. All rights reserved.

Rapid Antibiotic Susceptibility Testing of Uropathogenic E. coli by Tracking Submicron Scale Motion of Single Bacterial Cells.

PubMed

Syal, Karan; Shen, Simon; Yang, Yunze; Wang, Shaopeng; Haydel, Shelley E; Tao, Nongjian

2017-08-25

To combat antibiotic resistance, a rapid antibiotic susceptibility testing (AST) technology that can identify resistant infections at disease onset is required. Current clinical AST technologies take 1-3 days, which is often too slow for accurate treatment. Here we demonstrate a rapid AST method by tracking sub-μm scale bacterial motion with an optical imaging and tracking technique. We apply the method to clinically relevant bacterial pathogens, Escherichia coli O157: H7 and uropathogenic E. coli (UPEC) loosely tethered to a glass surface. By analyzing dose-dependent sub-μm motion changes in a population of bacterial cells, we obtain the minimum bactericidal concentration within 2 h using human urine samples spiked with UPEC. We validate the AST method using the standard culture-based AST methods. In addition to population studies, the method allows single cell analysis, which can identify subpopulations of resistance strains within a sample.

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

PubMed

Merritt, Jason; Kuehn, Seppe

2016-09-12

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

Microfluidic Device

NASA Technical Reports Server (NTRS)

Tai, Yu-Chong (Inventor); Kasdan, Harvey L. (Inventor); Zheng, Siyang (Inventor); Lin, Jeffrey Chun-Hui (Inventor)

2016-01-01

Described herein are particular embodiments relating to a microfluidic device that may be utilized for cell sensing, counting, and/or sorting. Particular aspects relate to a microfabricated device that is capable of differentiating single cell types from dense cell populations. One particular embodiment relates a device and methods of using the same for sensing, counting, and/or sorting leukocytes from whole, undiluted blood samples.

Microfluidic Device

NASA Technical Reports Server (NTRS)

Zheng, Siyang (Inventor); Lin, Jeffrey Chun-Hui (Inventor); Kasdan, Harvey (Inventor); Tai, Yu-Chong (Inventor)

2015-01-01

Described herein are particular embodiments relating to a microfluidic device that may be utilized for cell sensing, counting, and/or sorting. Particular aspects relate to a microfabricated device that is capable of differentiating single cell types from dense cell populations. One particular embodiment relates a device and methods of using the same for sensing, counting, and/or sorting leukocytes from whole, undiluted blood samples.

Microfluidic Device

NASA Technical Reports Server (NTRS)

Tai, Yu-Chong (Inventor); Zheng, Siyang (Inventor); Lin, Jeffrey Chun-Hui (Inventor); Kasdan, Harvey L. (Inventor)

2017-01-01

Described herein are particular embodiments relating to a microfluidic device that may be utilized for cell sensing, counting, and/or sorting. Particular aspects relate to a microfabricated device that is capable of differentiating single cell types from dense cell populations. One particular embodiment relates a device and methods of using the same for sensing, counting, and/or sorting leukocytes from whole, undiluted blood samples.

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.

Sequential establishment of stripe patterns in an expanding cell population.

PubMed

Liu, Chenli; Fu, Xiongfei; Liu, Lizhong; Ren, Xiaojing; Chau, Carlos K L; Li, Sihong; Xiang, Lu; Zeng, Hualing; Chen, Guanhua; Tang, Lei-Han; Lenz, Peter; Cui, Xiaodong; Huang, Wei; Hwa, Terence; Huang, Jian-Dong

2011-10-14

Periodic stripe patterns are ubiquitous in living organisms, yet the underlying developmental processes are complex and difficult to disentangle. We describe a synthetic genetic circuit that couples cell density and motility. This system enabled programmed Escherichia coli cells to form periodic stripes of high and low cell densities sequentially and autonomously. Theoretical and experimental analyses reveal that the spatial structure arises from a recurrent aggregation process at the front of the continuously expanding cell population. The number of stripes formed could be tuned by modulating the basal expression of a single gene. The results establish motility control as a simple route to establishing recurrent structures without requiring an extrinsic pacemaker.

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

Imaging trace element distributions in single organelles and subcellular features

NASA Astrophysics Data System (ADS)

Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; Rose, Volker; Vogt, Stefan; El-Muayed, Malek

2016-02-01

The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro- and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cd (which some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators. It could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies.

Single Cell Analysis of Human RAD18-Dependent DNA Post-Replication Repair by Alkaline Bromodeoxyuridine Comet Assay

PubMed Central

Mórocz, Mónika; Gali, Himabindu; Raskó, István; Downes, C. Stephen; Haracska, Lajos

2013-01-01

Damage to DNA can block replication progression resulting in gaps in the newly synthesized DNA. Cells utilize a number of post-replication repair (PRR) mechanisms such as the RAD18 controlled translesion synthesis or template switching to overcome the discontinuities formed opposite the DNA lesions and to complete DNA replication. Gaining more insights into the role of PRR genes promotes better understanding of DNA damage tolerance and of how their malfunction can lead to increased genome instability and cancer. However, a simple and efficient method to characterise gene specific PRR deficiencies at a single cell level has not been developed. Here we describe the so named BrdU comet PRR assay to test the contribution of human RAD18 to PRR at a single cell level, by which we kinetically characterized the consequences of the deletion of human RAD18 on the replication of UV-damaged DNA. Moreover, we demonstrate the capability of our method to evaluate PRR at a single cell level in unsynchronized cell population. PMID:23936422

Influence of type-I fimbriae and fluid shear stress on bacterial behavior and multicellular architecture of early Escherichia coli biofilms at single-cell resolution.

PubMed

Wang, Liyun; Keatch, Robert; Zhao, Qi; Wright, John A; Bryant, Clare E; Redmann, Anna L; Terentjev, Eugene M

2018-01-12

Biofilm formation on abiotic surfaces in food and medical industry can cause severe contamination and infection, yet how biological and physical factors determine cellular architecture of early biofilms and bacterial behavior of the constituent cells remains largely unknown. In this study we examine the specific role of type-I fimbriae in nascent stages of biofilm formation and the response of micro-colonies to environmental flow shear at single-cell resolution. The results show that type-I fimbriae are not required for reversible adhesion from plankton, but critical for irreversible adhesion of Escherichia coli ( E.coli ) MG1655 forming biofilms on polyethylene terephthalate (PET) surfaces. Besides establishing a firm cell-surface contact, the irreversible adhesion seems necessary to initiate the proliferation of E.coli on the surface. After application of shear stress, bacterial retention is dominated by the 3D architecture of colonies independent of the population and the multi-layered structure could protect the embedded cells from being insulted by fluid shear, while cell membrane permeability mainly depends on the biofilm population and the duration time of the shear stress. Importance Bacterial biofilms could lead to severe contamination problems in medical devices and food processing equipment. However, biofilms are usually studied at a rough macroscopic level, thus little is known about how individual bacterial behavior within biofilms and multicellular architecture are influenced by bacterial appendages (e.g. pili/fimbriae) and environmental factors during early biofilm formation. We apply Confocal Laser Scanning Microscopy (CLSM) to visualize E.coli micro-colonies at single-cell resolution. Our findings suggest that type-I fimbriae are vital to the initiation of bacterial proliferation on surfaces and that the responses of biofilm architecture and cell membrane permeability of constituent bacteria to fluid shear stress are different, which are respectively regulated by the 3D morphology and the population of micro-colonies. Copyright © 2018 American Society for Microbiology.

In vivo marking of single cells in chick embryos using photoactivation of GFP.

PubMed

Stark, D A; Kulesa, P M

2005-10-01

Selective marking of a single cell within a living embryo is often difficult due to the inaccuracy and invasiveness of standard techniques. This unit describes a minimally invasive optical protocol that uses 405-nm laser light to photoactivate a variant of green fluorescent protein (PAGFP). This method takes advantage of the accessibility of the chick embryo to inject PAGFP into a region of interest and uses electroporation to deliver the construct into cells. This unit describes in detail how single and small groups of cells (n<10) that express PAGFP can be made visually distinguishable from the host population using the photoactivation process. Included is a means to maximize the fluorescence increase due to photoactivated GFP signal and to reduce photobleaching. Briefly outlined are previously developed chick culture and time-lapse imaging techniques to allow for the subsequent monitoring of photoactivated cell migratory behaviors. The technique has the potential to be a less-invasive, accurate tool for in vivo studies that involve following cell lineage and cell migration.

Integrating single-cell transcriptomic data across different conditions, technologies, and species.

PubMed

Butler, Andrew; Hoffman, Paul; Smibert, Peter; Papalexi, Efthymia; Satija, Rahul

2018-06-01

Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

Palladium-based Mass-Tag Cell Barcoding with a Doublet-Filtering Scheme and Single Cell Deconvolution Algorithm

PubMed Central

Zunder, Eli R.; Finck, Rachel; Behbehani, Gregory K.; Amir, El-ad D.; Krishnaswamy, Smita; Gonzalez, Veronica D.; Lorang, Cynthia G.; Bjornson, Zach; Spitzer, Matthew H.; Bodenmiller, Bernd; Fantl, Wendy J.; Pe’er, Dana; Nolan, Garry P.

2015-01-01

SUMMARY Mass-tag cell barcoding (MCB) labels individual cell samples with unique combinatorial barcodes, after which they are pooled for processing and measurement as a single multiplexed sample. The MCB method eliminates variability between samples in antibody staining and instrument sensitivity, reduces antibody consumption, and shortens instrument measurement time. Here, we present an optimized MCB protocol with several improvements over previously described methods. The use of palladium-based labeling reagents expands the number of measurement channels available for mass cytometry and reduces interference with lanthanide-based antibody measurement. An error-detecting combinatorial barcoding scheme allows cell doublets to be identified and removed from the analysis. A debarcoding algorithm that is single cell-based rather than population-based improves the accuracy and efficiency of sample deconvolution. This debarcoding algorithm has been packaged into software that allows rapid and unbiased sample deconvolution. The MCB procedure takes 3–4 h, not including sample acquisition time of ~1 h per million cells. PMID:25612231

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

Vasdekis, Andreas E.; Stephanopoulos, Gregory

The sampling and manipulation of cells down to the individual has been of substantial interest since the very beginning of Life Sciences. Herein, our objective is to highlight the most recent developments in single cell manipulation, as well as pioneering ones. First, flow-through methods will be discussed, namely methods in which the single cells flow continuously in an ordered manner during their analysis. This section will be followed by confinement techniques that enable cell isolation and confinement in one, two- or three-dimensions. Flow cytometry and droplet microfluidics are the two most common methods of flow-through analysis. While both are high-throughputmore » techniques, their difference lays in the fact that the droplet encapsulated cells experience a restricted and personal microenvironment, while in flow cytometry cells experience similar nutrient and stimuli initial concentrations. These methods are rather well established; however, they recently enabled immense strides in single cell phenotypic analysis, namely the identification and analysis of metabolically distinct individuals from an isogenic population using both droplet microfluidics and flow cytometry.« less

Introduction to Single-Cell RNA Sequencing.

PubMed

Olsen, Thale Kristin; Baryawno, Ninib

2018-04-01

During the last decade, high-throughput sequencing methods have revolutionized the entire field of biology. The opportunity to study entire transcriptomes in great detail using RNA sequencing (RNA-seq) has fueled many important discoveries and is now a routine method in biomedical research. However, RNA-seq is typically performed in "bulk," and the data represent an average of gene expression patterns across thousands to millions of cells; this might obscure biologically relevant differences between cells. Single-cell RNA-seq (scRNA-seq) represents an approach to overcome this problem. By isolating single cells, capturing their transcripts, and generating sequencing libraries in which the transcripts are mapped to individual cells, scRNA-seq allows assessment of fundamental biological properties of cell populations and biological systems at unprecedented resolution. Here, we present the most common scRNA-seq protocols in use today and the basics of data analysis and discuss factors that are important to consider before planning and designing an scRNA-seq project. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

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

PubMed Central

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

2018-01-01

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

Tracing the origin of disseminated tumor cells in breast cancer using single-cell sequencing.

PubMed

Demeulemeester, Jonas; Kumar, Parveen; Møller, Elen K; Nord, Silje; Wedge, David C; Peterson, April; Mathiesen, Randi R; Fjelldal, Renathe; Zamani Esteki, Masoud; Theunis, Koen; Fernandez Gallardo, Elia; Grundstad, A Jason; Borgen, Elin; Baumbusch, Lars O; Børresen-Dale, Anne-Lise; White, Kevin P; Kristensen, Vessela N; Van Loo, Peter; Voet, Thierry; Naume, Bjørn

2016-12-09

Single-cell micro-metastases of solid tumors often occur in the bone marrow. These disseminated tumor cells (DTCs) may resist therapy and lay dormant or progress to cause overt bone and visceral metastases. The molecular nature of DTCs remains elusive, as well as when and from where in the tumor they originate. Here, we apply single-cell sequencing to identify and trace the origin of DTCs in breast cancer. We sequence the genomes of 63 single cells isolated from six non-metastatic breast cancer patients. By comparing the cells' DNA copy number aberration (CNA) landscapes with those of the primary tumors and lymph node metastasis, we establish that 53% of the single cells morphologically classified as tumor cells are DTCs disseminating from the observed tumor. The remaining cells represent either non-aberrant "normal" cells or "aberrant cells of unknown origin" that have CNA landscapes discordant from the tumor. Further analyses suggest that the prevalence of aberrant cells of unknown origin is age-dependent and that at least a subset is hematopoietic in origin. Evolutionary reconstruction analysis of bulk tumor and DTC genomes enables ordering of CNA events in molecular pseudo-time and traced the origin of the DTCs to either the main tumor clone, primary tumor subclones, or subclones in an axillary lymph node metastasis. Single-cell sequencing of bone marrow epithelial-like cells, in parallel with intra-tumor genetic heterogeneity profiling from bulk DNA, is a powerful approach to identify and study DTCs, yielding insight into metastatic processes. A heterogeneous population of CNA-positive cells is present in the bone marrow of non-metastatic breast cancer patients, only part of which are derived from the observed tumor lineages.

Diffusion maps for high-dimensional single-cell analysis of differentiation data.

PubMed

Haghverdi, Laleh; Buettner, Florian; Theis, Fabian J

2015-09-15

Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in cell populations. Analyzing such high-dimensional single-cell data has its own statistical and computational challenges. Popular multivariate approaches are based on data normalization, followed by dimension reduction and clustering to identify subgroups. However, in the case of cellular differentiation, we would not expect clear clusters to be present but instead expect the cells to follow continuous branching lineages. Here, we propose the use of diffusion maps to deal with the problem of defining differentiation trajectories. We adapt this method to single-cell data by adequate choice of kernel width and inclusion of uncertainties or missing measurement values, which enables the establishment of a pseudotemporal ordering of single cells in a high-dimensional gene expression space. We expect this output to reflect cell differentiation trajectories, where the data originates from intrinsic diffusion-like dynamics. Starting from a pluripotent stage, cells move smoothly within the transcriptional landscape towards more differentiated states with some stochasticity along their path. We demonstrate the robustness of our method with respect to extrinsic noise (e.g. measurement noise) and sampling density heterogeneities on simulated toy data as well as two single-cell quantitative polymerase chain reaction datasets (i.e. mouse haematopoietic stem cells and mouse embryonic stem cells) and an RNA-Seq data of human pre-implantation embryos. We show that diffusion maps perform considerably better than Principal Component Analysis and are advantageous over other techniques for non-linear dimension reduction such as t-distributed Stochastic Neighbour Embedding for preserving the global structures and pseudotemporal ordering of cells. The Matlab implementation of diffusion maps for single-cell data is available at https://www.helmholtz-muenchen.de/icb/single-cell-diffusion-map. fbuettner.phys@gmail.com, fabian.theis@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Enhanced metastatic capacity of breast cancer cells after interaction and hybrid formation with mesenchymal stroma/stem cells (MSC).

PubMed

Melzer, Catharina; von der Ohe, Juliane; Hass, Ralf

2018-01-05

Fusion of breast cancer cells with tumor-associated populations of the microenvironment including mesenchymal stroma/stem-like cells (MSC) represents a rare event in cell communication whereby the metastatic capacity of those hybrid cells remains unclear. Functional changes were investigated in vitro and in vivo following spontaneous fusion and hybrid cell formation between primary human MSC and human MDA-MB-231 breast cancer cells. Thus, lentiviral eGFP-labeled MSC and breast cancer cells labeled with mcherry resulted in dual-fluorescing hybrid cells after co-culture. Double FACS sorting and single cell cloning revealed two different aneuploid male hybrid populations (MDA-hyb1 and MDA-hyb2) with different STR profiles, pronounced telomerase activities, and enhanced proliferative capacities as compared to the parental cells. Microarray-based mRNA profiling demonstrated marked regulation of genes involved in epithelial-mesenchymal transition and increased expression of metastasis-associated genes including S100A4. In vivo studies following subcutaneous injection of the breast cancer and the two hybrid populations substantiated the in vitro findings by a significantly elevated tumor growth of the hybrid cells. Moreover, both hybrid populations developed various distant organ metastases in a much shorter period of time than the parental breast cancer cells. Together, these data demonstrate spontaneous development of new tumor cell populations exhibiting different parental properties after close interaction and subsequent fusion of MSC with breast cancer cells. This formation of tumor hybrids contributes to continuously increasing tumor heterogeneity and elevated metastatic capacities.

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

PubMed Central

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

2014-01-01

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

Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets

PubMed Central

Macosko, Evan Z.; Basu, Anindita; Satija, Rahul; Nemesh, James; Shekhar, Karthik; Goldman, Melissa; Tirosh, Itay; Bialas, Allison R.; Kamitaki, Nolan; Martersteck, Emily M.; Trombetta, John J.; Weitz, David A.; Sanes, Joshua R.; Shalek, Alex K.; Regev, Aviv; McCarroll, Steven A.

2015-01-01

Summary Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-Seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell’s RNAs, and sequencing them all together. Drop-Seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts’ cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-Seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. PMID:26000488

How to design a single-cell RNA-sequencing experiment: pitfalls, challenges and perspectives.

PubMed

Dal Molin, Alessandra; Di Camillo, Barbara

2018-01-31

The sequencing of the transcriptome of single cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types in heterogeneous cell populations or for the study of stochastic gene expression. In recent years, various experimental methods and computational tools for analysing single-cell RNA-sequencing data have been proposed. However, most of them are tailored to different experimental designs or biological questions, and in many cases, their performance has not been benchmarked yet, thus increasing the difficulty for a researcher to choose the optimal single-cell transcriptome sequencing (scRNA-seq) experiment and analysis workflow. In this review, we aim to provide an overview of the current available experimental and computational methods developed to handle single-cell RNA-sequencing data and, based on their peculiarities, we suggest possible analysis frameworks depending on specific experimental designs. Together, we propose an evaluation of challenges and open questions and future perspectives in the field. In particular, we go through the different steps of scRNA-seq experimental protocols such as cell isolation, messenger RNA capture, reverse transcription, amplification and use of quantitative standards such as spike-ins and Unique Molecular Identifiers (UMIs). We then analyse the current methodological challenges related to preprocessing, alignment, quantification, normalization, batch effect correction and methods to control for confounding effects. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

Scaling and automation of a high-throughput single-cell-derived tumor sphere assay chip.

