Single cell array impedance analysis in a microfluidic device

NASA Astrophysics Data System (ADS)

Altinagac, Emre; Taskin, Selen; Kizil, Huseyin

2016-10-01

Impedance analysis of single cells is presented in this paper. Following the separation of a target cell type by dielectrophoresis in our previous work, this paper focuses on capturing the cells as a single array and performing impedance analysis to point out the signature difference between each cell type. Lab-on-a-chip devices having a titanium interdigitated electrode layer on a glass substrate and a PDMS microchannel are fabricated to capture each cell in a single form and perform impedance analysis. HCT116 (homosapiens colon colorectal carcin) and HEK293 (human embryonic kidney) cells are used in our experiments.

High-throughput microfluidic single-cell digital polymerase chain reaction.

PubMed

White, A K; Heyries, K A; Doolin, C; Vaninsberghe, M; Hansen, C L

2013-08-06

Here we present an integrated microfluidic device for the high-throughput digital polymerase chain reaction (dPCR) analysis of single cells. This device allows for the parallel processing of single cells and executes all steps of analysis, including cell capture, washing, lysis, reverse transcription, and dPCR analysis. The cDNA from each single cell is distributed into a dedicated dPCR array consisting of 1020 chambers, each having a volume of 25 pL, using surface-tension-based sample partitioning. The high density of this dPCR format (118,900 chambers/cm(2)) allows the analysis of 200 single cells per run, for a total of 204,000 PCR reactions using a device footprint of 10 cm(2). Experiments using RNA dilutions show this device achieves shot-noise-limited performance in quantifying single molecules, with a dynamic range of 10(4). We performed over 1200 single-cell measurements, demonstrating the use of this platform in the absolute quantification of both high- and low-abundance mRNA transcripts, as well as micro-RNAs that are not easily measured using alternative hybridization methods. We further apply the specificity and sensitivity of single-cell dPCR to performing measurements of RNA editing events in single cells. High-throughput dPCR provides a new tool in the arsenal of single-cell analysis methods, with a unique combination of speed, precision, sensitivity, and specificity. We anticipate this approach will enable new studies where high-performance single-cell measurements are essential, including the analysis of transcriptional noise, allelic imbalance, and RNA processing.

Single prokaryotic cell isolation and total transcript amplification protocol for transcriptomic analysis.

PubMed

Kang, Yun; McMillan, Ian; Norris, Michael H; Hoang, Tung T

2015-07-01

Until recently, transcriptome analyses of single cells have been confined to eukaryotes. The information obtained from single-cell transcripts can provide detailed insight into spatiotemporal gene expression, and it could be even more valuable if expanded to prokaryotic cells. Transcriptome analysis of single prokaryotic cells is a recently developed and powerful tool. Here we describe a procedure that allows amplification of the total transcript of a single prokaryotic cell for in-depth analysis. This is performed by using a laser-capture microdissection instrument for single-cell isolation, followed by reverse transcription via Moloney murine leukemia virus, degradation of chromosomal DNA with McrBC and DpnI restriction enzymes, single-stranded cDNA (ss-cDNA) ligation using T4 polynucleotide kinase and CircLigase, and polymerization of ss-cDNA to double-stranded cDNA (ds-cDNA) by Φ29 polymerase. This procedure takes ∼5 d, and sufficient amounts of ds-cDNA can be obtained from single-cell RNA template for further microarray analysis.

Single-Cell RNA-Sequencing: Assessment of Differential Expression Analysis Methods.

PubMed

Dal Molin, Alessandra; Baruzzo, Giacomo; Di Camillo, Barbara

2017-01-01

The sequencing of the transcriptomes of single-cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types and for the study of stochastic gene expression. In recent years, various tools for analyzing single-cell RNA-sequencing data have been proposed, many of them with the purpose of performing differentially expression analysis. In this work, we compare four different tools for single-cell RNA-sequencing differential expression, together with two popular methods originally developed for the analysis of bulk RNA-sequencing data, but largely applied to single-cell data. We discuss results obtained on two real and one synthetic dataset, along with considerations about the perspectives of single-cell differential expression analysis. In particular, we explore the methods performance in four different scenarios, mimicking different unimodal or bimodal distributions of the data, as characteristic of single-cell transcriptomics. We observed marked differences between the selected methods in terms of precision and recall, the number of detected differentially expressed genes and the overall performance. Globally, the results obtained in our study suggest that is difficult to identify a best performing tool and that efforts are needed to improve the methodologies for single-cell RNA-sequencing data analysis and gain better accuracy of results.