PubMed

Cheng, Yu-Heng; Chen, Yu-Chih; Brien, Riley; Yoon, Euisik

2016-10-07

Recent research suggests that cancer stem-like cells (CSCs) are the key subpopulation for tumor relapse and metastasis. Due to cancer plasticity in surface antigen and enzymatic activity markers, functional tumorsphere assays are promising alternatives for CSC identification. To reliably quantify rare CSCs (1-5%), thousands of single-cell suspension cultures are required. While microfluidics is a powerful tool in handling single cells, previous works provide limited throughput and lack automatic data analysis capability required for high-throughput studies. In this study, we present the scaling and automation of high-throughput single-cell-derived tumor sphere assay chips, facilitating the tracking of up to ∼10 000 cells on a chip with ∼76.5% capture rate. The presented cell capture scheme guarantees sampling a representative population from the bulk cells. To analyze thousands of single-cells with a variety of fluorescent intensities, a highly adaptable analysis program was developed for cell/sphere counting and size measurement. Using a Pluronic® F108 (poly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol)) coating on polydimethylsiloxane (PDMS), a suspension culture environment was created to test a controversial hypothesis: whether larger or smaller cells are more stem-like defined by the capability to form single-cell-derived spheres. Different cell lines showed different correlations between sphere formation rate and initial cell size, suggesting heterogeneity in pathway regulation among breast cancer cell lines. More interestingly, by monitoring hundreds of spheres, we identified heterogeneity in sphere growth dynamics, indicating the cellular heterogeneity even within CSCs. These preliminary results highlight the power of unprecedented high-throughput and automation in CSC studies.

Isolation and Purification of Satellite Cells for Skeletal Muscle Tissue Engineering

PubMed Central

Syverud, Brian C; Lee, Jonah D; VanDusen, Keith W; Larkin, Lisa M

2015-01-01

Engineered skeletal muscle holds promise as a source of graft tissue for the repair of traumatic injuries such as volumetric muscle loss. The resident skeletal muscle stem cell, the satellite cell, has been identified as an ideal progenitor for tissue engineering due to its role as an essential player in the potent skeletal muscle regeneration mechanism. A significant challenge facing tissue engineers, however, is the isolation of sufficiently large satellite cell populations with high purity. The two common isolation techniques, single fiber explant culture and enzymatic dissociation, can yield either a highly pure satellite cell population or a suitably large number or cells but fail to do both simultaneously. As a result, it is often necessary to use a purification technique such as pre-plating or cell sorting to enrich the satellite cell population post-isolation. Furthermore, the absence of complex chemical and biophysical cues influencing the in vivo satellite cell “niche” complicates the culture of isolated satellite cells. Techniques under investigation to maximize myogenic proliferation and differentiation in vitro are described in this article, along with current methods for isolating and purifying satellite cells. PMID:26413555

The simultaneous isolation of multiple high and low frequent T-cell populations from donor peripheral blood mononuclear cells using the major histocompatibility complex I-Streptamer isolation technology.

PubMed

Roex, Marthe C J; Hageman, Lois; Heemskerk, Matthias T; Veld, Sabrina A J; van Liempt, Ellis; Kester, Michel G D; Germeroth, Lothar; Stemberger, Christian; Falkenburg, J H Frederik; Jedema, Inge

2018-04-01

Adoptive transfer of donor-derived T cells can be applied to improve immune reconstitution in immune-compromised patients after allogeneic stem cell transplantation. The separation of beneficial T cells from potentially harmful T cells can be achieved by using the major histocompatibility complex (MHC) I-Streptamer isolation technology, which has proven its feasibility for the fast and pure isolation of T-cell populations with a single specificity. We have analyzed the feasibility of the simultaneous isolation of multiple antigen-specific T-cell populations in one procedure by combining different MHC I-Streptamers. First, the effect of combining different amounts of MHC I-Streptamers used in the isolation procedure on the isolation efficacy of target antigen-specific T cells and on the number of off-target co-isolated contaminating cells was assessed. The feasibility of this approach was demonstrated in large-scale validation procedures targeting both high and low frequent T-cell populations using the Good Manufacturing Practice (GMP)-compliant CliniMACS Plus device. T-cell products targeting up to 24 different T-cell populations could be isolated in one, simultaneous MHC I-Streptamer procedure, by adjusting the amount of MHC I- Streptamers per target antigen-specific T-cell population. Concurrently, the co-isolation of potentially harmful contaminating T cells remained below our safety limit. This technology allows the reproducible isolation of high and low frequent T-cell populations. However, the expected therapeutic relevance of direct clinical application without in vitro expansion of these low frequent T-cell populations is questionable. This study provides a feasible, fast and safe method for the generation of highly personalized MHC I-Streptamer isolated T-cell products for adoptive immunotherapy. Copyright © 2018 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Continuous cell introduction and rapid dynamic lysis for high-throughput single-cell analysis on microfludic chips with hydrodynamic focusing.

PubMed

Xu, Chun-Xiu; Yin, Xue-Feng

2011-02-04

A chip-based microfluidic system for high-throughput single-cell analysis is described. The system was integrated with continuous introduction of individual cells, rapid dynamic lysis, capillary electrophoretic (CE) separation and laser induced fluorescence (LIF) detection. A cross microfluidic chip with one sheath-flow channel located on each side of the sampling channel was designed. The labeled cells were hydrodynamically focused by sheath-flow streams and sequentially introduced into the cross section of the microchip under hydrostatic pressure generated by adjusting liquid levels in the reservoirs. Combined with the electric field applied on the separation channel, the aligned cells were driven into the separation channel and rapidly lysed within 33ms at the entry of the separation channel by Triton X-100 added in the sheath-flow solution. The maximum rate for introducing individual cells into the separation channel was about 150cells/min. The introduction of sheath-flow streams also significantly reduced the concentration of phosphate-buffered saline (PBS) injected into the separation channel along with single cells, thus reducing Joule heating during electrophoretic separation. The performance of this microfluidic system was evaluated by analysis of reduced glutathione (GSH) and reactive oxygen species (ROS) in single erythrocytes. A throughput of 38cells/min was obtained. The proposed method is simple and robust for high-throughput single-cell analysis, allowing for analysis of cell population with considerable size to generate results with statistical significance. Copyright © 2010 Elsevier B.V. All rights reserved.

Single-cell codetection of metabolic activity, intracellular functional proteins, and genetic mutations from rare circulating tumor cells.

PubMed

Zhang, Yu; Tang, Yin; Sun, Shuai; Wang, Zhihua; Wu, Wenjun; Zhao, Xiaodong; Czajkowsky, Daniel M; Li, Yan; Tian, Jianhui; Xu, Ling; Wei, Wei; Deng, Yuliang; Shi, Qihui

2015-10-06

The high glucose uptake and activation of oncogenic signaling pathways in cancer cells has long made these features, together with the mutational spectrum, prime diagnostic targets of circulating tumor cells (CTCs). Further, an ability to characterize these properties at a single cell resolution is widely believed to be essential, as the known extensive heterogeneity in CTCs can obscure important correlations in data obtained from cell population-based methods. However, to date, it has not been possible to quantitatively measure metabolic, proteomic, and genetic data from a single CTC. Here we report a microchip-based approach that allows for the codetection of glucose uptake, intracellular functional proteins, and genetic mutations at the single-cell level from rare tumor cells. The microchip contains thousands of nanoliter grooves (nanowells) that isolate individual CTCs and allow for the assessment of their glucose uptake via imaging of a fluorescent glucose analog, quantification of a panel of intracellular signaling proteins using a miniaturized antibody barcode microarray, and retrieval of the individual cell nuclei for subsequent off-chip genome amplification and sequencing. This approach integrates molecular-scale information on the metabolic, proteomic, and genetic status of single cells and permits the inference of associations between genetic signatures, energy consumption, and phosphoproteins oncogenic signaling activities in CTCs isolated from blood samples of patients. Importantly, this microchip chip-based approach achieves this multidimensional molecular analysis with minimal cell loss (<20%), which is the bottleneck of the rare cell analysis.

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.

The Poisson distribution and beyond: methods for microfluidic droplet production and single cell encapsulation.

PubMed

Collins, David J; Neild, Adrian; deMello, Andrew; Liu, Ai-Qun; Ai, Ye

2015-09-07

There is a recognized and growing need for rapid and efficient cell assays, where the size of microfluidic devices lend themselves to the manipulation of cellular populations down to the single cell level. An exceptional way to analyze cells independently is to encapsulate them within aqueous droplets surrounded by an immiscible fluid, so that reagents and reaction products are contained within a controlled microenvironment. Most cell encapsulation work has focused on the development and use of passive methods, where droplets are produced continuously at high rates by pumping fluids from external pressure-driven reservoirs through defined microfluidic geometries. With limited exceptions, the number of cells encapsulated per droplet in these systems is dictated by Poisson statistics, reducing the proportion of droplets that contain the desired number of cells and thus the effective rate at which single cells can be encapsulated. Nevertheless, a number of recently developed actively-controlled droplet production methods present an alternative route to the production of droplets at similar rates and with the potential to improve the efficiency of single-cell encapsulation. In this critical review, we examine both passive and active methods for droplet production and explore how these can be used to deterministically and non-deterministically encapsulate cells.

A Bilayer Construct Controls Adipose-Derived Stem Cell Differentiation into Endothelial Cells and Pericytes without Growth Factor Stimulation

DTIC Science & Technology

2011-01-01

A Bilayer Construct Controls Adipose-Derived Stem Cell Differentiation into Endothelial Cells and Pericytes Without Growth Factor Stimulation...Ph.D.3 This work describes the differentiation of adipose-derived mesenchymal stem cells (ASC) in a composite hy- drogel for use as a vascularized...tissue from a single population of ASC. This work underscores the importance of the extracellular matrix in controlling stem cell phenotype. It is our

Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis.

PubMed

Savas, Peter; Virassamy, Balaji; Ye, Chengzhong; Salim, Agus; Mintoff, Christopher P; Caramia, Franco; Salgado, Roberto; Byrne, David J; Teo, Zhi L; Dushyanthen, Sathana; Byrne, Ann; Wein, Lironne; Luen, Stephen J; Poliness, Catherine; Nightingale, Sophie S; Skandarajah, Anita S; Gyorki, David E; Thornton, Chantel M; Beavis, Paul A; Fox, Stephen B; Darcy, Phillip K; Speed, Terence P; Mackay, Laura K; Neeson, Paul J; Loi, Sherene

2018-06-25

The quantity of tumor-infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival, particularly in triple-negative and HER2-overexpressing BC subtypes 1 . Although T cells are the predominant TIL population 2 , the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6,311 T cells isolated from human BCs and show that significant heterogeneity exists in the infiltrating T cell population. We demonstrate that BCs with a high number of TILs contained CD8 + T cells with features of tissue-resident memory T (T RM ) cell differentiation and that these CD8 + T RM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8 + T RM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple-negative breast cancer (TNBC) and provided better prognostication than CD8 expression alone. Our data suggest that CD8 + T RM cells contribute to BC immunosurveillance and are the key targets of modulation by immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of T RM cells will be crucial for successful immunotherapeutic development in BC.

Multiscale Modeling of Microbial Communities

NASA Astrophysics Data System (ADS)

Blanchard, Andrew

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

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

PubMed

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

2016-11-01

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

Effects of acute hypoxia/acidosis on intracellular pH in differentiating neural progenitor cells.

PubMed

Nordström, Tommy; Jansson, Linda C; Louhivuori, Lauri M; Akerman, Karl E O

2012-06-21

The response of differentiating mouse neural progenitor cells, migrating out from neurospheres, to conditions simulating ischemia (hypoxia and extracellular or intracellular acidosis) was studied. We show here, by using BCECF and single cell imaging to monitor intracellular pH (pH(i)), that two main populations can be distinguished by exposing migrating neural progenitor cells to low extracellular pH or by performing an acidifying ammonium prepulse. The cells dominating at the periphery of the neurosphere culture, which were positive for neuron specific markers MAP-2, calbindin and NeuN had lower initial resting pH(i) and could also easily be further acidified by lowering the extracellular pH. Moreover, in this population, a more profound acidification was seen when the cells were acidified using the ammonium prepulse technique. However, when the cell population was exposed to depolarizing potassium concentrations no alterations in pH(i) took place in this population. In contrast, depolarization caused an increase in pH(i) (by 0.5 pH units) in the cell population closer to the neurosphere body, which region was positive for the radial cell marker (GLAST). This cell population, having higher resting pH(i) (pH 6.9-7.1) also responded to acute hypoxia. During hypoxic treatment the resting pH(i) decreased by 0.1 pH units and recovered rapidly after reoxygenation. Our results show that migrating neural progenitor cells are highly sensitive to extracellular acidosis and that irreversible damage becomes evident at pH 6.2. Moreover, our results show that a response to acidosis clearly distinguishes two individual cell populations probably representing neuronal and radial cells. Copyright © 2012 Elsevier B.V. All rights reserved.

Targeted reconstruction of T cell receptor sequence from single cell RNA-seq links CDR3 length to T cell differentiation state

PubMed Central

Yates, Kathleen B.; Bi, Kevin; Darko, Samuel; Godec, Jernej; Gerdemann, Ulrike; Swadling, Leo; Douek, Daniel C.; Klenerman, Paul; Barnes, Eleanor J.; Sharpe, Arlene H.

2017-01-01

Abstract The T cell compartment must contain diversity in both T cell receptor (TCR) repertoire and cell state to provide effective immunity against pathogens. However, it remains unclear how differences in the TCR contribute to heterogeneity in T cell state. Single cell RNA-sequencing (scRNA-seq) can allow simultaneous measurement of TCR sequence and global transcriptional profile from single cells. However, current methods for TCR inference from scRNA-seq are limited in their sensitivity and require long sequencing reads, thus increasing the cost and decreasing the number of cells that can be feasibly analyzed. Here we present TRAPeS, a publicly available tool that can efficiently extract TCR sequence information from short-read scRNA-seq libraries. We apply it to investigate heterogeneity in the CD8+ T cell response in humans and mice, and show that it is accurate and more sensitive than existing approaches. Coupling TRAPeS with transcriptome analysis of CD8+ T cells specific for a single epitope from Yellow Fever Virus (YFV), we show that the recently described ‘naive-like’ memory population have significantly longer CDR3 regions and greater divergence from germline sequence than do effector-memory phenotype cells. This suggests that TCR usage is associated with the differentiation state of the CD8+ T cell response to YFV. PMID:28934479

Development of a single-cell X-ray fluorescence flow cytometer

DOE PAGES

Crawford, Andrew M.; Kurecka, Patrick; Yim, Tsz Kwan; ...

2016-06-17

An X-ray fluorescence flow cytometer that can determine the total metal content of single cells has been developed. Capillary action or pressure was used to load cells into hydrophilic or hydrophobic capillaries, respectively. Once loaded, the cells were transported at a fixed vertical velocity past a focused X-ray beam. X-ray fluorescence was then used to determine the mass of metal in each cell. By making single-cell measurements, the population heterogeneity for metals in the µ M to m M concentration range on fL sample volumes can be directly measured, a measurement that is difficult using most analytical methods. This approachmore » has been used to determine the metal composition of 936 individual bovine red blood cells (bRBC), 31 individual 3T3 mouse fibroblasts (NIH3T3) and 18 Saccharomyces cerevisiae (yeast) cells with an average measurement frequency of ~4 cells min –1. These data show evidence for surprisingly broad metal distributions. Lastly, details of the device design, data analysis and opportunities for further sensitivity improvement are described.« less

Single-hit mechanism of tumour cell killing by radiation.

PubMed

Chapman, J D

2003-02-01

To review the relative importance of the single-hit mechanism of radiation killing for tumour response to 1.8-2.0 Gy day(-1) fractions and to low dose-rate brachytherapy. Tumour cell killing by ionizing radiation is well described by the linear-quadratic equation that contains two independent components distinguished by dose kinetics. Analyses of tumour cell survival curves that contain six or more dose points usually provide good estimates of the alpha- and beta-inactivation coefficients. Superior estimates of tumour cell intrinsic radiosensitivity are obtained when synchronized populations are employed. The characteristics of single-hit inactivation of tumour cells are reviewed and compared with the characteristics of beta-inactivation. Potential molecular targets associated with single-hit inactivation are discussed along with strategies for potentiating cell killing by this mechanism. The single-hit mechanism of tumour cell killing shows no dependence on dose-rate and, consequently, no evidence of sublethal damage repair. It is uniquely potentiated by high linear-energy-transfer radiation, exhibits a smaller oxygen enhancement ratio and exhibits a larger indirect effect by hydroxyl radicals than the beta-mechanism. alpha-inactivation coefficients vary slightly throughout interphase but mitotic cells exhibit extremely high alpha-coefficients in the range of those observed for lymphocytes and some repair-deficient cells. Evidence is accumulating to suggest that chromatin in compacted form could be a radiation-hypersensitive target associated with single-hit radiation killing. Analyses of tumour cell survival curves demonstrate that it is the single-hit mechanism (alpha) that determines the majority of cell killing after doses of 2Gy and that this mechanism is highly variable between tumour cell lines. The characteristics of single-hit inactivation are qualitatively and quantitatively distinct from those of beta-inactivation. Compacted chromatin in tumour cells should be further investigated as a radiation-hypersensitive target that could be modulated for therapeutic advantage.

Uncovering stem-cell heterogeneity in the microniche with label-free microfluidics

NASA Astrophysics Data System (ADS)

Sohn, Lydia L.

2013-03-01

Better suited for large number of cells from bulk tissue, traditional cell-screening techniques, such as fluorescence-activated cell sorting (FACS) and magnetic-activated cell sorting (MACS), cannot easily screen stem or progenitor cells from minute populations found in their physiological niches. Furthermore, they rely upon irreversible antibody binding, potentially altering cell properties, including gene expression and regenerative capacity. We have developed a label-free, single-cell analysis microfluidic platform capable of quantifying cell-surface marker expression of functional organ stem cells directly isolated from their micro-anatomical niche. With this platform, we have screened single quiescent muscle stem (satellite) cells derived from single myofibers, and we have uncovered an important heterogeneity in the surface-marker expression of these cells. By sorting the screened cells with our microfluidic device, we have determined what this heterogeneity means in terms of muscle stem-cell functionality. For instance, we show that the levels of beta1-integrin can predict the differentiation capacity of quiescent satellite cells, and in contrast to recent literature, that some CXCR4 + cells are not myogenic. Our results provide the first direct demonstration of a microniche-specific variation in gene expression in stem cells of the same lineage. Overall, our label-free, single-cell analysis and cell-sorting platform could be extended to other systems involving rare-cell subsets. This work was funded by the W. M. Keck Foundation, NIH, and California Institute of Regenerative Medicine

Single-cell lineage tracking analysis reveals that an established cell line comprises putative cancer stem cells and their heterogeneous progeny

PubMed Central

Sato, Sachiko; Rancourt, Ann; Sato, Yukiko; Satoh, Masahiko S.

2016-01-01

Mammalian cell culture has been used in many biological studies on the assumption that a cell line comprises putatively homogeneous clonal cells, thereby sharing similar phenotypic features. This fundamental assumption has not yet been fully tested; therefore, we developed a method for the chronological analysis of individual HeLa cells. The analysis was performed by live cell imaging, tracking of every single cell recorded on imaging videos, and determining the fates of individual cells. We found that cell fate varied significantly, indicating that, in contrast to the assumption, the HeLa cell line is composed of highly heterogeneous cells. Furthermore, our results reveal that only a limited number of cells are immortal and renew themselves, giving rise to the remaining cells. These cells have reduced reproductive ability, creating a functionally heterogeneous cell population. Hence, the HeLa cell line is maintained by the limited number of immortal cells, which could be putative cancer stem cells. PMID:27003384

Improved native UV laser induced fluorescence detection for single cell analysis in poly(dimethylsiloxane) microfluidic devices.