Integrated Droplet-Based Microextraction with ESI-MS for Removal of Matrix Interference in Single-Cell Analysis.

PubMed

Zhang, Xiao-Chao; Wei, Zhen-Wei; Gong, Xiao-Yun; Si, Xing-Yu; Zhao, Yao-Yao; Yang, Cheng-Dui; Zhang, Si-Chun; Zhang, Xin-Rong

2016-04-29

Integrating droplet-based microfluidics with mass spectrometry is essential to high-throughput and multiple analysis of single cells. Nevertheless, matrix effects such as the interference of culture medium and intracellular components influence the sensitivity and the accuracy of results in single-cell analysis. To resolve this problem, we developed a method that integrated droplet-based microextraction with single-cell mass spectrometry. Specific extraction solvent was used to selectively obtain intracellular components of interest and remove interference of other components. Using this method, UDP-Glc-NAc, GSH, GSSG, AMP, ADP and ATP were successfully detected in single MCF-7 cells. We also applied the method to study the change of unicellular metabolites in the biological process of dysfunctional oxidative phosphorylation. The method could not only realize matrix-free, selective and sensitive detection of metabolites in single cells, but also have the capability for reliable and high-throughput single-cell analysis.

Single-cell isolation by a modular single-cell pipette for RNA-sequencing.

PubMed

Zhang, Kai; Gao, Min; Chong, Zechen; Li, Ying; Han, Xin; Chen, Rui; Qin, Lidong

2016-11-29

Single-cell transcriptome sequencing highly requires a convenient and reliable method to rapidly isolate a live cell into a specific container such as a PCR tube. Here, we report a modular single-cell pipette (mSCP) consisting of three modular components, a SCP-Tip, an air-displacement pipette (ADP), and ADP-Tips, that can be easily assembled, disassembled, and reassembled. By assembling the SCP-Tip containing a hydrodynamic trap, the mSCP can isolate single cells from 5-10 cells per μL of cell suspension. The mSCP is compatible with microscopic identification of captured single cells to finally achieve 100% single-cell isolation efficiency. The isolated live single cells are in submicroliter volumes and well suitable for single-cell PCR analysis and RNA-sequencing. The mSCP possesses merits of convenience, rapidness, and high efficiency, making it a powerful tool to isolate single cells for transcriptome analysis.

Optofluidic Cell Selection from Complex Microbial Communities for Single-Genome Analysis

PubMed Central

Landry, Zachary C.; Giovanonni, Stephen J.; Quake, Stephen R.; Blainey, Paul C.

2013-01-01

Genetic analysis of single cells is emerging as a powerful approach for studies of heterogeneous cell populations. Indeed, the notion of homogeneous cell populations is receding as approaches to resolve genetic and phenotypic variation between single cells are applied throughout the life sciences. A key step in single-cell genomic analysis today is the physical isolation of individual cells from heterogeneous populations, particularly microbial populations, which often exhibit high diversity. Here, we detail the construction and use of instrumentation for optical trapping inside microfluidic devices to select individual cells for analysis by methods including nucleic acid sequencing. This approach has unique advantages for analyses of rare community members, cells with irregular morphologies, small quantity samples, and studies that employ advanced optical microscopy. PMID:24060116

Enhanced electrochemical nanoring electrode for analysis of cytosol in single cells.

PubMed

Zhuang, Lihong; Zuo, Huanzhen; Wu, Zengqiang; Wang, Yu; Fang, Danjun; Jiang, Dechen

2014-12-02

A microelectrode array has been applied for single cell analysis with relatively high throughput; however, the cells were typically cultured on the microelectrodes under cell-size microwell traps leading to the difficulty in the functionalization of an electrode surface for higher detection sensitivity. Here, nanoring electrodes embedded under the microwell traps were fabricated to achieve the isolation of the electrode surface and the cell support, and thus, the electrode surface can be modified to obtain enhanced electrochemical sensitivity for single cell analysis. Moreover, the nanometer-sized electrode permitted a faster diffusion of analyte to the surface for additional improvement in the sensitivity, which was evidenced by the electrochemical characterization and the simulation. To demonstrate the concept of the functionalized nanoring electrode for single cell analysis, the electrode surface was deposited with prussian blue to detect intracellular hydrogen peroxide at a single cell. Hundreds of picoamperes were observed on our functionalized nanoring electrode exhibiting the enhanced electrochemical sensitivity. The success in the achievement of a functionalized nanoring electrode will benefit the development of high throughput single cell electrochemical analysis.

A generic, cost-effective, and scalable cell lineage analysis platform

PubMed Central

Biezuner, Tamir; Spiro, Adam; Raz, Ofir; Amir, Shiran; Milo, Lilach; Adar, Rivka; Chapal-Ilani, Noa; Berman, Veronika; Fried, Yael; Ainbinder, Elena; Cohen, Galit; Barr, Haim M.; Halaban, Ruth; Shapiro, Ehud

2016-01-01

Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing-based methods for cell lineage analysis depend on low-resolution bulk analysis or rely on extensive single-cell sequencing, which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective, and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data, and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way toward large-scale human cell lineage discovery. PMID:27558250

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.

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

NASA Astrophysics Data System (ADS)

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

2010-08-01

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

Design and Analysis of Single-Cell Sequencing Experiments.

PubMed

Grün, Dominic; van Oudenaarden, Alexander

2015-11-05

Recent advances in single-cell sequencing hold great potential for exploring biological systems with unprecedented resolution. Sequencing the genome of individual cells can reveal somatic mutations and allows the investigation of clonal dynamics. Single-cell transcriptome sequencing can elucidate the cell type composition of a sample. However, single-cell sequencing comes with major technical challenges and yields complex data output. In this Primer, we provide an overview of available methods and discuss experimental design and single-cell data analysis. We hope that these guidelines will enable a growing number of researchers to leverage the power of single-cell sequencing. Copyright © 2015 Elsevier Inc. All rights reserved.

Making a big thing of a small cell--recent advances in single cell analysis.

PubMed

Galler, Kerstin; Bräutigam, Katharina; Große, Christina; Popp, Jürgen; Neugebauer, Ute

2014-03-21

Single cell analysis is an emerging field requiring a high level interdisciplinary collaboration to provide detailed insights into the complex organisation, function and heterogeneity of life. This review is addressed to life science researchers as well as researchers developing novel technologies. It covers all aspects of the characterisation of single cells (with a special focus on mammalian cells) from morphology to genetics and different omics-techniques to physiological, mechanical and electrical methods. In recent years, tremendous advances have been achieved in all fields of single cell analysis: (1) improved spatial and temporal resolution of imaging techniques to enable the tracking of single molecule dynamics within single cells; (2) increased throughput to reveal unexpected heterogeneity between different individual cells raising the question what characterizes a cell type and what is just natural biological variation; and (3) emerging multimodal approaches trying to bring together information from complementary techniques paving the way for a deeper understanding of the complexity of biological processes. This review also covers the first successful translations of single cell analysis methods to diagnostic applications in the field of tumour research (especially circulating tumour cells), regenerative medicine, drug discovery and immunology.

A nanobiosensor for dynamic single cell analysis during microvascular self-organization.