PubMed

Hellmich, Wibke; Greif, Dominik; Pelargus, Christoph; Anselmetti, Dario; Ros, Alexandra

2006-10-20

Single cell analytics is a key method in the framework of proteom research allowing analyses, which are not subjected to ensemble-averaging, cell-cycle or heterogeneous cell-population effects. Our previous studies on single cell analysis in poly(dimethylsiloxane) microfluidic devices with native label-free laser induced fluorescence detection [W. Hellmich, C. Pelargus, K. Leffhalm, A. Ros, D. Anselmetti, Electrophoresis 26 (2005) 3689] were extended in order to improve separation efficiency and detection sensitivity. Here, we particularly focus on the influence of poly(oxyethylene) based coatings on the separation performance. In addition, the influence on background fluorescence is studied by the variation of the incident laser power as well as the adaptation of the confocal volume to the microfluidic channel dimensions. Last but not least, the use of carbon black particles further enhanced the detection limit to 25 nM, thereby reaching the relevant concentration ranges necessary for the label-free detection of low abundant proteins in single cells. On the basis of these results, we demonstrate the first electropherogram from an individual Spodoptera frugiperda (Sf9) cell with native label-free UV-LIF detection in a microfluidic chip.

Genome-nuclear lamina interactions: from cell populations to single cells.

PubMed

Yáñez-Cuna, J Omar; van Steensel, Bas

2017-04-01

Lamina-associated domains (LADs) are large genomic regions that interact with the nuclear lamina (NL) and help to guide the spatial folding of chromosomes in the interphase nucleus. LADs have been linked to gene repression and other functions. Recent studies have begun to uncover some of the molecular players that drive LAD-NL interactions. A picture emerges in which DNA sequence, chromatin components and nuclear lamina proteins play an important role. Complementary to this, imaging and single-cell genomics approaches have revealed that some LAD-NL interactions are variable from cell to cell, while others are very stable. Understanding LADs can provide a unique perspective into the general process of genome organization. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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

Application of fluorescent dye substrates for functional characterization of ABC multidrug transporters at a single cell level.

PubMed

Nerada, Zsuzsanna; Hegyi, Zoltán; Szepesi, Áron; Tóth, Szilárd; Hegedüs, Csilla; Várady, György; Matula, Zsolt; Homolya, László; Sarkadi, Balázs; Telbisz, Ágnes

2016-09-01

ABC multidrug transporters are key players in cancer multidrug resistance and in determining the ADME-Tox properties of drugs and xenobiotics. The most sensitive and specific detection of these transporters is based on functional assays. Assessment of the transporter-dependent reduction of cellular uptake of the fluorescent dyes, such as Hoechst 33342 (Ho) and more recently DyeCycle Violet (DCV), have been widely advocated for the characterization of both ABCB1 and ABCG2 multidrug transporters. Detailed comparison of these supravital DNA-binding dyes revealed that DCV is less toxic to ABCG2- and ABCB1-expressing cells than Ho. ATPase measurements imply that DCV and Ho are similarly handled by ABCB1, whereas ABCG2 seems to transport DVC more effectively. In addition, we have developed an image-based high content microscopy screening method for simultaneous in situ measurement of the cellular activity and expression of the ABCG2 multidrug transporter. We demonstrated the applicability of this method for identifying ABCG2-positive cells in heterogeneous cell population by a single dye uptake measurement. These results may promote multidrug transporter studies at a single cell level and allow the quantitative detection of clinically important drug-resistant sub-populations. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Temporal Variation in Single-Cell Power-Law Rheology Spans the Ensemble Variation of Cell Population.

PubMed

Cai, PingGen; Takahashi, Ryosuke; Kuribayashi-Shigetomi, Kaori; Subagyo, Agus; Sueoka, Kazuhisa; Maloney, John M; Van Vliet, Krystyn J; Okajima, Takaharu

2017-08-08

Changes in the cytoskeletal organization within cells can be characterized by large spatial and temporal variations in rheological properties of the cell (e.g., the complex shear modulus G ∗ ). Although the ensemble variation in G ∗ of single cells has been elucidated, the detailed temporal variation of G ∗ remains unknown. In this study, we investigated how the rheological properties of individual fibroblast cells change under a spatially confined environment in which the cell translational motion is highly restricted and the whole cell shape remains unchanged. The temporal evolution of single-cell rheology was probed at the same measurement location within the cell, using atomic force microscopy-based oscillatory deformation. The measurements reveal that the temporal variation in the power-law rheology of cells is quantitatively consistent with the ensemble variation, indicating that the cell system satisfies an ergodic hypothesis in which the temporal statistics are identical to the ensemble statistics. The autocorrelation of G ∗ implies that the cell mechanical state evolves in the ensemble of possible states with a characteristic timescale. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Genetic modification of mesenchymal stem cells to express a single-chain antibody against EGFRvIII on the cell surface.

PubMed

Balyasnikova, Irina V; Franco-Gou, Rosa; Mathis, J Michael; Lesniak, Maciej S

2010-06-01

Human adult mesenchymal stem cells (hMSCs) are under active investigation as cellular carriers for gene therapy. hMSCs possess natural tropism toward tumours; however, the targeting of hMSCs to specific cell populations within tumours is unexplored. In the case of glioblastoma multiforme (GBM), at least half of the tumours express EGFRvIII on the cell surface, an ideal target for antibody-mediated gene/drug delivery. In this study, we investigated the feasibility of genetically modifying hMSCs to express a single-chain antibody (scFv) to EGFRvIII on their surfaces. Nucleofection was used to transfect hMSCs with cDNA encoding scFv EGFRvIII fused with PDGFR or human B7-1 transmembrane domains. The expression of scFv EGFRvIII on the cell surface was assessed by FACS. A stable population of scFv EGFRvIII-expressing hMSCs was selected, based on antibiotic resistance, and enriched using FACS. We found that nucleofection allows the efficient expression of scFv EGFRvIII on the cell surface of hMSCs. hMSCs transfected with the construct encoding scFv EGFRvIII as a fusion with PDGFRtm showed scFv EGFRvIII expression in up to 86% of cells. Most importantly, human MSCs expressing scFv against EGFRvIII demonstrated enhanced binding to U87-EGFRvIII cells in vitro and significantly increased retention in human U87-EGFRvIII-expressing tumours in vivo. In summary, we provide the first conclusive evidence of genetic modification of hMSCs with a single-chain antibody against an antigen expressed on the surface of tumour cells, thereby opening up a new venue for enhanced delivery of gene therapy applications in the context of malignant brain cancer. Copyright 2009 John Wiley & Sons, Ltd.

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

PubMed

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

2016-11-01

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

Intracellular pH Response to Weak Acid Stress in Individual Vegetative Bacillus subtilis Cells.

PubMed

Pandey, Rachna; Vischer, Norbert O E; Smelt, Jan P P M; van Beilen, Johan W A; Ter Beek, Alexander; De Vos, Winnok H; Brul, Stanley; Manders, Erik M M

2016-11-01

Intracellular pH (pH i ) critically affects bacterial cell physiology. Hence, a variety of food preservation strategies are aimed at perturbing pH i homeostasis. Unfortunately, accurate pH i quantification with existing methods is suboptimal, since measurements are averages across populations of cells, not taking into account interindividual heterogeneity. Yet, physiological heterogeneity in isogenic populations is well known to be responsible for differences in growth and division kinetics of cells in response to external stressors. To assess in this context the behavior of intracellular acidity, we have developed a robust method to quantify pH i at single-cell levels in Bacillus subtilis Bacilli spoil food, cause disease, and are well known for their ability to form highly stress-resistant spores. Using an improved version of the genetically encoded ratiometric pHluorin (IpHluorin), we have quantified pH i in individual B. subtilis cells, cultured at an external pH of 6.4, in the absence or presence of weak acid stresses. In the presence of 3 mM potassium sorbate, a decrease in pH i and an increase in the generation time of growing cells were observed. Similar effects were observed when cells were stressed with 25 mM potassium acetate. Time-resolved analysis of individual bacteria in growing colonies shows that after a transient pH decrease, long-term pH evolution is highly cell dependent. The heterogeneity at the single-cell level shows the existence of subpopulations that might be more resistant and contribute to population survival. Our approach contributes to an understanding of pH i regulation in individual bacteria and may help scrutinizing effects of existing and novel food preservation strategies. This study shows how the physiological response to commonly used weak organic acid food preservatives, such as sorbic and acetic acids, can be measured at the single-cell level. These data are key to coupling often-observed single-cell heterogeneous growth behavior upon the addition of weak organic acid food preservatives. Generally, these data are gathered in the form of plate counting of samples incubated with the acids. Here, we visualize the underlying heterogeneity in cellular pH homeostasis, opening up avenues for mechanistic analyses of the heterogeneity in the weak acid stress response. Thus, microbial risk assessment can become more robust, widening the scope of use of these well-known weak organic acid food preservatives. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Single-cell genomics-based analysis of virus–host interactions in marine surface bacterioplankton

DOE PAGES

Labonté, Jessica M.; Swan, Brandon K.; Poulos, Bonnie; ...

2015-04-07

Viral infections dynamically alter the composition and metabolic potential of marine microbial communities and the evolutionary trajectories of host populations with resulting feedback on biogeochemical cycles. It is quite possible that all microbial populations in the ocean are impacted by viral infections. Our knowledge of virus–host relationships, however, has been limited to a minute fraction of cultivated host groups. Here, we utilized single-cell sequencing to obtain genomic blueprints of viruses inside or attached to individual bacterial and archaeal cells captured in their native environment, circumventing the need for host and virus cultivation. Furthermore, a combination of comparative genomics, metagenomic fragmentmore » recruitment, sequence anomalies and irregularities in sequence coverage depth and genome recovery were utilized to detect viruses and to decipher modes of virus–host interactions. Members of all three tailed phage families were identified in 20 out of 58 phylogenetically and geographically diverse single amplified genomes (SAGs) of marine bacteria and archaea. At least four phage–host interactions had the characteristics of late lytic infections, all of which were found in metabolically active cells. One virus had genetic potential for lysogeny. Our findings include first known viruses of Thaumarchaeota, Marinimicrobia, Verrucomicrobia and Gammaproteobacteria clusters SAR86 and SAR92. Viruses were also found in SAGs of Alphaproteobacteria and Bacteroidetes. A high fragment recruitment of viral metagenomic reads confirmed that most of the SAG-associated viruses are abundant in the ocean. This study demonstrates that single-cell genomics, in conjunction with sequence-based computational tools, enable in situ, cultivation-independent insights into host–virus interactions in complex microbial communities.« less

Isotachophoresis for fractionation and recovery of cytoplasmic RNA and nucleus from single cells.

PubMed

Kuriyama, Kentaro; Shintaku, Hirofumi; Santiago, Juan G

2015-07-01

There is a substantial need for simultaneous analyses of RNA and DNA from individual single cells. Such analysis provides unique evidence of cell-to-cell differences and the correlation between gene expression and genomic mutation in highly heterogeneous cell populations. We present a novel microfluidic system that leverages isotachophoresis to fractionate and isolate cytoplasmic RNA and genomic DNA (gDNA) from single cells. The system uniquely enables independent, sequence-specific analyses of these critical markers. Our system uses a microfluidic chip with a simple geometry and four end-channel electrodes, and completes the entire process in <5 min, including lysis, purification, fractionation, and delivery to DNA and RNA output reservoirs, each containing high quality and purity aliquots with no measurable cross-contamination of cytoplasmic RNA versus gDNA. We demonstrate our system with simultaneous, sequence-specific quantitation using off-chip RT-qPCR and qPCR for simultaneous cytoplasmic RNA and gDNA analyses, respectively. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Heterogeneity of spontaneous DNA replication errors in single isogenic Escherichia coli cells

PubMed Central

2018-01-01

Despite extensive knowledge of the molecular mechanisms that control mutagenesis, it is not known how spontaneous mutations are produced in cells with fully operative mutation-prevention systems. By using a mutation assay that allows visualization of DNA replication errors and stress response transcriptional reporters, we examined populations of isogenic Escherichia coli cells growing under optimal conditions without exogenous stress. We found that spontaneous DNA replication errors in proliferating cells arose more frequently in subpopulations experiencing endogenous stresses, such as problems with proteostasis, genome maintenance, and reactive oxidative species production. The presence of these subpopulations of phenotypic mutators is not expected to affect the average mutation frequency or to reduce the mean population fitness in a stable environment. However, these subpopulations can contribute to overall population adaptability in fluctuating environments by serving as a reservoir of increased genetic variability.

Self-Organizing and Stochastic Behaviors During the Regeneration of Hair Stem Cells

PubMed Central

Plikus, Maksim V.; Baker, Ruth E.; Chen, Chih-Chiang; Fare, Clyde; de la Cruz, Damon; Andl, Thomas; Maini, Philip K.; Millar, Sarah E.; Widelitz, Randall; Chuong, Cheng-Ming

2012-01-01

Stem cells cycle through active and quiescent states. Large populations of stem cells in an organ may cycle randomly or in a coordinated manner. Although stem cell cycling within single hair follicles has been studied, less is known about regenerative behavior in a hair follicle population. By combining predictive mathematical modeling with in vivo studies in mice and rabbits, we show that a follicle progresses through cycling stages by continuous integration of inputs from intrinsic follicular and extrinsic environmental signals based on universal patterning principles. Signaling from the WNT/bone morphogenetic protein activator/inhibitor pair is coopted to mediate interactions among follicles in the population. This regenerative strategy is robust and versatile because relative activator/inhibitor strengths can be modulated easily, adapting the organism to different physiological and evolutionary needs. PMID:21527712

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.

Single-cell analysis of HIV-1 transcriptional activity reveals expression of proviruses in expanded clones during ART

PubMed Central

Wiegand, Ann; Spindler, Jonathan; Hong, Feiyu F.; Shao, Wei; Cyktor, Joshua C.; Cillo, Anthony R.; Halvas, Elias K.; Coffin, John M.; Mellors, John W.; Kearney, Mary F.

2017-01-01

Little is known about the fraction of human immunodeficiency virus type 1 (HIV-1) proviruses that express unspliced viral RNA in vivo or about the levels of HIV RNA expression within single infected cells. We developed a sensitive cell-associated HIV RNA and DNA single-genome sequencing (CARD-SGS) method to investigate fractional proviral expression of HIV RNA (1.3-kb fragment of p6, protease, and reverse transcriptase) and the levels of HIV RNA in single HIV-infected cells from blood samples obtained from individuals with viremia or individuals on long-term suppressive antiretroviral therapy (ART). Spiking experiments show that the CARD-SGS method can detect a single cell expressing HIV RNA. Applying CARD-SGS to blood mononuclear cells in six samples from four HIV-infected donors (one with viremia and not on ART and three with viremia suppressed on ART) revealed that an average of 7% of proviruses (range: 2–18%) expressed HIV RNA. Levels of expression varied from one to 62 HIV RNA molecules per cell (median of 1). CARD-SGS also revealed the frequent expression of identical HIV RNA sequences across multiple single cells and across multiple time points in donors on suppressive ART consistent with constitutive expression of HIV RNA in infected cell clones. Defective proviruses were found to express HIV RNA at levels similar to those proviruses that had no obvious defects. CARD-SGS is a useful tool to characterize fractional proviral expression in single infected cells that persist despite ART and to assess the impact of experimental interventions on proviral populations and their expression. PMID:28416661

Regulation of voltage-gated potassium channels attenuates resistance of side-population cells to gefitinib in the human lung cancer cell line NCI-H460.

PubMed

Choi, Seon Young; Kim, Hang-Rae; Ryu, Pan Dong; Lee, So Yeong

2017-02-21

Side-population (SP) cells that exclude anti-cancer drugs have been found in various tumor cell lines. Moreover, SP cells have a higher proliferative potential and drug resistance than main population cells (Non-SP cells). Also, several ion channels are responsible for the drug resistance and proliferation of SP cells in cancer. To confirm the expression and function of voltage-gated potassium (Kv) channels of SP cells, these cells, as well as highly expressed ATP-binding cassette (ABC) transporters and stemness genes, were isolated from a gefitinib-resistant human lung adenocarcinoma cell line (NCI-H460), using Hoechst 33342 efflux. In the present study, we found that mRNA expression of Kv channels in SP cells was different compared to Non-SP cells, and the resistance of SP cells to gefitinib was weakened with a combination treatment of gefitinib and Kv channel blockers or a Kv7 opener, compared to single-treatment gefitinib, through inhibition of the Ras-Raf signaling pathway. The findings indicate that Kv channels in SP cells could be new targets for reducing the resistance to gefitinib.

Development of a micromanipulation method for single cell isolation of prokaryotes and its application in food safety.

PubMed

Hohnadel, Marisa; Maumy, Myriam; Chollet, Renaud

2018-01-01

For nearly a century, conventional microbiological methods have been standard practice for detecting and identifying pathogens in food. Nevertheless, the microbiological safety of food has improved and various rapid methods have been developed to overcome the limitations of conventional methods. Alternative methods are expected to detect low cell numbers, since the presence in food of even a single cell of a pathogenic organism may be infectious. With respect to low population levels, the performance of a detection method is assessed by producing serial dilutions of a pure bacterial suspension to inoculate representative food matrices with highly diluted bacterial cells (fewer than 10 CFU/ml). The accuracy of data obtained by multiple dilution techniques is not certain and does not exclude some colonies arising from clumps of cells. Micromanipulation techniques to capture and isolate single cells from environmental samples were introduced more than 40 years ago. The main limitation of the current micromanipulation technique is still the low recovery rate for the growth of a single cell in culture medium. In this study, we describe a new single cell isolation method and demonstrate that it can be used successfully to grow various types of microorganism from picked individual cells. Tests with Gram-positive and Gram-negative organisms, including cocci, rods, aerobes, anaerobes, yeasts and molds showed growth recovery rates from 60% to 100% after micromanipulation. We also highlight the use of our method to evaluate and challenge the detection limits of standard detection methods in food samples contaminated by a single cell of Salmonella enterica.

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

PubMed

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

2016-02-01

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

Culture History and Population Heterogeneity as Determinants of Bacterial Adaptation: the Adaptomics of a Single Environmental Transition

PubMed Central

Ryall, Ben; Eydallin, Gustavo

2012-01-01

Summary: Diversity in adaptive responses is common within species and populations, especially when the heterogeneity of the frequently large populations found in environments is considered. By focusing on events in a single clonal population undergoing a single transition, we discuss how environmental cues and changes in growth rate initiate a multiplicity of adaptive pathways. Adaptation is a comprehensive process, and stochastic, regulatory, epigenetic, and mutational changes can contribute to fitness and overlap in timing and frequency. We identify culture history as a major determinant of both regulatory adaptations and microevolutionary change. Population history before a transition determines heterogeneities due to errors in translation, stochastic differences in regulation, the presence of aged, damaged, cheating, or dormant cells, and variations in intracellular metabolite or regulator concentrations. It matters whether bacteria come from dense, slow-growing, stressed, or structured states. Genotypic adaptations are history dependent due to variations in mutation supply, contingency gene changes, phase variation, lateral gene transfer, and genome amplifications. Phenotypic adaptations underpin genotypic changes in situations such as stress-induced mutagenesis or prophage induction or in biofilms to give a continuum of adaptive possibilities. Evolutionary selection additionally provides diverse adaptive outcomes in a single transition and generally does not result in single fitter types. The totality of heterogeneities in an adapting population increases the chance that at least some individuals meet immediate or future challenges. However, heterogeneity complicates the adaptomics of single transitions, and we propose that subpopulations will need to be integrated into future population biology and systems biology predictions of bacterial behavior. PMID:22933562

Is central dogma a global property of cellular information flow?

PubMed Central

Piras, Vincent; Tomita, Masaru; Selvarajoo, Kumar

2012-01-01

The central dogma of molecular biology has come under scrutiny in recent years. Here, we reviewed high-throughput mRNA and protein expression data of Escherichia coli, Saccharomyces cerevisiae, and several mammalian cells. At both single cell and population scales, the statistical comparisons between the entire transcriptomes and proteomes show clear correlation structures. In contrast, the pair-wise correlations of single transcripts to proteins show nullity. These data suggest that the organizing structure guiding cellular processes is observed at omics-wide scale, and not at single molecule level. The central dogma, thus, globally emerges as an average integrated flow of cellular information. PMID:23189060

Is central dogma a global property of cellular information flow?

PubMed

Piras, Vincent; Tomita, Masaru; Selvarajoo, Kumar

2012-01-01

The central dogma of molecular biology has come under scrutiny in recent years. Here, we reviewed high-throughput mRNA and protein expression data of Escherichia coli, Saccharomyces cerevisiae, and several mammalian cells. At both single cell and population scales, the statistical comparisons between the entire transcriptomes and proteomes show clear correlation structures. In contrast, the pair-wise correlations of single transcripts to proteins show nullity. These data suggest that the organizing structure guiding cellular processes is observed at omics-wide scale, and not at single molecule level. The central dogma, thus, globally emerges as an average integrated flow of cellular information.

Multi-parameter analysis using photovoltaic cell-based optofluidic cytometer

PubMed Central

Yan, Chien-Shun; Wang, Yao-Nan

2016-01-01

A multi-parameter optofluidic cytometer based on two low-cost commercial photovoltaic cells and an avalanche photodetector is proposed. The optofluidic cytometer is fabricated on a polydimethylsiloxane (PDMS) substrate and is capable of detecting side scattered (SSC), extinction (EXT) and fluorescence (FL) signals simultaneously using a free-space light transmission technique without the need for on-chip optical waveguides. The feasibility of the proposed device is demonstrated by detecting fluorescent-labeled polystyrene beads with sizes of 3 μm, 5 μm and 10 μm, respectively, and label-free beads with a size of 7.26 μm. The detection experiments are performed using both single-bead population samples and mixed-bead population samples. The detection results obtained using the SSC/EXT, EXT/FL and SSC/FL signals are compared with those obtained using a commercial flow cytometer. It is shown that the optofluidic cytometer achieves a high detection accuracy for both single-bead population samples and mixed-bead population samples. Consequently, the proposed device provides a versatile, straightforward and low-cost solution for a wide variety of point-of-care (PoC) cytometry applications. PMID:27699122

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.

Systems biology: A tool for charting the antiviral landscape.

PubMed

Bowen, James R; Ferris, Martin T; Suthar, Mehul S

2016-06-15

The host antiviral programs that are initiated following viral infection form a dynamic and complex web of responses that we have collectively termed as "the antiviral landscape". Conventional approaches to studying antiviral responses have primarily used reductionist systems to assess the function of a single or a limited subset of molecules. Systems biology is a holistic approach that considers the entire system as a whole, rather than individual components or molecules. Systems biology based approaches facilitate an unbiased and comprehensive analysis of the antiviral landscape, while allowing for the discovery of emergent properties that are missed by conventional approaches. The antiviral landscape can be viewed as a hierarchy of complexity, beginning at the whole organism level and progressing downward to isolated tissues, populations of cells, and single cells. In this review, we will discuss how systems biology has been applied to better understand the antiviral landscape at each of these layers. At the organismal level, the Collaborative Cross is an invaluable genetic resource for assessing how genetic diversity influences the antiviral response. Whole tissue and isolated bulk cell transcriptomics serves as a critical tool for the comprehensive analysis of antiviral responses at both the tissue and cellular levels of complexity. Finally, new techniques in single cell analysis are emerging tools that will revolutionize our understanding of how individual cells within a bulk infected cell population contribute to the overall antiviral landscape. Copyright © 2016 Elsevier B.V. All rights reserved.

Modelling emergence of oscillations in communicating bacteria: a structured approach from one to many cells

PubMed Central

Mina, Petros; di Bernardo, Mario; Savery, Nigel J.; Tsaneva-Atanasova, Krasimira

2013-01-01

Population-level measurements of phenotypic behaviour in biological systems may not necessarily reflect individual cell behaviour. To assess qualitative changes in the behaviour of a single cell, when alone and when part of a community, we developed an agent-based model describing the metabolic states of a population of quorum-coupled cells. The modelling is motivated by published experimental work of a synthetic genetic regulatory network (GRN) used in Escherichia coli cells that exhibit oscillatory behaviour across the population. To decipher the mechanisms underlying oscillations in the system, we investigate the behaviour of the model via numerical simulation and bifurcation analysis. In particular, we study the effect of an increase in population size as well as the spatio-temporal behaviour of the model. Our results demonstrate that oscillations are possible only in the presence of a high concentration of the coupling chemical and are due to a time scale separation in key regulatory components of the system. The model suggests that the population establishes oscillatory behaviour as the system's preferred stable state. This is achieved via an effective increase in coupling across the population. We conclude that population effects in GRN design need to be taken into consideration and be part of the design process. This is important in planning intervention strategies or designing specific cell behaviours. PMID:23135248

Modelling emergence of oscillations in communicating bacteria: a structured approach from one to many cells.

PubMed

Mina, Petros; di Bernardo, Mario; Savery, Nigel J; Tsaneva-Atanasova, Krasimira

2013-01-06

Population-level measurements of phenotypic behaviour in biological systems may not necessarily reflect individual cell behaviour. To assess qualitative changes in the behaviour of a single cell, when alone and when part of a community, we developed an agent-based model describing the metabolic states of a population of quorum-coupled cells. The modelling is motivated by published experimental work of a synthetic genetic regulatory network (GRN) used in Escherichia coli cells that exhibit oscillatory behaviour across the population. To decipher the mechanisms underlying oscillations in the system, we investigate the behaviour of the model via numerical simulation and bifurcation analysis. In particular, we study the effect of an increase in population size as well as the spatio-temporal behaviour of the model. Our results demonstrate that oscillations are possible only in the presence of a high concentration of the coupling chemical and are due to a time scale separation in key regulatory components of the system. The model suggests that the population establishes oscillatory behaviour as the system's preferred stable state. This is achieved via an effective increase in coupling across the population. We conclude that population effects in GRN design need to be taken into consideration and be part of the design process. This is important in planning intervention strategies or designing specific cell behaviours.

Ca2+ and MgATP2- dependence of shortening in skinned single smooth muscle cells.

PubMed

Warshaw, D M; McBride, W J; Hubbard, M S

1987-04-01

Most studies of skinned smooth muscle have been performed in whole tissue preparations. In this study, we report the development of a chemically skinned single smooth muscle cell preparation from the toad, Bufo marinus, stomach. Isolated smooth muscle cells were skinned using saponin. The effect of various ionic environments (i.e., changing free Ca2+ and MgATP2-) on skinned cell contractile response was assessed by measuring cell lengths from populations of cells using a computer-assisted length-measuring system. Comparison of cell length histograms were used to determine the extent of cell shortening in response to a given ionic perturbation. Once skinned, the single cells shortened with a sensitivity to free calcium (ED50 = 1.5 microM Ca2+) that was three orders of magnitude lower than potassium depolarized cells (ED50 = 1.5 mM Ca2+). In addition to the calcium sensitivity, the effect of free MgATP2- on the extent of cell shortening was investigated. The extent of cell shortening was dependent on free MgATP2- with the maximum shortening response occurring at MgATP2- greater than 1 mM.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-02-28

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

The Case for Absolute Ligand Discrimination: Modeling Information Processing and Decision by Immune T Cells

NASA Astrophysics Data System (ADS)

François, Paul; Altan-Bonnet, Grégoire

2016-03-01

Some cells have to take decision based on the quality of surroundings ligands, almost irrespective of their quantity, a problem we name "absolute discrimination". An example of absolute discrimination is recognition of not-self by immune T Cells. We show how the problem of absolute discrimination can be solved by a process called "adaptive sorting". We review several implementations of adaptive sorting, as well as its generic properties such as antagonism. We show how kinetic proofreading with negative feedback implement an approximate version of adaptive sorting in the immune context. Finally, we revisit the decision problem at the cell population level, showing how phenotypic variability and feedbacks between population and single cells are crucial for proper decision.

Urokinase production by electrophoretically separated cultured human embryonic kidney cells

NASA Technical Reports Server (NTRS)

Kunze, M. E.; Plank, L. D.; Giranda, V.; Sedor, K.; Todd, P. W.

1985-01-01

Urokinase is a plasminogen activator found in urine. Relatively pure preparations have been tested in Europe, Japan and the United States for the treatment of deep vein thrombosis and other dangerous blood clots. Human embryonic kidney cell cultures have been found to produce urokinase at much higher concentrations, but less than 5% of the cells in typical cultures are producers. Since human diploid cells become senescent in culture the selection of clones derived from single cells will not provide enough material to be useful, so a bulk purification method is needed for the isolation of urokinase producing cell populations. Preparative cell electrophoresis was chosen as the method, since evidence exists that human embryonic cell cultures are richly heterogeneous with respect to electrophoretic mobility, and preliminary electrophoretic separations on the Apollo-Soyuz space flight produced cell populations that were rich in urokinase production. Similarly, erythropoietin is useful in the treatment of certain anemias and is a kidney cell duct, and electrophoretically enriched cell populations producing this product have been reported. Thus, there is a clear need for diploid human cells that produce these products, and there is evidence that such cells should be separable by free-flow cell electrophoresis.

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis

PubMed Central

Ji, Zhicheng; Ji, Hongkai

2016-01-01

When analyzing single-cell RNA-seq data, constructing a pseudo-temporal path to order cells based on the gradual transition of their transcriptomes is a useful way to study gene expression dynamics in a heterogeneous cell population. Currently, a limited number of computational tools are available for this task, and quantitative methods for comparing different tools are lacking. Tools for Single Cell Analysis (TSCAN) is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis. TSCAN uses a cluster-based minimum spanning tree (MST) approach to order cells. Cells are first grouped into clusters and an MST is then constructed to connect cluster centers. Pseudo-time is obtained by projecting each cell onto the tree, and the ordered sequence of cells can be used to study dynamic changes of gene expression along the pseudo-time. Clustering cells before MST construction reduces the complexity of the tree space. This often leads to improved cell ordering. It also allows users to conveniently adjust the ordering based on prior knowledge. TSCAN has a graphical user interface (GUI) to support data visualization and user interaction. Furthermore, quantitative measures are developed to objectively evaluate and compare different pseudo-time reconstruction methods. TSCAN is available at https://github.com/zji90/TSCAN and as a Bioconductor package. PMID:27179027

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis.

PubMed

Ji, Zhicheng; Ji, Hongkai

2016-07-27

When analyzing single-cell RNA-seq data, constructing a pseudo-temporal path to order cells based on the gradual transition of their transcriptomes is a useful way to study gene expression dynamics in a heterogeneous cell population. Currently, a limited number of computational tools are available for this task, and quantitative methods for comparing different tools are lacking. Tools for Single Cell Analysis (TSCAN) is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis. TSCAN uses a cluster-based minimum spanning tree (MST) approach to order cells. Cells are first grouped into clusters and an MST is then constructed to connect cluster centers. Pseudo-time is obtained by projecting each cell onto the tree, and the ordered sequence of cells can be used to study dynamic changes of gene expression along the pseudo-time. Clustering cells before MST construction reduces the complexity of the tree space. This often leads to improved cell ordering. It also allows users to conveniently adjust the ordering based on prior knowledge. TSCAN has a graphical user interface (GUI) to support data visualization and user interaction. Furthermore, quantitative measures are developed to objectively evaluate and compare different pseudo-time reconstruction methods. TSCAN is available at https://github.com/zji90/TSCAN and as a Bioconductor package. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Novel single-cell functional analysis of red blood cells using laser tweezers Raman spectroscopy: application for sickle cell disease.

PubMed

Liu, Rui; Mao, Ziliang; Matthews, Dennis L; Li, Chin-Shang; Chan, James W; Satake, Noriko

2013-07-01

Laser tweezers Raman spectroscopy was used to characterize the oxygenation response of single normal adult, sickle, and cord blood red blood cells (RBCs) to an applied mechanical force. Individual cells were subjected to different forces by varying the laser power of a single-beam optical trap, and the intensities of several oxygenation-specific Raman spectral peaks were monitored to determine the oxygenation state of the cells. For all three cell types, an increase in laser power (or mechanical force) induced a greater deoxygenation of the cell. However, sickle RBCs deoxygenated more readily than normal RBCs when subjected to the same optical forces. Conversely, cord blood RBCs were able to maintain their oxygenation better than normal RBCs. These results suggest that differences in the chemical or mechanical properties of fetal, normal, and sickle cells affect the degree to which applied mechanical forces can deoxygenate the cell. Populations of normal, sickle, and cord RBCs were identified and discriminated based on this mechanochemical phenomenon. This study demonstrates the potential application of laser tweezers Raman spectroscopy as a single-cell, label-free analytical tool to characterize the functional (e.g., mechanical deformability, oxygen binding) properties of normal and diseased RBCs. Copyright © 2013 ISEH - Society for Hematology and Stem Cells. Published by Elsevier Inc. All rights reserved.

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.

Differentiated cell behavior: a multiscale approach using measure theory.

PubMed

Colombi, Annachiara; Scianna, Marco; Tosin, Andrea

2015-11-01

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

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

PubMed

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

2015-01-01

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

Colourful death: six-parameter classification of cell death by flow cytometry--dead cells tell tales.

PubMed

Munoz, Luis E; Maueröder, Christian; Chaurio, Ricardo; Berens, Christian; Herrmann, Martin; Janko, Christina

2013-08-01

The response of the immune system against dying and dead cells strongly depends on the cell death phenotype. Beside other forms of cell death, two clearly distinct populations, early apoptotic and secondary necrotic cells, have been shown to induce anti-inflammation/tolerance and inflammation/immune priming, respectively. Cytofluorometry is a powerful technique to detect morphological and phenotypical changes occurring during cell death. Here, we describe a new technique using AnnexinA5, propidiumiodide, DiIC1(5) and Hoechst 33342 to sub-classify populations of apoptotic and/or necrotic cells. The method allows the fast and reliable identification of several different phases and pathways of cell death by analysing the following cell death associated changes in a single tube: cellular granularity and shrinkage, phosphatidylserine exposure, ion selectivity of the plasma membrane, mitochondrial membrane potential, and DNA content. The clear characterisation of cell death is of major importance for instance in immunization studies, in experimental therapeutic settings, and in the exploration of cell-death associated diseases. It also enables the analysis of immunological properties of distinct populations of dying cells and the pathways involved in this process.

Adaptability of non-genetic diversity in bacterial chemotaxis

PubMed Central

Frankel, Nicholas W; Pontius, William; Dufour, Yann S; Long, Junjiajia; Hernandez-Nunez, Luis; Emonet, Thierry

2014-01-01

Bacterial chemotaxis systems are as diverse as the environments that bacteria inhabit, but how much environmental variation can cells tolerate with a single system? Diversification of a single chemotaxis system could serve as an alternative, or even evolutionary stepping-stone, to switching between multiple systems. We hypothesized that mutations in gene regulation could lead to heritable control of chemotactic diversity. By simulating foraging and colonization of E. coli using a single-cell chemotaxis model, we found that different environments selected for different behaviors. The resulting trade-offs show that populations facing diverse environments would ideally diversify behaviors when time for navigation is limited. We show that advantageous diversity can arise from changes in the distribution of protein levels among individuals, which could occur through mutations in gene regulation. We propose experiments to test our prediction that chemotactic diversity in a clonal population could be a selectable trait that enables adaptation to environmental variability. DOI: http://dx.doi.org/10.7554/eLife.03526.001 PMID:25279698

Mex3a marks slow-proliferating multilineage progenitors of the intestinal epithelium

PubMed Central

Barriga, Francisco M.; Montagni, Elisa; Mana, Miyeko; Guillaumet-Adkins, Amy; Hernando-Momblona, Xavier; Sevillano, Marta; Rodriguez-Esteban, Gustavo; Mendez-Lago, Maria; Buczacki, Simon J. A.; Gut, Ivo; Gut, Marta; Winton, Douglas J.; Yilmaz, Omer; Stephan-Otto, Camille; Hein, Holger; Batlle, Eduard

2017-01-01

SUMMARY The intestinal epithelium is continuously regenerated by highly proliferative Lgr5+ intestinal stem cells (ISCs). The existence of a population of quiescent ISCs has been suggested yet its identity and features remain controversial. Here we describe that the expression of the RNA-binding protein Mex3a labels a subpopulation of Lgr5+ cells that divide less frequently and contribute to regenerate all intestinal lineages with slow kinetics. Single cell transcriptomic analysis revealed two classes of Lgr5-high cells, one of them defined by the Mex3a-expression program and by low levels of proliferation genes. Lineage tracing experiments show that large fraction of Mex3a+ cell population is continuously recalled into the rapidly dividing self-renewing ISC pool in homeostatic conditions. Chemotherapy and radiation target preferentially rapidly dividing Lgr5+ cells but spare the Mex3a-high/Lgr5+ population, which helps sustain the renewal of the intestinal epithelium during treatment. PMID:28285904

Quantifying Stochastic Noise in Cultured Circadian Reporter Cells

DOE PAGES

John, Peter C.; Doyle, III, Francis J.

2015-11-20

We report that stochastic noise at the cellular level has been shown to play a fundamental role in circadian oscillations, influencing how groups of cells entrain to external cues and likely serving as the mechanism by which cell-autonomous rhythms are generated. Despite this importance, few studies have investigated how clock perturbations affect stochastic noise—even as increasing numbers of high-throughput screens categorize how gene knockdowns or small molecules can change clock period and amplitude. This absence is likely due to the difficulty associated with measuring cell-autonomous stochastic noise directly, which currently requires the careful collection and processing of single-cell data. Inmore » this study, we show that the damping rate of population-level bioluminescence recordings can serve as an accurate measure of overall stochastic noise, and one that can be applied to future and existing high-throughput circadian screens. Using cell-autonomous fibroblast data, we first show directly that higher noise at the single-cell results in faster damping at the population level. Next, we show that the damping rate of cultured cells can be changed in a dose-dependent fashion by small molecule modulators, and confirm that such a change can be explained by single-cell noise using a mathematical model. We further demonstrate the insights that can be gained by applying our method to a genome-wide siRNA screen, revealing that stochastic noise is altered independently from period, amplitude, and phase. Finally, we hypothesize that the unperturbed clock is highly optimized for robust rhythms, as very few gene perturbations are capable of simultaneously increasing amplitude and lowering stochastic noise. Ultimately, this study demonstrates the importance of considering the effect of circadian perturbations on stochastic noise, particularly with regard to the development of small-molecule circadian therapeutics.« less

Through the Looking Glass: Time-lapse Microscopy and Longitudinal Tracking of Single Cells to Study Anti-cancer Therapeutics

PubMed Central

Burke, Russell T.; Orth, James D.

2016-01-01

The response of single cells to anti-cancer drugs contributes significantly in determining the population response, and therefore is a major contributing factor in the overall outcome. Immunoblotting, flow cytometry and fixed cell experiments are often used to study how cells respond to anti-cancer drugs. These methods are important, but they have several shortcomings. Variability in drug responses between cancer and normal cells, and between cells of different cancer origin, and transient and rare responses are difficult to understand using population averaging assays and without being able to directly track and analyze them longitudinally. The microscope is particularly well suited to image live cells. Advancements in technology enable us to routinely image cells at a resolution that enables not only cell tracking, but also the observation of a variety of cellular responses. We describe an approach in detail that allows for the continuous time-lapse imaging of cells during the drug response for essentially as long as desired, typically up to 96 hr. Using variations of the approach, cells can be monitored for weeks. With the employment of genetically encoded fluorescent biosensors numerous processes, pathways and responses can be followed. We show examples that include tracking and quantification of cell growth and cell cycle progression, chromosome dynamics, DNA damage, and cell death. We also discuss variations of the technique and its flexibility, and highlight some common pitfalls. PMID:27213923

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

In Vivo Multiphoton Microscopy for Investigating Biomechanical Properties of Human Skin.