PubMed

Wang, S; Sun, J; Zhang, D D; Wong, P K

2016-10-14

The formation of microvascular networks plays essential roles in regenerative medicine and tissue engineering. Nevertheless, the self-organization mechanisms underlying the dynamic morphogenic process are poorly understood due to a paucity of effective tools for mapping the spatiotemporal dynamics of single cell behaviors. By establishing a single cell nanobiosensor along with live cell imaging, we perform dynamic single cell analysis of the morphology, displacement, and gene expression during microvascular self-organization. Dynamic single cell analysis reveals that endothelial cells self-organize into subpopulations with specialized phenotypes to form microvascular networks and identifies the involvement of Notch1-Dll4 signaling in regulating the cell subpopulations. The cell phenotype correlates with the initial Dll4 mRNA expression level and each subpopulation displays a unique dynamic Dll4 mRNA expression profile. Pharmacological perturbations and RNA interference of Notch1-Dll4 signaling modulate the cell subpopulations and modify the morphology of the microvascular network. Taken together, a nanobiosensor enables a dynamic single cell analysis approach underscoring the importance of Notch1-Dll4 signaling in microvascular self-organization.

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 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.

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.

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.

Single-Cell Sequencing Technologies for Cardiac Stem Cell Studies.

PubMed

Liu, Tiantian; Wu, Hongjin; Wu, Shixiu; Wang, Charles

2017-11-01

Today with the rapid advancements in stem cell studies and the promising potential of using stem cells in clinical therapy, there is an increasing demand for in-depth comprehensive analysis on individual cell transcriptome and epigenome, as they play critical roles in a number of cell functions such as cell differentiation, growth, and reprogramming. The development of single-cell sequencing technologies has helped in revealing some exciting new perspectives in stem cells and regenerative medicine research. Among the various potential applications, single-cell analysis for cardiac stem cells (CSCs) holds tremendous promises in understanding the mechanisms of heart development and regeneration, which might light up the path toward cell therapy for cardiovascular diseases. This review briefly highlights the recent progresses in single-cell sequencing analysis technologies and their applications in CSC research.

Nanoliter-Scale Oil-Air-Droplet Chip-Based Single Cell Proteomic Analysis.

PubMed

Li, Zi-Yi; Huang, Min; Wang, Xiu-Kun; Zhu, Ying; Li, Jin-Song; Wong, Catherine C L; Fang, Qun

2018-04-17

Single cell proteomic analysis provides crucial information on cellular heterogeneity in biological systems. Herein, we describe a nanoliter-scale oil-air-droplet (OAD) chip for achieving multistep complex sample pretreatment and injection for single cell proteomic analysis in the shotgun mode. By using miniaturized stationary droplet microreaction and manipulation techniques, our system allows all sample pretreatment and injection procedures to be performed in a nanoliter-scale droplet with minimum sample loss and a high sample injection efficiency (>99%), thus substantially increasing the analytical sensitivity for single cell samples. We applied the present system in the proteomic analysis of 100 ± 10, 50 ± 5, 10, and 1 HeLa cell(s), and protein IDs of 1360, 612, 192, and 51 were identified, respectively. The OAD chip-based system was further applied in single mouse oocyte analysis, with 355 protein IDs identified at the single oocyte level, which demonstrated its special advantages of high enrichment of sequence coverage, hydrophobic proteins, and enzymatic digestion efficiency over the traditional in-tube system.

Microfluidics for Single-Cell Genetic Analysis

PubMed Central

Thompson, A. M.; Paguirigan, A. L.; Kreutz, J. E.; Radich, J. P.; Chiu, D. T.

2014-01-01

The ability to correlate single-cell genetic information to cellular phenotypes will provide the kind of detailed insight into human physiology and disease pathways that is not possible to infer from bulk cell analysis. Microfluidic technologies are attractive for single-cell manipulation due to precise handling and low risk of contamination. Additionally, microfluidic single-cell techniques can allow for high-throughput and detailed genetic analyses that increase accuracy and decreases reagent cost compared to bulk techniques. Incorporating these microfluidic platforms into research and clinical laboratory workflows can fill an unmet need in biology, delivering the highly accurate, highly informative data necessary to develop new therapies and monitor patient outcomes. In this perspective, we describe the current and potential future uses of microfluidics at all stages of single-cell genetic analysis, including cell enrichment and capture, single-cell compartmentalization and manipulation, and detection and analyses. PMID:24789374

Technical aspects and recommendations for single-cell qPCR.

PubMed

Ståhlberg, Anders; Kubista, Mikael

2018-02-01

Single cells are basic physiological and biological units that can function individually as well as in groups in tissues and organs. It is central to identify, characterize and profile single cells at molecular level to be able to distinguish different kinds, to understand their functions and determine how they interact with each other. During the last decade several technologies for single-cell profiling have been developed and used in various applications, revealing many novel findings. Quantitative PCR (qPCR) is one of the most developed methods for single-cell profiling that can be used to interrogate several analytes, including DNA, RNA and protein. Single-cell qPCR has the potential to become routine methodology but the technique is still challenging, as it involves several experimental steps and few molecules are handled. Here, we discuss technical aspects and provide recommendation for single-cell qPCR analysis. The workflow includes experimental design, sample preparation, single-cell collection, direct lysis, reverse transcription, preamplification, qPCR and data analysis. Detailed reporting and sharing of experimental details and data will promote further development and make validation studies possible. Efforts aiming to standardize single-cell qPCR open up means to move single-cell analysis from specialized research settings to standard research laboratories. Copyright © 2017 Elsevier Ltd. All rights reserved.

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots.

PubMed

Hirata, Yoshito; Oda, Arisa; Ohta, Kunihiro; Aihara, Kazuyuki

2016-10-11

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Oda, Arisa; Ohta, Kunihiro; Aihara, Kazuyuki

2016-10-01

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

Label-Free Optofluidic Nanobiosensor Enables Real-Time Analysis of Single-Cell Cytokine Secretion.

PubMed

Li, Xiaokang; Soler, Maria; Szydzik, Crispin; Khoshmanesh, Khashayar; Schmidt, Julien; Coukos, George; Mitchell, Arnan; Altug, Hatice

2018-06-01

Single-cell analysis of cytokine secretion is essential to understand the heterogeneity of cellular functionalities and develop novel therapies for multiple diseases. Unraveling the dynamic secretion process at single-cell resolution reveals the real-time functional status of individual cells. Fluorescent and colorimetric-based methodologies require tedious molecular labeling that brings inevitable interferences with cell integrity and compromises the temporal resolution. An innovative label-free optofluidic nanoplasmonic biosensor is introduced for single-cell analysis in real time. The nanobiosensor incorporates a novel design of a multifunctional microfluidic system with small volume microchamber and regulation channels for reliable monitoring of cytokine secretion from individual cells for hours. Different interleukin-2 secretion profiles are detected and distinguished from single lymphoma cells. The sensor configuration combined with optical spectroscopic imaging further allows us to determine the spatial single-cell secretion fingerprints in real time. This new biosensor system is anticipated to be a powerful tool to characterize single-cell signaling for basic and clinical research. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2017-05-02

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

Platforms for Single-Cell Collection and Analysis.

PubMed

Valihrach, Lukas; Androvic, Peter; Kubista, Mikael

2018-03-11

Single-cell analysis has become an established method to study cell heterogeneity and for rare cell characterization. Despite the high cost and technical constraints, applications are increasing every year in all fields of biology. Following the trend, there is a tremendous development of tools for single-cell analysis, especially in the RNA sequencing field. Every improvement increases sensitivity and throughput. Collecting a large amount of data also stimulates the development of new approaches for bioinformatic analysis and interpretation. However, the essential requirement for any analysis is the collection of single cells of high quality. The single-cell isolation must be fast, effective, and gentle to maintain the native expression profiles. Classical methods for single-cell isolation are micromanipulation, microdissection, and fluorescence-activated cell sorting (FACS). In the last decade several new and highly efficient approaches have been developed, which not just supplement but may fully replace the traditional ones. These new techniques are based on microfluidic chips, droplets, micro-well plates, and automatic collection of cells using capillaries, magnets, an electric field, or a punching probe. In this review we summarize the current methods and developments in this field. We discuss the advantages of the different commercially available platforms and their applicability, and also provide remarks on future developments.