PubMed

Liang, Xing; Graf, Benedikt W; Boppart, Stephen A

2011-06-01

The biomechanical properties of living cells depend on their molecular building blocks, and are important for maintaining structure and function in cells, the extracellular matrix, and tissues. These biomechanical properties and forces also shape and modify the cellular and extracellular structures under stress. While many studies have investigated the biomechanics of single cells or small populations of cells in culture, or the properties of organs and tissues, few studies have investigated the biomechanics of complex cell populations in vivo. With the use of advanced multiphoton microscopy to visualize in vivo cell populations in human skin, the biomechanical properties are investigated in a depth-dependent manner in the stratum corneum and epidermis using quasi-static mechanical deformations. A 2D elastic registration algorithm was used to analyze the images before and after deformation to determine displacements in different skin layers. In this feasibility study, the images and results from one human subject demonstrate the potential of the technique for revealing differences in elastic properties between the stratum corneum and the rest of the epidermis. This interrogational imaging methodology has the potential to enable a wide range of investigations for understanding how the biomechanical properties of in vivo cell populations influence function in health and disease.

Using measures of single-cell physiology and physiological state to understand organismic aging.

PubMed

Mendenhall, Alexander; Driscoll, Monica; Brent, Roger

2016-02-01

Genetically identical organisms in homogeneous environments have different lifespans and healthspans. These differences are often attributed to stochastic events, such as mutations and 'epimutations', changes in DNA methylation and chromatin that change gene function and expression. But work in the last 10 years has revealed differences in lifespan- and health-related phenotypes that are not caused by lasting changes in DNA or identified by modifications to DNA or chromatin. This work has demonstrated persistent differences in single-cell and whole-organism physiological states operationally defined by values of reporter gene signals in living cells. While some single-cell states, for example, responses to oxygen deprivation, were defined previously, others, such as a generally heightened ability to make proteins, were, revealed by direct experiment only recently, and are not well understood. Here, we review technical progress that promises to greatly increase the number of these measurable single-cell physiological variables and measureable states. We discuss concepts that facilitate use of single-cell measurements to provide insight into physiological states and state transitions. We assert that researchers will use this information to relate cell level physiological readouts to whole-organism outcomes, to stratify aging populations into groups based on different physiologies, to define biomarkers predictive of outcomes, and to shed light on the molecular processes that bring about different individual physiologies. For these reasons, quantitative study of single-cell physiological variables and state transitions should provide a valuable complement to genetic and molecular explanations of how organisms age. © 2015 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Tirilazad mesylate protects stored erythrocytes against osmotic fragility.

PubMed

Epps, D E; Knechtel, T J; Bacznskyj, O; Decker, D; Guido, D M; Buxser, S E; Mathews, W R; Buffenbarger, S L; Lutzke, B S; McCall, J M

1994-12-01

The hypoosmotic lysis curve of freshly collected human erythrocytes is consistent with a single Gaussian error function with a mean of 46.5 +/- 0.25 mM NaCl and a standard deviation of 5.0 +/- 0.4 mM NaCl. After extended storage of RBCs under standard blood bank conditions the lysis curve conforms to the sum of two error functions instead of a possible shift in the mean and a broadening of a single error function. Thus, two distinct sub-populations with different fragilities are present instead of a single, broadly distributed population. One population is identical to the freshly collected erythrocytes, whereas the other population consists of osmotically fragile cells. The rate of generation of the new, osmotically fragile, population of cells was used to probe the hypothesis that lipid peroxidation is responsible for the induction of membrane fragility. If it is so, then the antioxidant, tirilazad mesylate (U-74,006f), should protect against this degradation of stored erythrocytes. We found that tirilazad mesylate, at 17 microM (1.5 mol% with respect to membrane lecithin), retards significantly the formation of the osmotically fragile RBCs. Concomitantly, the concentration of free hemoglobin which accumulates during storage is markedly reduced by the drug. Since the presence of the drug also decreases the amount of F2-isoprostanes formed during the storage period, an antioxidant mechanism must be operative. These results demonstrate that tirilazad mesylate significantly decreases the number of fragile erythrocytes formed during storage in the blood bank.

Single cell genomic study of dehalogenating Chloroflexi from deep sea sediments of Peruvian Margin

NASA Astrophysics Data System (ADS)

Spormann, A.; Kaster, A.; Meyer-Blackwell, K.; Biddle, J.

2012-12-01

Dehalogenating Chloroflexi, such as Dehalococcoidites (Dhc), are members of the rare biosphere of deep sea sediments but were originally discovered as the key microbes mediating reductive dehalogenation of the prevalent groundwater contaminants tetrachloroethene and trichloroethene to ethene. Dhc are slow growing, highly niche adapted microbes that are specialized to organohalide respiration as the sole mode of energy conservation. These strictly anaerobic microbes depend on a supporting microbial community to mitigate electron donor and cofactor requirements among other factors. Molecular and genomic studies on the key enzymes for energy conservation, reductive dehalogenases, have provided evidence for rapid adaptive evolution in terrestrial environments. However, the metabolic life style of Dhc in the absence of anthropogenic contaminants, such as in pristine deep sea sediments, is still unknown. In order to provide fundamental insights into life style, genomic population structure and evolution of Dhc, we analyzed a non-contaminated deep sea sediment sample of the Peru Margin 1230 site collected 6 mbf by a metagenomic and single cell genomic. We present for the first time single cell genomic data on dehalogenating Chloroflexi, a significant microbial population in the poorly understood oligotrophic marine sub-surface environments.

Single cell genomic study of dehalogenating Chloroflexi in deep sea sediments of Peru Margin 1230

NASA Astrophysics Data System (ADS)

Kaster, A.; Meyer-Blackwell, K.; Biddle, J.; Spormann, A.

2012-12-01

Dehalogenating Chloroflexi, such as Dehalococcoidites (Dhc), are members of the rare biosphere of deep sea sediments but were originally discovered as the key microbes mediating reductive dehalogenation of the prevalent groundwater contaminants tetrachloroethene and trichloroethene to ethene. Dhc are slow growing, highly niche adapted microbes that are specialized to organohalide respiration as the sole mode of energy conservation. They are strictly anaerobic microbes that depend on a supporting microbial community for electron donor and cofactor requirements among other factors. Molecular and genomic studies on the key enzymes for energy conservation, reductive dehalogenases, have provided evidence for rapid adaptive evolution in terrestrial environments. However, the metabolic life style of Dhc in the absence of anthropogenic contaminants, such as in pristine deep sea sediments, is still unknown. In order to provide fundamental insights into life style, genomic population structure and evolution of Dhc, we analyzed a non-contaminated deep sea sediment sample of the Peru Margin 1230 site collected 6 mbsf by a metagenomic and single cell genomic approach. We present for the first time single cell genomic data on dehalogenating Chloroflexi, a significant microbial population in the poorly understood oligotrophic marine sub-surface environment.

Pharmacological profiles of acute myeloid leukemia treatments in patient samples by automated flow cytometry: a bridge to individualized medicine.

PubMed

Bennett, Teresa A; Montesinos, Pau; Moscardo, Federico; Martinez-Cuadron, David; Martinez, Joaquin; Sierra, Jorge; García, Raimundo; de Oteyza, Jaime Perez; Fernandez, Pascual; Serrano, Josefina; Fernandez, Angeles; Herrera, Pilar; Gonzalez, Ataulfo; Bethancourt, Concepcion; Rodriguez-Macias, Gabriela; Alonso, Arancha; Vera, Juan A; Navas, Begoña; Lavilla, Esperanza; Lopez, Juan A; Jimenez, Santiago; Simiele, Adriana; Vidriales, Belen; Gonzalez, Bernardo J; Burgaleta, Carmen; Hernandez Rivas, Jose A; Mascuñano, Raul Cordoba; Bautista, Guiomar; Perez Simon, Jose A; Fuente, Adolfo de la; Rayón, Consolación; Troconiz, Iñaki F; Janda, Alvaro; Bosanquet, Andrew G; Hernandez-Campo, Pilar; Primo, Daniel; Lopez, Rocio; Liebana, Belen; Rojas, Jose L; Gorrochategui, Julian; Sanz, Miguel A; Ballesteros, Joan

2014-08-01

We have evaluated the ex vivo pharmacology of single drugs and drug combinations in malignant cells of bone marrow samples from 125 patients with acute myeloid leukemia using a novel automated flow cytometry-based platform (ExviTech). We have improved previous ex vivo drug testing with 4 innovations: identifying individual leukemic cells, using intact whole blood during the incubation, using an automated platform that escalates reliably data, and performing analyses pharmacodynamic population models. Samples were sent from 24 hospitals to a central laboratory and incubated for 48 hours in whole blood, after which drug activity was measured in terms of depletion of leukemic cells. The sensitivity of single drugs is assessed for standard efficacy (EMAX) and potency (EC50) variables, ranked as percentiles within the population. The sensitivity of drug-combination treatments is assessed for the synergism achieved in each patient sample. We found a large variability among patient samples in the dose-response curves to a single drug or combination treatment. We hypothesize that the use of the individual patient ex vivo pharmacological profiles may help to guide a personalized treatment selection. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Population-expression models of immune response

NASA Astrophysics Data System (ADS)

Stromberg, Sean P.; Antia, Rustom; Nemenman, Ilya

2013-06-01

The immune response to a pathogen has two basic features. The first is the expansion of a few pathogen-specific cells to form a population large enough to control the pathogen. The second is the process of differentiation of cells from an initial naive phenotype to an effector phenotype which controls the pathogen, and subsequently to a memory phenotype that is maintained and responsible for long-term protection. The expansion and the differentiation have been considered largely independently. Changes in cell populations are typically described using ecologically based ordinary differential equation models. In contrast, differentiation of single cells is studied within systems biology and is frequently modeled by considering changes in gene and protein expression in individual cells. Recent advances in experimental systems biology make available for the first time data to allow the coupling of population and high dimensional expression data of immune cells during infections. Here we describe and develop population-expression models which integrate these two processes into systems biology on the multicellular level. When translated into mathematical equations, these models result in non-conservative, non-local advection-diffusion equations. We describe situations where the population-expression approach can make correct inference from data while previous modeling approaches based on common simplifying assumptions would fail. We also explore how model reduction techniques can be used to build population-expression models, minimizing the complexity of the model while keeping the essential features of the system. While we consider problems in immunology in this paper, we expect population-expression models to be more broadly applicable.

Single-Cell RNA-Seq of Mouse Dopaminergic Neurons Informs Candidate Gene Selection for Sporadic Parkinson Disease.

PubMed

Hook, Paul W; McClymont, Sarah A; Cannon, Gabrielle H; Law, William D; Morton, A Jennifer; Goff, Loyal A; McCallion, Andrew S

2018-03-01

Genetic variation modulating risk of sporadic Parkinson disease (PD) has been primarily explored through genome-wide association studies (GWASs). However, like many other common genetic diseases, the impacted genes remain largely unknown. Here, we used single-cell RNA-seq to characterize dopaminergic (DA) neuron populations in the mouse brain at embryonic and early postnatal time points. These data facilitated unbiased identification of DA neuron subpopulations through their unique transcriptional profiles, including a postnatal neuroblast population and substantia nigra (SN) DA neurons. We use these population-specific data to develop a scoring system to prioritize candidate genes in all 49 GWAS intervals implicated in PD risk, including genes with known PD associations and many with extensive supporting literature. As proof of principle, we confirm that the nigrostriatal pathway is compromised in Cplx1-null mice. Ultimately, this systematic approach establishes biologically pertinent candidates and testable hypotheses for sporadic PD, informing a new era of PD genetic research. Copyright © 2018 American Society of Human Genetics. All rights reserved.

Experimental study on the interspecific interactions between the two bloom-forming algal species and the rotifer Brachionus plicatilis

NASA Astrophysics Data System (ADS)

Xie, Zhihao; Xiao, Hui; Tang, Xuexi; Cai, Hengjiang

2009-06-01

The interspecific interactions between the rotifer Brachionus plicatilis and two harmful algal blooms (HAB) species were investigated experimentally by single culture method. B. plicatilis population and the growth of the two algae were compared at different algal cell densities. The results demonstrated that the B. plicatilis obtained sufficient nutrition from Prorocentrum donghaiense to support net population increase. With exposure to 2.5×104 cells mL-1 of P. donghaiense, the number of B. plicatilis increased faster than it did when exposed to other four algal densities (5, 10, 15 and 20 ×104 cells mL-1), and the increase rate of B. plicatilis population ( r) at this algal density was 0.104 ± 0.015 rd-1. Cell densities of P. donghaiense decreased due to the grazing of B. plicatilis. In contrast, Heterosigma akashiwo had an adverse effect on B. plicatilis population and its growth was largely unaffected by rotifer grazing. In this case, B. plicatilis population decreased and H. akashiwo grew at a rate similar to that of the control.

Optical fiber-based sensors: application to chemical biology.

PubMed

Brogan, Kathryn L; Walt, David R

2005-10-01

Optical fibers have been used to develop sensors based on nucleic acids and cells. Sensors employing DNA probes have been developed for various genomics applications and microbial pathogen detection. Live cell-based sensors have enabled the monitoring of environmental toxins, and have been used for fundamental studies on populations of individual cells. Both single-core optical fiber sensors and optical fiber sensor arrays have been used for sensing based on nucleic acids and live cells.

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

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2016-01-01

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

[Effect of penicillin and the habitat medium in the body of bacterial carriers on the intercellular bonds in populations of the meningococcus and pertussis microbe].

PubMed

Vysotskiĭ, V V; Smirnova-Mutusheva, M A; Efimova, O G; Bakulina, N A

1983-04-01

The relationship of the bacterial cells in populations and their adhesion activity is at present one of the research priorities in microbiological studies. The stimulating effect of penicillin on the development of morphologically different intercellular bonds (IB) in populations of the pertussis causative agent and first of all derivatives or evaginates of the cell wall membranes was observed. Morphologically similar systems and polytubular IB were detected in populations of meningococcal strains isolated from carriers having no signs of the disease. Correlation between the after-effect of penicillin and the presence of the causative agent in bacterial carriers was shown. Unknown systems of interlacing tubular structures not directly bound with the cells, the walls of which were single contour membranes were determined in the meningococcal populations treated with penicillin. IB were observed in the population in the form of transpopulation cords. Morphologically different IB playing the role of specialized organelles might be considered as factors of the functional unity of the bacterial population as a multicellular system.

Evidence of two populations of GABA(A) receptors in cerebellar granule cells in culture: different desensitization kinetics, pharmacology, serine/threonine kinase sensitivity, and localization.

PubMed

Robello, M; Amico, C; Cupello, A

1999-12-20

GABA(A) receptors of rat cerebellar granule cells in culture have been studied by the whole cell patch clamp technique. The biphasic desensitization kinetic observed could be due either to different desensitization mechanisms of a single receptor population or to different receptor populations. The overall data indicate that the latter hypothesis is most probably the correct one. In fact, the fast desensitizing component was selectively potentiated by a benzodiazepine agonist and preferentially down-regulated by activation of the protein serine/threonine kinases A and G, as a consequence of the latter characteristic that receptor population was preferentially down-regulated by previous activation of N-methyl-d-aspartate glutamate receptors, via production of nitric oxide and PKG activation, most probably in dendrites. The other population is benzodiazepine insensitive and not influenced by activation of PKA or PKG. This slowly desensitizing population may correspond to the extrasynaptic delta subunit containing GABA(A) receptors described by other authors. Instead, the rapidly desensitizing population appears to represent dendritic synaptic GABA(A) receptors. Copyright 1999 Academic Press.

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

PubMed

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

2016-09-06

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

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

PubMed Central

2014-01-01

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

Current Progresses of Single Cell DNA Sequencing in Breast Cancer Research.

PubMed

Liu, Jianlin; Adhav, Ragini; Xu, Xiaoling

2017-01-01

Breast cancers display striking genetic and phenotypic diversities. To date, several hypotheses are raised to explain and understand the heterogeneity, including theories for cancer stem cell (CSC) and clonal evolution. According to the CSC theory, the most tumorigenic cells, while maintaining themselves through symmetric division, divide asymmetrically to generate non-CSCs with less tumorigenic and metastatic potential, although they can also dedifferentiate back to CSCs. Clonal evolution theory recapitulates that a tumor initially arises from a single cell, which then undergoes clonal expansion to a population of cancer cells. During tumorigenesis and evolution process, cancer cells undergo different degrees of genetic instability and consequently obtain varied genetic aberrations. Yet the heterogeneity in breast cancers is very complex, poorly understood and subjected to further investigation. In recent years, single cell sequencing (SCS) technology developed rapidly, providing a powerful new way to better understand the heterogeneity, which may lay foundations to some new strategies for breast cancer therapies. In this review, we will summarize development of SCS technologies and recent advances of SCS in breast cancer.

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

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

PubMed Central

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

2000-01-01

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

Single-cell paired-end genome sequencing reveals structural variation per cell cycle

PubMed Central

Voet, Thierry; Kumar, Parveen; Van Loo, Peter; Cooke, Susanna L.; Marshall, John; Lin, Meng-Lay; Zamani Esteki, Masoud; Van der Aa, Niels; Mateiu, Ligia; McBride, David J.; Bignell, Graham R.; McLaren, Stuart; Teague, Jon; Butler, Adam; Raine, Keiran; Stebbings, Lucy A.; Quail, Michael A.; D’Hooghe, Thomas; Moreau, Yves; Futreal, P. Andrew; Stratton, Michael R.; Vermeesch, Joris R.; Campbell, Peter J.

2013-01-01

The nature and pace of genome mutation is largely unknown. Because standard methods sequence DNA from populations of cells, the genetic composition of individual cells is lost, de novo mutations in cells are concealed within the bulk signal and per cell cycle mutation rates and mechanisms remain elusive. Although single-cell genome analyses could resolve these problems, such analyses are error-prone because of whole-genome amplification (WGA) artefacts and are limited in the types of DNA mutation that can be discerned. We developed methods for paired-end sequence analysis of single-cell WGA products that enable (i) detecting multiple classes of DNA mutation, (ii) distinguishing DNA copy number changes from allelic WGA-amplification artefacts by the discovery of matching aberrantly mapping read pairs among the surfeit of paired-end WGA and mapping artefacts and (iii) delineating the break points and architecture of structural variants. By applying the methods, we capture DNA copy number changes acquired over one cell cycle in breast cancer cells and in blastomeres derived from a human zygote after in vitro fertilization. Furthermore, we were able to discover and fine-map a heritable inter-chromosomal rearrangement t(1;16)(p36;p12) by sequencing a single blastomere. The methods will expedite applications in basic genome research and provide a stepping stone to novel approaches for clinical genetic diagnosis. PMID:23630320

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

CRISPR-UMI: single-cell lineage tracing of pooled CRISPR-Cas9 screens.