Platforms for Single-Cell Collection and Analysis

PubMed Central

Valihrach, Lukas; Androvic, Peter; Kubista, Mikael

2018-01-01

Single-cell analysis has become an established method to study cell heterogeneity and for rare cell characterization. Despite the high cost and technical constraints, applications are increasing every year in all fields of biology. Following the trend, there is a tremendous development of tools for single-cell analysis, especially in the RNA sequencing field. Every improvement increases sensitivity and throughput. Collecting a large amount of data also stimulates the development of new approaches for bioinformatic analysis and interpretation. However, the essential requirement for any analysis is the collection of single cells of high quality. The single-cell isolation must be fast, effective, and gentle to maintain the native expression profiles. Classical methods for single-cell isolation are micromanipulation, microdissection, and fluorescence-activated cell sorting (FACS). In the last decade several new and highly efficient approaches have been developed, which not just supplement but may fully replace the traditional ones. These new techniques are based on microfluidic chips, droplets, micro-well plates, and automatic collection of cells using capillaries, magnets, an electric field, or a punching probe. In this review we summarize the current methods and developments in this field. We discuss the advantages of the different commercially available platforms and their applicability, and also provide remarks on future developments. PMID:29534489

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.

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.

Lessons from single-cell transcriptome analysis of oxygen-sensing cells.

PubMed

Zhou, Ting; Matsunami, Hiroaki

2018-05-01

The advent of single-cell RNA-sequencing (RNA-Seq) technology has enabled transcriptome profiling of individual cells. Comprehensive gene expression analysis at the single-cell level has proven to be effective in characterizing the most fundamental aspects of cellular function and identity. This unbiased approach is revolutionary for small and/or heterogeneous tissues like oxygen-sensing cells in identifying key molecules. Here, we review the major methods of current single-cell RNA-Seq technology. We discuss how this technology has advanced the understanding of oxygen-sensing glomus cells in the carotid body and helped uncover novel oxygen-sensing cells and mechanisms in the mice olfactory system. We conclude by providing our perspective on future single-cell RNA-Seq research directed at oxygen-sensing cells.

Novel Single-Cell Analysis Platform Based on a Solid-State Zinc-Coadsorbed Carbon Quantum Dots Electrochemiluminescence Probe for the Evaluation of CD44 Expression on Breast Cancer Cells.

PubMed

Qiu, Youyi; Zhou, Bin; Yang, Xiaojuan; Long, Dongping; Hao, Yan; Yang, Peihui

2017-05-24

A novel single-cell analysis platform was fabricated using solid-state zinc-coadsorbed carbon quantum dot (ZnCQDs) nanocomposites as an electrochemiluminescence (ECL) probe for the detection of breast cancer cells and evaluation of the CD44 expression level. Solid-state ZnCQDs nanocomposite probes were constructed through the attachment of ZnCQDs to gold nanoparticles and then the loading of magnetic beads to amplify the ECL signal, exhibiting a remarkable 120-fold enhancement of the ECL intensity. Hyaluronic acid (HA)-functionalized solid-state probes were used to label a single breast cancer cell by the specific recognition of HA with CD44 on the cell surface, revealing more stable, sensitive, and effective tagging in comparison with the water-soluble CQDs. This strategy exhibited a good analytical performance for the analysis of MDA-MB-231 and MCF-7 single cells with linear range from 1 to 18 and from 1 to 12 cells, respectively. Furthermore, this single-cell analysis platform was used for evaluation of the CD44 expression level of these two cell lines, in which the MDA-MB-231 cells revealed a 2.8-5.2-fold higher CD44 expression level. A total of 20 single cells were analyzed individually, and the distributions of the ECL intensity revealed larger variations, indicating the high cellular heterogeneity of the CD44 expression level on the same cell line. The as-proposed single-cell analysis platform might provide a novel protocol to effectively study the individual cellular function and cellular heterogeneity.

Quantitative analysis of gold nanoparticles in single cells by laser ablation inductively coupled plasma-mass spectrometry.

PubMed

Wang, Meng; Zheng, Ling-Na; Wang, Bing; Chen, Han-Qing; Zhao, Yu-Liang; Chai, Zhi-Fang; Reid, Helen J; Sharp, Barry L; Feng, Wei-Yue

2014-10-21

Single cell analysis has become an important field of research in recent years reflecting the heterogeneity of cellular responses in biological systems. Here, we demonstrate a new method, based on laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS), which can quantify in situ gold nanoparticles (Au NPs) in single cells. Dried residues of picoliter droplets ejected by a commercial inkjet printer were used to simulate matrix-matched calibration standards. The gold mass in single cells exposed to 100 nM NIST Au NPs (Reference material 8012, 30 nm) for 4 h showed a log-normal distribution, ranging from 1.7 to 72 fg Au per cell, which approximately corresponds to 9 to 370 Au NPs per cell. The average result from 70 single cells (15 ± 13 fg Au per cell) was in good agreement with the result from an aqua regia digest solution of 1.2 × 10(6) cells (18 ± 1 fg Au per cell). The limit of quantification was 1.7 fg Au. This paper demonstrates the great potential of LA-ICPMS for single cell analysis and the beneficial study of biological responses to metal drugs or NPs at the single cell level.

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.

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.

Proteomic analysis of single mammalian cells enabled by microfluidic nanodroplet sample preparation and ultrasensitive nanoLC-MS.

PubMed

Zhu, Ying; Clair, Geremy; Chrisler, William; Shen, Yufeng; Zhao, Rui; Shukla, Anil; Moore, Ronald; Misra, Ravi; Pryhuber, Gloria; Smith, Richard; Ansong, Charles; Kelly, Ryan T

2018-05-24

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analysed by ultrasensitive nanoLC-MS. An average of ~670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A polymeric micro total analysis system for single-cell analysis

NASA Astrophysics Data System (ADS)

Lai, Hsuan-Hong

The advancement of microengineering has enabled the manipulation and analysis of single cells, which is critical in understanding the molecular mechanisms underlying the basic physiological functions from the point of view of modern biologists. Unfortunately, analysis of single cells remains challenging from a technical perspective, mainly because of the miniature nature of the cell and the high throughput requirements of the analysis. Lab-on-a-chip (LOC) emerges as a research field that shows great promise in this perspective. We have demonstrated a micro total analysis system (mu-TAS) combining chip-based electrophoretic separation, fluorescence detection, and a pulsed Nd:YAG laser cell lysis system, in a Poly(dimethylsiloxane) (PDMS) microfluidic analytical platform for the implementation of single-cell analysis. To accomplish the task, a polymeric microfluidic device was fabricated and UV graft polymerization surface modification techniques were used. To optimize the conditions for the surface treatment techniques, the modified surfaces of PDMS were characterized using AIR-IR spectrum and sessile water drop contact angle measurements, and in-channel surfaces were characterized by their electroosmotic flow mobility. Accurate single-cell analysis relies on rapid cell lysis and therefore an optical measure of fast cell lysis was implemented and optimized in a microscopic station. The influences of pulse energy and the location of the laser beam with respect to the cell in the microchannel were explored. The observation from the cell disruption experiments suggested that the cell lysis was enabled mainly via a thermo-mechanical instead of a plasma-mediated mechanism. Finally, after chip-based electrophoresis and a laser-induced fluorescence (LIF) detection system were incorporated with the laser lysis system in a microfluidic analytical station, a feasibility demonstration of single-cell analysis was implemented. The analytical platform exhibited the capability of fluidic transportation, optical lysis of single cells, separation, and analysis of the lysates by electrophoresis and LIF detection. In comparison with the control experiment, the migration times of the fluorescent signals for the cytosolic fluorophores were in good agreement with those for the standard fluorophores, which confirmed the feasibility of the analytical processes.

Quantitative high-resolution genomic analysis of single cancer cells.

PubMed

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.

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

Dissecting Transcriptional Heterogeneity in Pluripotency: Single Cell Analysis of Mouse Embryonic Stem Cells.

PubMed

Guedes, Ana M V; Henrique, Domingos; Abranches, Elsa

2016-01-01

Mouse Embryonic Stem cells (mESCs) show heterogeneous and dynamic expression of important pluripotency regulatory factors. Single-cell analysis has revealed the existence of cell-to-cell variability in the expression of individual genes in mESCs. Understanding how these heterogeneities are regulated and what their functional consequences are is crucial to obtain a more comprehensive view of the pluripotent state.In this chapter we describe how to analyze transcriptional heterogeneity by monitoring gene expression of Nanog, Oct4, and Sox2, using single-molecule RNA FISH in single mESCs grown in different cell culture medium. We describe in detail all the steps involved in the protocol, from RNA detection to image acquisition and processing, as well as exploratory data analysis.