PubMed

Michlits, Georg; Hubmann, Maria; Wu, Szu-Hsien; Vainorius, Gintautas; Budusan, Elena; Zhuk, Sergei; Burkard, Thomas R; Novatchkova, Maria; Aichinger, Martin; Lu, Yiqing; Reece-Hoyes, John; Nitsch, Roberto; Schramek, Daniel; Hoepfner, Dominic; Elling, Ulrich

2017-12-01

Pooled CRISPR screens are a powerful tool for assessments of gene function. However, conventional analysis is based exclusively on the relative abundance of integrated single guide RNAs (sgRNAs) between populations, which does not discern distinct phenotypes and editing outcomes generated by identical sgRNAs. Here we present CRISPR-UMI, a single-cell lineage-tracing methodology for pooled screening to account for cell heterogeneity. We generated complex sgRNA libraries with unique molecular identifiers (UMIs) that allowed for screening of clonally expanded, individually tagged cells. A proof-of-principle CRISPR-UMI negative-selection screen provided increased sensitivity and robustness compared with conventional analysis by accounting for underlying cellular and editing-outcome heterogeneity and detection of outlier clones. Furthermore, a CRISPR-UMI positive-selection screen uncovered new roadblocks in reprogramming mouse embryonic fibroblasts as pluripotent stem cells, distinguishing reprogramming frequency and speed (i.e., effect size and probability). CRISPR-UMI boosts the predictive power, sensitivity, and information content of pooled CRISPR screens.

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

Imaging trace element distributions in single organelles and subcellular features

DOE PAGES

Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; ...

2016-02-25

The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro-and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cd (whichmore » some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators. In conclusion, it could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies.« less

A survey of human brain transcriptome diversity at the single cell level.

PubMed

Darmanis, Spyros; Sloan, Steven A; Zhang, Ye; Enge, Martin; Caneda, Christine; Shuer, Lawrence M; Hayden Gephart, Melanie G; Barres, Ben A; Quake, Stephen R

2015-06-09

The human brain is a tissue of vast complexity in terms of the cell types it comprises. Conventional approaches to classifying cell types in the human brain at single cell resolution have been limited to exploring relatively few markers and therefore have provided a limited molecular characterization of any given cell type. We used single cell RNA sequencing on 466 cells to capture the cellular complexity of the adult and fetal human brain at a whole transcriptome level. Healthy adult temporal lobe tissue was obtained during surgical procedures where otherwise normal tissue was removed to gain access to deeper hippocampal pathology in patients with medical refractory seizures. We were able to classify individual cells into all of the major neuronal, glial, and vascular cell types in the brain. We were able to divide neurons into individual communities and show that these communities preserve the categorization of interneuron subtypes that is typically observed with the use of classic interneuron markers. We then used single cell RNA sequencing on fetal human cortical neurons to identify genes that are differentially expressed between fetal and adult neurons and those genes that display an expression gradient that reflects the transition between replicating and quiescent fetal neuronal populations. Finally, we observed the expression of major histocompatibility complex type I genes in a subset of adult neurons, but not fetal neurons. The work presented here demonstrates the applicability of single cell RNA sequencing on the study of the adult human brain and constitutes a first step toward a comprehensive cellular atlas of the human brain.

Interplay between type IV pili activity and exopolysaccharides secretion controls motility patterns in single cells of Myxococcus xanthus

PubMed Central

Hu, Wei; Gibiansky, Maxsim L.; Wang, Jing; Wang, Chuandong; Lux, Renate; Li, Yuezhong; Wong, Gerard C. L.; Shi, Wenyuan

2016-01-01

Myxococcus xanthus performs coordinated social motility of cell groups through the extension and retraction of type IV pili (TFP) on solid surfaces, which requires both TFP and exopolysaccharides (EPS). By submerging cells in a liquid medium containing 1% methylcellulose, M. xanthus TFP-driven motility was induced in isolated cells and independently of EPS. We measured and analyzed the movements of cells using community tracking algorithms, which combine single-cell resolution with statistics from large sample populations. Cells without significant multi-cellular social interactions have surprisingly complex behaviors: EPS− cells exhibited a pronounced increase in the tendency to stand vertically and moved with qualitatively different characteristics than other cells. A decrease in the EPS secretion of cells correlates with a higher instantaneous velocity, but with lower directional persistence in trajectories. Moreover, EPS− cells do not adhere to the surface as strongly as wild-type and EPS overproducing cells, and display a greater tendency to have large deviations between the direction of movement and the cell axis, with cell velocity showing only minimal dependence on the direction of movement. The emerging picture is that EPS does not simply provide rheological resistance to a single mechanism but rather that the availability of EPS impacts motility pattern. PMID:26821939

Single cell RNA Seq reveals dynamic paracrine control of cellular variation

PubMed Central

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

2014-01-01

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

Specific binding of sup 125 I-rErythropoietin to Friend polycythemia virus-transformed erythroleukemia cells purified by centrifugal elutriation

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

Correa, P.N.; Bard, V.; Axelrad, A.A.

1990-01-01

We have used countercurrent centrifugal elutriation (CCE) to determine the distribution of cells with respect to cell volume and buoyant density for an erythroleukemia cell line (JG6) transformed by the polycythemia strain of Friend virus (FV-P), and to determine the effect of inducing the cells to differentiate with dimethylsulfoxide (DMSO) on this distribution. CCE made it possible to obtain suspensions of modal JG6 populations virtually free of dead cells and uniform with respect to volume and buoyant density. These modal populations were assayed for specific binding of erythropoietin (Epo). Between 500 and 550 Epo receptors per cell were detected. Thesemore » belonged to a single class having a dissociation constant of 0.36 nM. DMSO induction of differentiation of the JG6 cells had no effect on the number of Epo receptors expressed.« less

High-Throughput Accurate Single-Cell Screening of Euglena gracilis with Fluorescence-Assisted Optofluidic Time-Stretch Microscopy.

PubMed

Guo, Baoshan; Lei, Cheng; Ito, Takuro; Jiang, Yiyue; Ozeki, Yasuyuki; Goda, Keisuke

2016-01-01

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, algal biofuel is expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel) within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate high-throughput, high-accuracy, single-cell screening of E. gracilis with fluorescence-assisted optofluidic time-stretch microscopy-a method that combines the strengths of microfluidic cell focusing, optical time-stretch microscopy, and fluorescence detection used in conventional flow cytometry. Specifically, our fluorescence-assisted optofluidic time-stretch microscope consists of an optical time-stretch microscope and a fluorescence analyzer on top of a hydrodynamically focusing microfluidic device and can detect fluorescence from every E. gracilis cell in a population and simultaneously obtain its image with a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary) and nitrogen-deficient (lipid-accumulated) E. gracilis cells with a low false positive rate of 1.0%. This method holds promise for evaluating cultivation techniques and selective breeding for microalgae-based biofuel production.

Analysis of cell mechanics in single vinculin-deficient cells using a magnetic tweezer

NASA Technical Reports Server (NTRS)

Alenghat, F. J.; Fabry, B.; Tsai, K. Y.; Goldmann, W. H.; Ingber, D. E.

2000-01-01

A magnetic tweezer was constructed to apply controlled tensional forces (10 pN to greater than 1 nN) to transmembrane receptors via bound ligand-coated microbeadswhile optically measuring lateral bead displacements within individual cells. Use of this system with wild-type F9 embryonic carcinoma cells and cells from a vinculin knockout mouse F9 Vin (-/-) revealed much larger differences in the stiffness of the transmembrane integrin linkages to the cytoskeleton than previously reported using related techniques that measured average mechanical properties of large cell populations. The mechanical properties measured varied widely among cells, exhibiting an approximately log-normal distribution. The median lateral bead displacement was 2-fold larger in F9 Vin (-/-) cells compared to wild-type cells whereas the arithmetic mean displacement only increased by 37%. We conclude that vinculin serves a greater mechanical role in cells than previously reported and that this magnetic tweezer device may be useful for probing the molecular basis of cell mechanics within single cells. Copyright 2000 Academic Press.

Multi-scale imaging and informatics pipeline for in situ pluripotent stem cell analysis.

PubMed

Gorman, Bryan R; Lu, Junjie; Baccei, Anna; Lowry, Nathan C; Purvis, Jeremy E; Mangoubi, Rami S; Lerou, Paul H

2014-01-01

Human pluripotent stem (hPS) cells are a potential source of cells for medical therapy and an ideal system to study fate decisions in early development. However, hPS cells cultured in vitro exhibit a high degree of heterogeneity, presenting an obstacle to clinical translation. hPS cells grow in spatially patterned colony structures, necessitating quantitative single-cell image analysis. We offer a tool for analyzing the spatial population context of hPS cells that integrates automated fluorescent microscopy with an analysis pipeline. It enables high-throughput detection of colonies at low resolution, with single-cellular and sub-cellular analysis at high resolutions, generating seamless in situ maps of single-cellular data organized by colony. We demonstrate the tool's utility by analyzing inter- and intra-colony heterogeneity of hPS cell cycle regulation and pluripotency marker expression. We measured the heterogeneity within individual colonies by analyzing cell cycle as a function of distance. Cells loosely associated with the outside of the colony are more likely to be in G1, reflecting a less pluripotent state, while cells within the first pluripotent layer are more likely to be in G2, possibly reflecting a G2/M block. Our multi-scale analysis tool groups colony regions into density classes, and cells belonging to those classes have distinct distributions of pluripotency markers and respond differently to DNA damage induction. Lastly, we demonstrate that our pipeline can robustly handle high-content, high-resolution single molecular mRNA FISH data by using novel image processing techniques. Overall, the imaging informatics pipeline presented offers a novel approach to the analysis of hPS cells that includes not only single cell features but also colony wide, and more generally, multi-scale spatial configuration.

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.

New technologies for the human cytome project.

PubMed

Tárnok, A

2004-01-01

Cytomes or cell systems are composed of various kinds of single-cells and constitute the elementary building units of organs and organisms. Their individualised (cytomic) analysis overcomes the problem of averaged results from cell and tissue homogenates where molecular changes in low frequency cell populations may be hidden and wrongly interpreted. Analysis of the cytome is of pivotal importance in basic research for the understanding of cells and their interrelations in complex environments like tissues and in predictive medicine where it is a prerequisite for individualised preventive therapy. Analysis of molecular phenotypes requires instrumentation that on the one hand provides high-throughput measurement of individual cells and is on the other hand highly multiplexed, enabling the simultaneous acquisition of many parameters on the single cell level. Upcoming technology suitable to this task, such as slide based cytometry is available or under development. The realisation of cytomic technology is important for the realisation of the human cytome project.

Digital Assays Part II: Digital Protein and Cell Assays.

PubMed

Basu, Amar S

2017-08-01

A digital assay is one in which the sample is partitioned into many containers such that each partition contains a discrete number of biological entities (0, 1, 2, 3, . . .). A powerful technique in the biologist's toolkit, digital assays bring a new level of precision in quantifying nucleic acids, measuring proteins and their enzymatic activity, and probing single-cell genotype and phenotype. Where part I of this review focused on the fundamentals of partitioning and digital PCR, part II turns its attention to digital protein and cell assays. Digital enzyme assays measure the kinetics of single proteins with enzymatic activity. Digital enzyme-linked immunoassays (ELISAs) quantify antigenic proteins with 2 to 3 log lower detection limit than conventional ELISA, making them well suited for low-abundance biomarkers. Digital cell assays probe single-cell genotype and phenotype, including gene expression, intracellular and surface proteins, metabolic activity, cytotoxicity, and transcriptomes (scRNA-seq). These methods exploit partitioning to 1) isolate single cells or proteins, 2) detect their activity via enzymatic amplification, and 3) tag them individually by coencapsulating them with molecular barcodes. When scaled, digital assays reveal stochastic differences between proteins or cells within a population, a key to understanding biological heterogeneity. This review is intended to give a broad perspective to scientists interested in adopting digital assays into their workflows.

A compound chimeric antigen receptor strategy for targeting multiple myeloma.

PubMed

Chen, K H; Wada, M; Pinz, K G; Liu, H; Shuai, X; Chen, X; Yan, L E; Petrov, J C; Salman, H; Senzel, L; Leung, E L H; Jiang, X; Ma, Y

2018-02-01

Current clinical outcomes using chimeric-antigen receptors (CARs) against multiple myeloma show promise in the eradication of bulk disease. However, these anti-BCMA (CD269) CARs observe relapse as a common phenomenon after treatment due to the reemergence of either antigen-positive or -negative cells. Hence, the development of improvements in CAR design to target antigen loss and increase effector cell persistency represents a critical need. Here, we report on the anti-tumor activity of a CAR T-cell possessing two complete and independent CAR receptors against the multiple myeloma antigens BCMA and CS1. We determined that the resulting compound CAR (cCAR) T-cell possesses consistent, potent and directed cytotoxicity against each target antigen population. Using multiple mouse models of myeloma and mixed cell populations, we are further able to show superior in vivo survival by directed cytotoxicity against multiple populations compared to a single-expressing CAR T-cell. These findings indicate that compound targeting of BCMA and CS1 on myeloma cells can potentially be an effective strategy for augmenting the response against myeloma bulk disease and for initiation of broader coverage CAR therapy.

A virus or more in (nearly) every cell: ubiquitous networks of virus-host interactions in extreme environments.

PubMed

Munson-McGee, Jacob H; Peng, Shengyun; Dewerff, Samantha; Stepanauskas, Ramunas; Whitaker, Rachel J; Weitz, Joshua S; Young, Mark J

2018-06-01

The application of viral and cellular metagenomics to natural environments has expanded our understanding of the structure, functioning, and diversity of microbial and viral communities. The high diversity of many communities, e.g., soils, surface ocean waters, and animal-associated microbiomes, make it difficult to establish virus-host associations at the single cell (rather than population) level, assign cellular hosts, or determine the extent of viral host range from metagenomics studies alone. Here, we combine single-cell sequencing with environmental metagenomics to characterize the structure of virus-host associations in a Yellowstone National Park (YNP) hot spring microbial community. Leveraging the relatively low diversity of the YNP environment, we are able to overlay evidence at the single-cell level with contextualized viral and cellular community structure. Combining evidence from hexanucelotide analysis, single cell read mapping, network-based analytics, and CRISPR-based inference, we conservatively estimate that >60% of cells contain at least one virus type and a majority of these cells contain two or more virus types. Of the detected virus types, nearly 50% were found in more than 2 cellular clades, indicative of a broad host range. The new lens provided by the combination of metaviromics and single-cell genomics reveals a network of virus-host interactions in extreme environments, provides evidence that extensive virus-host associations are common, and further expands the unseen impact of viruses on cellular life.

Modelling the balance between quiescence and cell death in normal and tumour cell populations.

PubMed

Spinelli, Lorenzo; Torricelli, Alessandro; Ubezio, Paolo; Basse, Britta

2006-08-01

When considering either human adult tissues (in vivo) or cell cultures (in vitro), cell number is regulated by the relationship between quiescent cells, proliferating cells, cell death and other controls of cell cycle duration. By formulating a mathematical description we see that even small alterations of this relationship may cause a non-growing population to start growing with doubling times characteristic of human tumours. Our model consists of two age structured partial differential equations for the proliferating and quiescent cell compartments. Model parameters are death rates from and transition rates between these compartments. The partial differential equations can be solved for the steady-age distributions, giving the distribution of the cells through the cell cycle, dependent on specific model parameter values. Appropriate formulas can then be derived for various population characteristic quantities such as labelling index, proliferation fraction, doubling time and potential doubling time of the cell population. Such characteristic quantities can be estimated experimentally, although with decreasing precision from in vitro, to in vivo experimental systems and to the clinic. The model can be used to investigate the effects of a single alteration of either quiescence or cell death control on the growth of the whole population and the non-trivial dependence of the doubling time and other observable quantities on particular underlying cell cycle scenarios of death and quiescence. The model indicates that tumour evolution in vivo is a sequence of steady-states, each characterised by particular death and quiescence rate functions. We suggest that a key passage of carcinogenesis is a loss of the communication between quiescence, death and cell cycle machineries, causing a defect in their precise, cell cycle dependent relationship.

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

Collective Motion in Bacterial Populations with Mixed Phenotypic Behaviors

NASA Astrophysics Data System (ADS)

Hoeger, Kentaro; Strickland, Ben; Shoup, Daniel; Ursell, Tristan

The motion of large, densely packed groups of organisms is often qualitatively distinct from the motion of individuals, yet hinges on individual properties and behaviors. Collective motion of bacteria depends strongly on the phenotypic behaviors of individual cells, the physical interactions between cells, and the geometry of their environment, often with multiple phenotypes coexisting in a population. Thus, to characterize how these selectively important interactions affect group traits, such as cell dispersal, spatial segregation of phenotypes, and material transport in groups, we use a library of Bacillus subtilis mutants that modulate chemotaxis, motility, and biofilm formation. By mixing phenotypes and observing bacterial behaviors and motion at single cell resolution, we probe collective motion as a function of phenotypic mixture and environmental geometry. Our work demonstrates that collective microbial motion exhibits a transition, from `turbulence' to semiballistic burrowing, as phenotypic composition varies. This work illuminates the role that individual cell behaviors play in the emergence of collective motion, and may signal qualitatively distinct regimes of material transport in bacterial populations. University of Oregon.

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.

Lipid body accumulation alters calcium signaling dynamics in immune cells

PubMed Central

Greineisen, William E.; Speck, Mark; Shimoda, Lori M.N.; Sung, Carl; Phan, Nolwenn; Maaetoft-Udsen, Kristina; Stokes, Alexander J.; Turner, Helen

2014-01-01

Summary There is well-established variability in the numbers of lipid bodies (LB) in macrophages, eosinophils, and neutrophils. Similarly to the steatosis observed in adipocytes and hepatocytes during hyperinsulinemia and nutrient overload, immune cell LB hyper-accumulate in response to bacterial and parasitic infection and inflammatory presentations. Recently we described that hyperinsulinemia, both in vitro and in vivo, drives steatosis and phenotypic changes in primary and transformed mast cells and basophils. LB reach high numbers in these steatotic cytosols, and here we propose that they could dramatically impact the transcytoplasmic signaling pathways. We compared calcium release and influx responses at the population and single cell level in normal and steatotic model mast cells. At the population level, all aspects of FcεRI-dependent calcium mobilization, as well as activation of calcium-dependent downstream signalling targets such as NFATC1 phosphorylation are suppressed. At the single cell level, we demonstrate that LB are both sources and sinks of calcium following FcεRI cross-linking. Unbiased analysis of the impact of the presence of LB on the rate of trans-cytoplasmic calcium signals suggest that LB enrichment accelerates calcium propagation, which may reflect a Bernoulli effect. LB abundance thus impacts this fundamental signalling pathway and its downstream targets. PMID:25016314

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

Vassilevska, Tanya

This is the first code, designed to run on a desktop, which models the intracellular replication and the cell-to-cell infection and demonstrates virus evolution at the molecular level. This code simulates the infection of a population of "idealized biological cells" (represented as objects that do not divide or have metabolism) with "virus" (represented by its genetic sequence), the replication and simultaneous mutation of the virus which leads to evolution of the population of genetically diverse viruses. The code is built to simulate single-stranded RNA viruses. The input for the code is 1. the number of biological cells in the culture,more » 2. the initial composition of the virus population, 3. the reference genome of the RNA virus, 4. the coordinates of the genome regions and their significance and, 5. parameters determining the dynamics of virus replication, such as the mutation rate. The simulation ends when all cells have been infected or when no more infections occurs after a given number of attempts. The code has the ability to simulate the evolution of the virus in serial passage of cell "cultures", i.e. after the end of a simulation, a new one is immediately scheduled with a new culture of infected cells. The code outputs characteristics of the resulting virus population dynamics and genetic composition of the virus population, such as the top dominant genomes, percentage of a genome with specific characteristics.« less

Fundamental differences in diversity and genomic population structure between Atlantic and Pacific Prochlorococcus.

PubMed

Kashtan, Nadav; Roggensack, Sara E; Berta-Thompson, Jessie W; Grinberg, Maor; Stepanauskas, Ramunas; Chisholm, Sallie W

2017-09-01

The Atlantic and Pacific Oceans represent different biogeochemical regimes in which the abundant marine cyanobacterium Prochlorococcus thrives. We have shown that Prochlorococcus populations in the Atlantic are composed of hundreds of genomically, and likely ecologically, distinct coexisting subpopulations with distinct genomic backbones. Here we ask if differences in the ecology and selection pressures between the Atlantic and Pacific are reflected in the diversity and genomic composition of their indigenous Prochlorococcus populations. We applied large-scale single-cell genomics and compared the cell-by-cell genomic composition of wild populations of co-occurring cells from samples from Station ALOHA off Hawaii, and from Bermuda Atlantic Time Series Station off Bermuda. We reveal fundamental differences in diversity and genomic structure of populations between the sites. The Pacific populations are more diverse than those in the Atlantic, composed of significantly more coexisting subpopulations and lacking dominant subpopulations. Prochlorococcus from the two sites seem to be composed of mostly non-overlapping distinct sets of subpopulations with different genomic backbones-likely reflecting different sets of ocean-specific micro-niches. Furthermore, phylogenetically closely related strains carry ocean-associated nutrient acquisition genes likely reflecting differences in major selection pressures between the oceans. This differential selection, along with geographic separation, clearly has a significant role in shaping these populations.

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

NASA Astrophysics Data System (ADS)

Magyar, Andrew; Collins, John

2015-07-01

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

Antibiotic regimen based on population analysis of residing persister cells eradicates Staphylococcus epidermidis biofilms

PubMed Central

Yang, Shoufeng; Hay, Iain D.; Cameron, David R.; Speir, Mary; Cui, Bintao; Su, Feifei; Peleg, Anton Y.; Lithgow, Trevor; Deighton, Margaret A.; Qu, Yue

2015-01-01

Biofilm formation is a major pathogenicity strategy of Staphylococcus epidermidis causing various medical-device infections. Persister cells have been implicated in treatment failure of such infections. We sought to profile bacterial subpopulations residing in S. epidermidis biofilms, and to establish persister-targeting treatment strategies to eradicate biofilms. Population analysis was performed by challenging single biofilm cells with antibiotics at increasing concentrations ranging from planktonic minimum bactericidal concentrations (MBCs) to biofilm MBCs (MBCbiofilm). Two populations of “persister cells” were observed: bacteria that survived antibiotics at MBCbiofilm for 24/48 hours were referred to as dormant cells; those selected with antibiotics at 8 X MICs for 3 hours (excluding dormant cells) were defined as tolerant-but-killable (TBK) cells. Antibiotic regimens targeting dormant cells were tested in vitro for their efficacies in eradicating persister cells and intact biofilms. This study confirmed that there are at least three subpopulations within a S. epidermidis biofilm: normal cells, dormant cells, and TBK cells. Biofilms comprise more TBK cells and dormant cells than their log-planktonic counterparts. Using antibiotic regimens targeting dormant cells, i.e. effective antibiotics at MBCbiofilm for an extended period, might eradicate S. epidermidis biofilms. Potential uses for this strategy are in antibiotic lock techniques and inhaled aerosolized antibiotics. PMID:26687035

Electrochemical Quantification of Extracellular Local H2O2 Kinetics Originating from Single Cells.

PubMed

Bozem, Monika; Knapp, Phillip; Mirčeski, Valentin; Slowik, Ewa J; Bogeski, Ivan; Kappl, Reinhard; Heinemann, Christian; Hoth, Markus

2017-05-15

H 2 O 2 is produced by all eukaryotic cells under physiological and pathological conditions. Due to its enormous relevance for cell signaling at low concentrations and antipathogenic function at high concentrations, precise quantification of extracellular local H 2 O 2 concentrations ([H 2 O 2 ]) originating from single cells is required. Using a scanning electrochemical microscope and bare platinum disk ultramicroelectrodes, we established sensitive long-term measurements of extracellular [H 2 O 2 ] kinetics originating from single primary human monocytes (MCs) ex vivo. For the electrochemical techniques square wave voltammetry, cyclic and linear scan voltammetry, and chronoamperometry, detection limits for [H 2 O 2 ] were determined to be 5, 50, and 500 nM, respectively. Following phorbol ester stimulation, local [H 2 O 2 ] 5-8 μm above a single MC increased by 3.4 nM/s within the first 10 min before reaching a plateau. After extracellular addition of H 2 O 2 to an unstimulated MC, the local [H 2 O 2 ] decreased on average by 4.2 nM/s due to degradation processes of the cell. Using the scanning mode of the setup, we found that H 2 O 2 is evenly distributed around the producing cell and can still be detected up to 30 μm away from the cell. The electrochemical single-cell measurements were validated in MC populations using electron spin resonance spectroscopy and the Amplex ® UltraRed assay. Innovation and Conclusion: We demonstrate a highly sensitive, spatially, and temporally resolved electrochemical approach to monitor dynamics of production and degradation processes for H 2 O 2 separately. Local extracellular [H 2 O 2 ] kinetics originating from single cells is quantified in real time. Antioxid. Redox Signal. 00, 000-000.

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

PubMed

Stolee, Jessica A; Vertes, Akos

2013-04-02

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

viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia.

PubMed

Amir, El-ad David; Davis, Kara L; Tadmor, Michelle D; Simonds, Erin F; Levine, Jacob H; Bendall, Sean C; Shenfeld, Daniel K; Krishnaswamy, Smita; Nolan, Garry P; Pe'er, Dana

2013-06-01

New high-dimensional, single-cell technologies offer unprecedented resolution in the analysis of heterogeneous tissues. However, because these technologies can measure dozens of parameters simultaneously in individual cells, data interpretation can be challenging. Here we present viSNE, a tool that allows one to map high-dimensional cytometry data onto two dimensions, yet conserve the high-dimensional structure of the data. viSNE plots individual cells in a visual similar to a scatter plot, while using all pairwise distances in high dimension to determine each cell's location in the plot. We integrated mass cytometry with viSNE to map healthy and cancerous bone marrow samples. Healthy bone marrow automatically maps into a consistent shape, whereas leukemia samples map into malformed shapes that are distinct from healthy bone marrow and from each other. We also use viSNE and mass cytometry to compare leukemia diagnosis and relapse samples, and to identify a rare leukemia population reminiscent of minimal residual disease. viSNE can be applied to any multi-dimensional single-cell technology.

Small is fast: astrocytic glucose and lactate metabolism at cellular resolution

PubMed Central

Barros, L. F.; San Martín, A.; Sotelo-Hitschfeld, T.; Lerchundi, R.; Fernández-Moncada, I.; Ruminot, I.; Gutiérrez, R.; Valdebenito, R.; Ceballo, S.; Alegría, K.; Baeza-Lehnert, F.; Espinoza, D.

2013-01-01

Brain tissue is highly dynamic in terms of electrical activity and energy demand. Relevant energy metabolites have turnover times ranging from milliseconds to seconds and are rapidly exchanged between cells and within cells. Until recently these fast metabolic events were inaccessible, because standard isotopic techniques require use of populations of cells and/or involve integration times of tens of minutes. Thanks to fluorescent probes and recently available genetically-encoded optical nanosensors, this Technology Report shows how it is now possible to monitor the concentration of metabolites in real-time and in single cells. In combination with ad hoc inhibitor-stop protocols, these probes have revealed a key role for K+ in the acute stimulation of astrocytic glycolysis by synaptic activity. They have also permitted detection of the Warburg effect in single cancer cells. Genetically-encoded nanosensors currently exist for glucose, lactate, NADH and ATP, and it is envisaged that other metabolite nanosensors will soon be available. These optical tools together with improved expression systems and in vivo imaging, herald an exciting era of single-cell metabolic analysis. PMID:23526722

The influence of single bursts vs. single spikes at excitatory dendrodendritic synapses

PubMed Central

Masurkar, Arjun V.; Chen, Wei R.

2015-01-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in-vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC–interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, vs. single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. PMID:22277089

Dual Coding Theory Explains Biphasic Collective Computation in Neural Decision-Making.

PubMed

Daniels, Bryan C; Flack, Jessica C; Krakauer, David C

2017-01-01

A central question in cognitive neuroscience is how unitary, coherent decisions at the whole organism level can arise from the distributed behavior of a large population of neurons with only partially overlapping information. We address this issue by studying neural spiking behavior recorded from a multielectrode array with 169 channels during a visual motion direction discrimination task. It is well known that in this task there are two distinct phases in neural spiking behavior. Here we show Phase I is a distributed or incompressible phase in which uncertainty about the decision is substantially reduced by pooling information from many cells. Phase II is a redundant or compressible phase in which numerous single cells contain all the information present at the population level in Phase I, such that the firing behavior of a single cell is enough to predict the subject's decision. Using an empirically grounded dynamical modeling framework, we show that in Phase I large cell populations with low redundancy produce a slow timescale of information aggregation through critical slowing down near a symmetry-breaking transition. Our model indicates that increasing collective amplification in Phase II leads naturally to a faster timescale of information pooling and consensus formation. Based on our results and others in the literature, we propose that a general feature of collective computation is a "coding duality" in which there are accumulation and consensus formation processes distinguished by different timescales.

Dual Coding Theory Explains Biphasic Collective Computation in Neural Decision-Making

PubMed Central

Daniels, Bryan C.; Flack, Jessica C.; Krakauer, David C.

2017-01-01

A central question in cognitive neuroscience is how unitary, coherent decisions at the whole organism level can arise from the distributed behavior of a large population of neurons with only partially overlapping information. We address this issue by studying neural spiking behavior recorded from a multielectrode array with 169 channels during a visual motion direction discrimination task. It is well known that in this task there are two distinct phases in neural spiking behavior. Here we show Phase I is a distributed or incompressible phase in which uncertainty about the decision is substantially reduced by pooling information from many cells. Phase II is a redundant or compressible phase in which numerous single cells contain all the information present at the population level in Phase I, such that the firing behavior of a single cell is enough to predict the subject's decision. Using an empirically grounded dynamical modeling framework, we show that in Phase I large cell populations with low redundancy produce a slow timescale of information aggregation through critical slowing down near a symmetry-breaking transition. Our model indicates that increasing collective amplification in Phase II leads naturally to a faster timescale of information pooling and consensus formation. Based on our results and others in the literature, we propose that a general feature of collective computation is a “coding duality” in which there are accumulation and consensus formation processes distinguished by different timescales. PMID:28634436

Automated deconvolution of structured mixtures from heterogeneous tumor genomic data

PubMed Central

Roman, Theodore; Xie, Lu

2017-01-01

With increasing appreciation for the extent and importance of intratumor heterogeneity, much attention in cancer research has focused on profiling heterogeneity on a single patient level. Although true single-cell genomic technologies are rapidly improving, they remain too noisy and costly at present for population-level studies. Bulk sequencing remains the standard for population-scale tumor genomics, creating a need for computational tools to separate contributions of multiple tumor clones and assorted stromal and infiltrating cell populations to pooled genomic data. All such methods are limited to coarse approximations of only a few cell subpopulations, however. In prior work, we demonstrated the feasibility of improving cell type deconvolution by taking advantage of substructure in genomic mixtures via a strategy called simplicial complex unmixing. We improve on past work by introducing enhancements to automate learning of substructured genomic mixtures, with specific emphasis on genome-wide copy number variation (CNV) data, as well as the ability to process quantitative RNA expression data, and heterogeneous combinations of RNA and CNV data. We introduce methods for dimensionality estimation to better decompose mixture model substructure; fuzzy clustering to better identify substructure in sparse, noisy data; and automated model inference methods for other key model parameters. We further demonstrate their effectiveness in identifying mixture substructure in true breast cancer CNV data from the Cancer Genome Atlas (TCGA). Source code is available at https://github.com/tedroman/WSCUnmix PMID:29059177

Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity.

PubMed

Nguyen, Quy H; Pervolarakis, Nicholas; Blake, Kerrigan; Ma, Dennis; Davis, Ryan Tevia; James, Nathan; Phung, Anh T; Willey, Elizabeth; Kumar, Raj; Jabart, Eric; Driver, Ian; Rock, Jason; Goga, Andrei; Khan, Seema A; Lawson, Devon A; Werb, Zena; Kessenbrock, Kai

2018-05-23

Breast cancer arises from breast epithelial cells that acquire genetic alterations leading to subsequent loss of tissue homeostasis. Several distinct epithelial subpopulations have been proposed, but complete understanding of the spectrum of heterogeneity and differentiation hierarchy in the human breast remains elusive. Here, we use single-cell mRNA sequencing (scRNAseq) to profile the transcriptomes of 25,790 primary human breast epithelial cells isolated from reduction mammoplasties of seven individuals. Unbiased clustering analysis reveals the existence of three distinct epithelial cell populations, one basal and two luminal cell types, which we identify as secretory L1- and hormone-responsive L2-type cells. Pseudotemporal reconstruction of differentiation trajectories produces one continuous lineage hierarchy that closely connects the basal lineage to the two differentiated luminal branches. Our comprehensive cell atlas provides insights into the cellular blueprint of the human breast epithelium and will form the foundation to understand how the system goes awry during breast cancer.

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

PubMed

Xue, Yuan; Acar, Murat

2018-05-30

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

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

PubMed

Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

2017-04-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data.

PubMed

Hu, Yongli; Hase, Takeshi; Li, Hui Peng; Prabhakar, Shyam; Kitano, Hiroaki; Ng, See Kiong; Ghosh, Samik; Wee, Lawrence Jin Kiat

2016-12-22

The ability to sequence the transcriptomes of single cells using single-cell RNA-seq sequencing technologies presents a shift in the scientific paradigm where scientists, now, are able to concurrently investigate the complex biology of a heterogeneous population of cells, one at a time. However, till date, there has not been a suitable computational methodology for the analysis of such intricate deluge of data, in particular techniques which will aid the identification of the unique transcriptomic profiles difference between the different cellular subtypes. In this paper, we describe the novel methodology for the analysis of single-cell RNA-seq data, obtained from neocortical cells and neural progenitor cells, using machine learning algorithms (Support Vector machine (SVM) and Random Forest (RF)). Thirty-eight key transcripts were identified, using the SVM-based recursive feature elimination (SVM-RFE) method of feature selection, to best differentiate developing neocortical cells from neural progenitor cells in the SVM and RF classifiers built. Also, these genes possessed a higher discriminative power (enhanced prediction accuracy) as compared commonly used statistical techniques or geneset-based approaches. Further downstream network reconstruction analysis was carried out to unravel hidden general regulatory networks where novel interactions could be further validated in web-lab experimentation and be useful candidates to be targeted for the treatment of neuronal developmental diseases. This novel approach reported for is able to identify transcripts, with reported neuronal involvement, which optimally differentiate neocortical cells and neural progenitor cells. It is believed to be extensible and applicable to other single-cell RNA-seq expression profiles like that of the study of the cancer progression and treatment within a highly heterogeneous tumour.

Multiple bidirectional alterations of phenotype and changes in proliferative potential during the in vitro and in vivo passage of clonal mast cell populations derived from mouse peritoneal mast cells

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

Kanakura, Y.; Thompson, H.; Nakano, T.

1988-09-01

Mouse peritoneal mast cells (PMC) express a connective tissue-type mast cell (CTMC) phenotype, including reactivity with the heparin-binding fluorescent dye berberine sulfate and incorporation of (35S) sulfate predominantly into heparin proteoglycans. When PMC purified to greater than 99% purity were cultured in methylcellulose with IL-3 and IL-4, approximately 25% of the PMC formed colonies, all of which contained both berberine sulfate-positive and berberine sulfate-negative mast cells. When these mast cells were transferred to suspension culture, they generated populations that were 100% berberine sulfate-negative, a characteristic similar to that of mucosal mast cells (MMC), and that synthesized predominantly chondroitin sulfate (35S)more » proteoglycans. When ''MMC-like'' cultured mast cells derived from WBB6F1-+/+ PMC were injected into the peritoneal cavities of mast cell-deficient WBB6F1-W/Wv mice, the adoptively transferred mast cell population became 100% berberine sulfate-positive. In methylcellulose culture, these ''second generation PMC'' formed clonal colonies containing both berberine sulfate-positive and berberine sulfate-negative cells, but exhibited significantly less proliferative ability than did normal +/+ PMC. Thus, clonal mast cell populations initially derived from single PMC exhibited multiple and bidirectional alterations between CTMC-like and MMC-like phenotypes. However, this process was associated with a progressive diminution of the mast cells' proliferative ability.« less

Microfluidic cell trap array for controlled positioning of single cells on adhesive micropatterns.

PubMed

Lin, Laiyi; Chu, Yeh-Shiu; Thiery, Jean Paul; Lim, Chwee Teck; Rodriguez, Isabel

2013-02-21

Adhesive micropattern arrays permit the continuous monitoring and systematic study of the behavior of spatially confined cells of well-defined shape and size in ordered configurations. This technique has contributed to defining mechanisms that control cell polarity and cell functions, including proliferation, apoptosis, differentiation and migration in two-dimensional cell culture systems. These micropattern studies often involve isolating a single cell on one adhesive protein micropattern using random seeding methods. Random seeding has been successful for isolated and, to a lesser degree, paired patterns, where two patterns are placed in close proximity. Using this method, we found that the probability of obtaining one cell per pattern decreases significantly as the number of micropatterns in a cluster increases, from 16% for paired micropatterns to 0.3% for clusters of 6 micropatterns. This work presents a simple yet effective platform based on a microfludic sieve-like trap array to exert precise control over the positioning of single cells on micropatterns. We observed a 4-fold improvement over random seeding in the efficiency of placing a pair of single cells on paired micropattern and a 40-fold improvement for 6-pattern clusters. The controlled nature of this platform can also allow the juxtaposition of two different cell populations through a simple modification in the trap arrangement. With excellent control of the identity, number and position of neighbouring cells, this cell-positioning platform provides a unique opportunity for the extension of two-dimensional micropattern studies beyond paired micropatterns to organizations containing many cells or different cell types.

Node-pore sensing enables label-free surface-marker profiling of single cells.

PubMed

Balakrishnan, Karthik R; Whang, Jeremy C; Hwang, Richard; Hack, James H; Godley, Lucy A; Sohn, Lydia L

2015-03-03

Flow cytometry is a ubiquitous, multiparametric method for characterizing cellular populations. However, this method can grow increasingly complex with the number of proteins that need to be screened simultaneously: spectral emission overlap of fluorophores and the subsequent need for compensation, lengthy sample preparation, and multiple control tests that need to be performed separately must all be considered. These factors lead to increased costs, and consequently, flow cytometry is performed in core facilities with a dedicated technician operating the instrument. Here, we describe a low-cost, label-free microfluidic method that can determine the phenotypic profiles of single cells. Our method employs Node-Pore Sensing to measure the transit times of cells as they interact with a series of different antibodies, each corresponding to a specific cell-surface antigen, that have been functionalized in a single microfluidic channel. We demonstrate the capabilities of our method not only by screening two acute promyelocytic leukemia human cells lines (NB4 and AP-1060) for myeloid antigens, CD13, CD14, CD15, and CD33, simultaneously, but also by distinguishing a mixture of cells of similar size—AP-1060 and NALM-1—based on surface markers CD13 and HLA-DR. Furthermore, we show that our method can screen complex subpopulations in clinical samples: we successfully identified the blast population in primary human bone marrow samples from patients with acute myeloid leukemia and screened these cells for CD13, CD34, and HLA-DR. We show that our label-free method is an affordable, highly sensitive, and user-friendly technology that has the potential to transform cellular screening at the benchside.

Genomically Encoded Analog Memory with Precise In vivo DNA Writing in Living Cell Populations

PubMed Central

Farzadfard, Fahim; Lu, Timothy K.

2014-01-01

Cellular memory is crucial to many natural biological processes and for sophisticated synthetic-biology applications. Existing cellular memories rely on epigenetic switches or recombinases, which are limited in scalability and recording capacity. Here, we use the DNA of living cell populations as genomic ‘tape recorders’ for the analog and distributed recording of long-term event histories. We describe a platform for generating single-stranded DNA (ssDNA) in vivo in response to arbitrary transcriptional signals. When co-expressed with a recombinase, these intracellularly expressed ssDNAs target specific genomic DNA addresses, resulting in precise mutations that accumulate in cell populations as a function of the magnitude and duration of the inputs. This platform could enable long-term cellular recorders for environmental and biomedical applications, biological state machines, and enhanced genome engineering strategies. PMID:25395541

In situ single cell detection via microfluidic magnetic bead assay.

PubMed

Liu, Fan; Kc, Pawan; Zhang, Ge; Zhe, Jiang

2017-01-01

We present a single cell detection device based on magnetic bead assay and micro Coulter counters. This device consists of two successive micro Coulter counters, coupled with a high gradient magnetic field generated by an external magnet. The device can identify single cells in terms of the transit time difference of the cell through the two micro Coulter counters. Target cells are conjugated with magnetic beads via specific antibody and antigen binding. A target cell traveling through the two Coulter counters interacts with the magnetic field, and have a longer transit time at the 1st counter than that at the 2nd counter. In comparison, a non-target cell has no interaction with the magnetic field, and hence has nearly the same transit times through the two counters. Each cell passing through the two counters generates two consecutive voltage pulses one after the other; the pulse widths and magnitudes indicating the cell's transit times through the counters and the cell's size respectively. Thus, by measuring the pulse widths (transit times) of each cell through the two counters, each single target cell can be differentiated from non-target cells even if they have similar sizes. We experimentally proved that the target human umbilical vein endothelial cells (HUVECs) and non-target rat adipose-derived stem cells (rASCs) have significant different transit time distribution, from which we can determine the recognition regions for both cell groups quantitatively. We further demonstrated that within a mixed cell population of rASCs and HUVECs, HUVECs can be detected in situ and the measured HUVECs ratios agree well with the pre-set ratios. With the simple device structure and easy sample preparation, this method is expected to enable single cell detection in a continuous flow and can be applied to facilitate general cell detection applications such as stem cell identification and enumeration.

Cells Respond to Distinct Nanoparticle Properties with Multiple Strategies As Revealed by Single-Cell RNA-Seq

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

Mitchell, Hugh D.; Markillie, Lye Meng; Chrisler, William B.

The impact of distinct nanoparticle (NP) properties on cellular response and ultimately human health is unclear. This gap is partially due to experimental difficulties in achieving uniform NP loads in the studied cells, creating heterogeneous populations with some cells “overloaded” while other cells are loaded with few or no NPs. Yet gene expression studies have been conducted in the population as a whole, identifying generic responses, while missing unique responses due to signal averaging across many cells, each carrying different loads. Here we applied single-cell RNA-Seq to alveolar epithelial cells carrying defined loads of aminated or carboxylated quantum dots (QDs),more » showing higher or lower toxicity, respectively. Interestingly, cells carrying lower loads responded with multiple strategies, mostly with upregulated processes, which were nonetheless coherent and unique to each QD type. In contrast, cells carrying higher loads responded more uniformly, with mostly downregulated processes that were shared across QD types. Strategies unique to aminated QDs showed strong upregulation of stress responses, coupled in some cases with regulation of cell cycle, protein synthesis and organelle activities. In contrast, strategies unique to carboxylated QDs showed upregulation of DNA repair and RNA activities, and decreased regulation of cell division, coupled in some cases with upregulation of stress responses and ATP related functions. Together, our studies suggest scenarios where higher NP loads lock cells into uniform responses, mostly shutdown of cellular processes, whereas lower loads allow for unique responses to each NP type that are more diversified, proactive defenses or repairs of the NP insults.« less

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.

Quantification of DNA-associated proteins inside eukaryotic cells using single-molecule localization microscopy

PubMed Central

Etheridge, Thomas J.; Boulineau, Rémi L.; Herbert, Alex; Watson, Adam T.; Daigaku, Yasukazu; Tucker, Jem; George, Sophie; Jönsson, Peter; Palayret, Matthieu; Lando, David; Laue, Ernest; Osborne, Mark A.; Klenerman, David; Lee, Steven F.; Carr, Antony M.

2014-01-01

Development of single-molecule localization microscopy techniques has allowed nanometre scale localization accuracy inside cells, permitting the resolution of ultra-fine cell structure and the elucidation of crucial molecular mechanisms. Application of these methodologies to understanding processes underlying DNA replication and repair has been limited to defined in vitro biochemical analysis and prokaryotic cells. In order to expand these techniques to eukaryotic systems, we have further developed a photo-activated localization microscopy-based method to directly visualize DNA-associated proteins in unfixed eukaryotic cells. We demonstrate that motion blurring of fluorescence due to protein diffusivity can be used to selectively image the DNA-bound population of proteins. We designed and tested a simple methodology and show that it can be used to detect changes in DNA binding of a replicative helicase subunit, Mcm4, and the replication sliding clamp, PCNA, between different stages of the cell cycle and between distinct genetic backgrounds. PMID:25106872

The basics of cell therapy to treat cardiovascular disease: one cell does not fit all.

PubMed

Taylor, Doris A; Robertson, Matthew J

2009-09-01

Cardiovascular disease represents a continuum of disease entities whose medical treatments differ. Cell therapy is a 21st century approach to treating cardiovascular disease and is being applied worldwide. However, no concerted approach exists for defining the best cell population(s) to use, or the best treatment conditions. It is naïve to believe that a single treatment -even a stem cell- can be found to treat the entire spectrum of cardiovascular disease. We describe the continuum of ischemic heart disease, the potential uses of cells for treating this continuum, and the basic issues that must be considered when contemplating cardiovascular cell therapy. The clinical goal is cardiac and vascular regeneration. Whether cells can deliver this remains to be determined. The correct cell, the ideal therapeutic window, and the patient likewise are open to debate. This article is designed to provide insights into the early, middle, and later stages of cardiovascular disease and how cells might be used differently for treatment at each stage.

Hematopoietic Stem Cells as a Novel Source of Dental Tissue Cells.

PubMed

Wilson, Katie R; Kang, In-Hong; Baliga, Uday; Xiong, Ying; Chatterjee, Shilpak; Moore, Emily; Parthiban, Beneta; Thyagarajan, Krishnamurthy; Borke, James L; Mehrotra, Shikhar; Kirkwood, Keith L; LaRue, Amanda C; Ogawa, Makio; Mehrotra, Meenal

2018-05-23

While earlier studies have suggested that cells positive for hematopoietic markers can be found in dental tissues, it has yet to be confirmed. To conclusively demonstrate this, we utilized a unique transgenic model in which all hematopoietic cells are green fluorescent protein + (GFP + ). Pulp, periodontal ligament (PDL) and alveolar bone (AvB) cell culture analysis demonstrated numerous GFP + cells, which were also CD45 + (indicating hematopoietic origin) and co-expressed markers of cellular populations in pulp (dentin matrix protein-1, dentin sialophosphoprotein, alpha smooth muscle actin [ASMA], osteocalcin), in PDL (periostin, ASMA, vimentin, osteocalcin) and in AvB (Runx-2, bone sialoprotein, alkaline phosphatase, osteocalcin). Transplantation of clonal population derived from a single GFP + hematopoietic stem cell (HSC), into lethally irradiated recipient mice, demonstrated numerous GFP + cells within dental tissues of recipient mice, which also stained for markers of cell populations in pulp, PDL and AvB (used above), indicating that transplanted HSCs can differentiate into cells in dental tissues. These hematopoietic-derived cells deposited collagen and can differentiate in osteogenic media, indicating that they are functional. Thus, our studies demonstrate, for the first time, that cells in pulp, PDL and AvB can have a hematopoietic origin, thereby opening new avenues of therapy for dental diseases and injuries.

Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

NASA Astrophysics Data System (ADS)

McReynolds, Naomi; Cooke, Fiona G. M.; Chen, Mingzhou; Powis, Simon J.; Dholakia, Kishan

2017-03-01

The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a means for validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.

Red blood cell-deformability measurement: review of techniques.

PubMed

Musielak, M

2009-01-01

Cell-deformability characterization involves general measurement of highly complex relationships between cell biology and physical forces to which the cell is subjected. The review takes account of the modern technical solutions simulating the action of the force applied to the red blood cell in macro- and microcirculation. Diffraction ektacytometers and rheoscopes measure the mean deformability value for the total red blood cell population investigated and the deformation distribution index of individual cells, respectively. Deformation assays of a whole single cell are possible by means of optical tweezers. The single cell-measuring setups for micropipette aspiration and atomic force microscopy allow conducting a selective investigation of deformation parameters (e.g., cytoplasm viscosity, viscoelastic membrane properties). The distinction between instrument sensitivity to various RBC-rheological features as well as the influence of temperature on measurement are discussed. The reports quoted confront fascinating possibilities of the techniques with their medical applications since the RBC-deformability has the key position in the etiology of a wide range of conditions.

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

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells.

PubMed

Rizzetto, Simone; Eltahla, Auda A; Lin, Peijie; Bull, Rowena; Lloyd, Andrew R; Ho, Joshua W K; Venturi, Vanessa; Luciani, Fabio

2017-10-06

Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% - 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

Technology advancement for integrative stem cell analyses.

PubMed

Jeong, Yoon; Choi, Jonghoon; Lee, Kwan Hyi

2014-12-01

Scientists have endeavored to use stem cells for a variety of applications ranging from basic science research to translational medicine. Population-based characterization of such stem cells, while providing an important foundation to further development, often disregard the heterogeneity inherent among individual constituents within a given population. The population-based analysis and characterization of stem cells and the problems associated with such a blanket approach only underscore the need for the development of new analytical technology. In this article, we review current stem cell analytical technologies, along with the advantages and disadvantages of each, followed by applications of these technologies in the field of stem cells. Furthermore, while recent advances in micro/nano technology have led to a growth in the stem cell analytical field, underlying architectural concepts allow only for a vertical analytical approach, in which different desirable parameters are obtained from multiple individual experiments and there are many technical challenges that limit vertically integrated analytical tools. Therefore, we propose--by introducing a concept of vertical and horizontal approach--that there is the need of adequate methods to the integration of information, such that multiple descriptive parameters from a stem cell can be obtained from a single experiment.

Technology Advancement for Integrative Stem Cell Analyses

PubMed Central

Jeong, Yoon

2014-01-01

Scientists have endeavored to use stem cells for a variety of applications ranging from basic science research to translational medicine. Population-based characterization of such stem cells, while providing an important foundation to further development, often disregard the heterogeneity inherent among individual constituents within a given population. The population-based analysis and characterization of stem cells and the problems associated with such a blanket approach only underscore the need for the development of new analytical technology. In this article, we review current stem cell analytical technologies, along with the advantages and disadvantages of each, followed by applications of these technologies in the field of stem cells. Furthermore, while recent advances in micro/nano technology have led to a growth in the stem cell analytical field, underlying architectural concepts allow only for a vertical analytical approach, in which different desirable parameters are obtained from multiple individual experiments and there are many technical challenges that limit vertically integrated analytical tools. Therefore, we propose—by introducing a concept of vertical and horizontal approach—that there is the need of adequate methods to the integration of information, such that multiple descriptive parameters from a stem cell can be obtained from a single experiment. PMID:24874188

In situ single cell detection via microfluidic magnetic bead assay

PubMed Central

KC, Pawan; Zhang, Ge; Zhe, Jiang

2017-01-01

We present a single cell detection device based on magnetic bead assay and micro Coulter counters. This device consists of two successive micro Coulter counters, coupled with a high gradient magnetic field generated by an external magnet. The device can identify single cells in terms of the transit time difference of the cell through the two micro Coulter counters. Target cells are conjugated with magnetic beads via specific antibody and antigen binding. A target cell traveling through the two Coulter counters interacts with the magnetic field, and have a longer transit time at the 1st counter than that at the 2nd counter. In comparison, a non-target cell has no interaction with the magnetic field, and hence has nearly the same transit times through the two counters. Each cell passing through the two counters generates two consecutive voltage pulses one after the other; the pulse widths and magnitudes indicating the cell’s transit times through the counters and the cell’s size respectively. Thus, by measuring the pulse widths (transit times) of each cell through the two counters, each single target cell can be differentiated from non-target cells even if they have similar sizes. We experimentally proved that the target human umbilical vein endothelial cells (HUVECs) and non-target rat adipose-derived stem cells (rASCs) have significant different transit time distribution, from which we can determine the recognition regions for both cell groups quantitatively. We further demonstrated that within a mixed cell population of rASCs and HUVECs, HUVECs can be detected in situ and the measured HUVECs ratios agree well with the pre-set ratios. With the simple device structure and easy sample preparation, this method is expected to enable single cell detection in a continuous flow and can be applied to facilitate general cell detection applications such as stem cell identification and enumeration. PMID:28222140

High Points of Human Genetics

ERIC Educational Resources Information Center

Stern, Curt

1975-01-01

Discusses such high points of human genetics as the study of chromosomes, somatic cell hybrids, the population formula: the Hardy-Weinberg Law, biochemical genetics, the single-active X Theory, behavioral genetics and finally how genetics can serve humanity. (BR)

Freezer anthropology: new uses for old blood.

PubMed Central

Merriwether, D A

1999-01-01

Archived blood fractions (plasma, settled red cells, white cells) have proved to be a rich and valuable source of DNA for human genetic studies. Large numbers of such samples were collected between 1960 and the present for protein and blood group studies, many of which are languishing in freezers or have already been discarded. More are discarded each year because the usefulness of these samples is not widely understood. Data from DNA derived from 10-35-year-old blood samples have been used to address the peopling of the New World and of the Pacific. Mitochondrial DNA haplotypes from studies using this source DNA support a single wave of migration into the New World (or a single source population for the New World), and that Mongolia was the likely source of the founding population. Data from Melanesia have shown that Polynesians are recent immigrants into the Pacific and did not arise from Melanesia. PMID:10091252

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

Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks

PubMed Central

Samusik, Nikolay; Wang, Xiaowei; Guan, Leying; Nolan, Garry P.

2017-01-01

Mass cytometry (CyTOF) has greatly expanded the capability of cytometry. It is now easy to generate multiple CyTOF samples in a single study, with each sample containing single-cell measurement on 50 markers for more than hundreds of thousands of cells. Current methods do not adequately address the issues concerning combining multiple samples for subpopulation discovery, and these issues can be quickly and dramatically amplified with increasing number of samples. To overcome this limitation, we developed Partition-Assisted Clustering and Multiple Alignments of Networks (PAC-MAN) for the fast automatic identification of cell populations in CyTOF data closely matching that of expert manual-discovery, and for alignments between subpopulations across samples to define dataset-level cellular states. PAC-MAN is computationally efficient, allowing the management of very large CyTOF datasets, which are increasingly common in clinical studies and cancer studies that monitor various tissue samples for each subject. PMID:29281633

Mapping cell populations in flow cytometry data for cross-sample comparison using the Friedman-Rafsky test statistic as a distance measure.

PubMed

Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu; Scheuermann, Richard H

2016-01-01

Flow cytometry (FCM) is a fluorescence-based single-cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap-FR, a novel method for cell population mapping across FCM samples. FlowMap-FR is based on the Friedman-Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap-FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap-FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap-FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap-FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap-FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback-Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL-distance in distinguishing equivalent from nonequivalent cell populations. FlowMap-FR was also employed as a distance metric to match cell populations delineated by manual gating across 30 FCM samples from a benchmark FlowCAP data set. An F-measure of 0.88 was obtained, indicating high precision and recall of the FR-based population matching results. FlowMap-FR has been implemented as a standalone R/Bioconductor package so that it can be easily incorporated into current FCM data analytical workflows. © The Authors. Published by Wiley Periodicals, Inc. on behalf of ISAC.

Developmental Origin Governs CD8+ T Cell Fate Decisions during Infection.

PubMed

Smith, Norah L; Patel, Ravi K; Reynaldi, Arnold; Grenier, Jennifer K; Wang, Jocelyn; Watson, Neva B; Nzingha, Kito; Yee Mon, Kristel J; Peng, Seth A; Grimson, Andrew; Davenport, Miles P; Rudd, Brian D

2018-06-06

Heterogeneity is a hallmark feature of the adaptive immune system in vertebrates. Following infection, naive T cells differentiate into various subsets of effector and memory T cells, which help to eliminate pathogens and maintain long-term immunity. The current model suggests there is a single lineage of naive T cells that give rise to different populations of effector and memory T cells depending on the type and amounts of stimulation they encounter during infection. Here, we have discovered that multiple sub-populations of cells exist in the naive CD8 + T cell pool that are distinguished by their developmental origin, unique transcriptional profiles, distinct chromatin landscapes, and different kinetics and phenotypes after microbial challenge. These data demonstrate that the naive CD8 + T cell pool is not as homogeneous as previously thought and offers a new framework for explaining the remarkable heterogeneity in the effector and memory T cell subsets that arise after infection. Copyright © 2018 Elsevier Inc. All rights reserved.

Design and Application of Sensors for Chemical Cytometry.

PubMed

Vickerman, Brianna M; Anttila, Matthew M; Petersen, Brae V; Allbritton, Nancy L; Lawrence, David S

2018-02-08

The bulk cell population response to a stimulus, be it a growth factor or a cytotoxic agent, neglects the cell-to-cell variability that can serve as a friend or as a foe in human biology. Biochemical variations among closely related cells furnish the basis for the adaptability of the immune system but also act as the root cause of resistance to chemotherapy by tumors. Consequently, the ability to probe for the presence of key biochemical variables at the single-cell level is now recognized to be of significant biological and biomedical impact. Chemical cytometry has emerged as an ultrasensitive single-cell platform with the flexibility to measure an array of cellular components, ranging from metabolite concentrations to enzyme activities. We briefly review the various chemical cytometry strategies, including recent advances in reporter design, probe and metabolite separation, and detection instrumentation. We also describe strategies for improving intracellular delivery, biochemical specificity, metabolic stability, and detection sensitivity of probes. Recent applications of these strategies to small molecules, lipids, proteins, and other analytes are discussed. Finally, we assess the current scope and limitations of chemical cytometry and discuss areas for future development to meet the needs of single-cell research.

Identification, characterization and isolation of a common progenitor for osteoclasts, macrophages and dendritic cells from murine bone marrow and periphery

PubMed Central

Jacome-Galarza, Christian E.; Lee, Sun-Kyeong; Lorenzo, Joseph A.; LeonardoAguila, Hector

2012-01-01

Osteoclasts are specialized bone resorbing cells that derive from monocyte precursors. We have identified three populations of cells with high osteoclastogenic potential in murine bone marrow, which expressed the phenotype: B220−CD3−CD11b−/low CD115+ and either CD117hi, CD117intermediate or CD117low. We have evaluated these populations for their ability to also generate macrophages and dendritic cells. At a single cell level, the population expressing higher CD117 levels was able to generate bone-resorbing osteoclasts, phagocytic macrophages and antigen-presenting dendritic cells in vitro with efficiencies of over 90 percent, indicating that there exists a common developmental pathway for these cell types. Cells with osteoclastogenic potential also exist in blood and peripheral hematopoietic organs. Their functional meaning and/or their relationship with bone marrow progenitors is not well established. Hence, we characterized murine peripheral cell populations for their ability to form osteoclasts, macrophages and dendritic cells in vitro. The spleen and peripheral blood monocyte progenitors share phenotypic markers with bone marrow progenitors, but differ in their expression of CD11b, which was low in bone marrow but high in periphery. We propose that circulating monocyte progenitors are derived from a common bone marrow osteoclasts/macrophage/dendritic cell progenitor (OcMDC), which we have now characterized at a clonal level. However, the lineage relationship between the bone marrow and peripheral monocyte progenitors has yet to be defined. PMID:23165930