Neutralizing antibodies against West Nile virus identified directly from human B cells by single-cell analysis and next generation sequencing

PubMed Central

Tsioris, Konstantinos; Gupta, Namita T.; Ogunniyi, Adebola O.; Zimnisky, Ross M.; Qian, Feng; Yao, Yi; Wang, Xiaomei; Stern, Joel N. H.; Chari, Raj; Briggs, Adrian W.; Clouser, Christopher R.; Vigneault, Francois; Church, George M.; Garcia, Melissa N.; Murray, Kristy O.; Montgomery, Ruth R.; Kleinstein, Steven H.; Love, J. Christopher

2015-01-01

West Nile virus infection (WNV) is an emerging mosquito-borne disease that can lead to severe neurological illness and currently has no available treatment or vaccine. Using microengraving, an integrated single-cell analysis method, we analyzed a cohort of subjects infected with WNV - recently infected and post-convalescent subjects - and efficiently identified four novel WNV neutralizing antibodies. We also assessed the humoral response to WNV on a single-cell and repertoire level by integrating next generation sequencing (NGS) into our analysis. The results from single-cell analysis indicate persistence of WNV-specific memory B cells and antibody-secreting cells in post-convalescent subjects. These cells exhibited class-switched antibody isotypes. Furthermore, the results suggest that the antibody response itself does not predict the clinical severity of the disease (asymptomatic or symptomatic). Using the nucleotide coding sequences for WNV-specific antibodies derived from single cells, we revealed the ontogeny of expanded WNV-specific clones in the repertoires of recently infected subjects through NGS and bioinformatic analysis. This analysis also indicated that the humoral response to WNV did not depend on an anamnestic response, due to an unlikely previous exposure to the virus. The innovative and integrative approach presented here to analyze the evolution of neutralizing antibodies from natural infection on a single-cell and repertoire level can also be applied to vaccine studies, and could potentially aid the development of therapeutic antibodies and our basic understanding of other infectious diseases. PMID:26481611

Neutralizing antibodies against West Nile virus identified directly from human B cells by single-cell analysis and next generation sequencing.

PubMed

Tsioris, Konstantinos; Gupta, Namita T; Ogunniyi, Adebola O; Zimnisky, Ross M; Qian, Feng; Yao, Yi; Wang, Xiaomei; Stern, Joel N H; Chari, Raj; Briggs, Adrian W; Clouser, Christopher R; Vigneault, Francois; Church, George M; Garcia, Melissa N; Murray, Kristy O; Montgomery, Ruth R; Kleinstein, Steven H; Love, J Christopher

2015-12-01

West Nile virus (WNV) infection is an emerging mosquito-borne disease that can lead to severe neurological illness and currently has no available treatment or vaccine. Using microengraving, an integrated single-cell analysis method, we analyzed a cohort of subjects infected with WNV - recently infected and post-convalescent subjects - and efficiently identified four novel WNV neutralizing antibodies. We also assessed the humoral response to WNV on a single-cell and repertoire level by integrating next generation sequencing (NGS) into our analysis. The results from single-cell analysis indicate persistence of WNV-specific memory B cells and antibody-secreting cells in post-convalescent subjects. These cells exhibited class-switched antibody isotypes. Furthermore, the results suggest that the antibody response itself does not predict the clinical severity of the disease (asymptomatic or symptomatic). Using the nucleotide coding sequences for WNV-specific antibodies derived from single cells, we revealed the ontogeny of expanded WNV-specific clones in the repertoires of recently infected subjects through NGS and bioinformatic analysis. This analysis also indicated that the humoral response to WNV did not depend on an anamnestic response, due to an unlikely previous exposure to the virus. The innovative and integrative approach presented here to analyze the evolution of neutralizing antibodies from natural infection on a single-cell and repertoire level can also be applied to vaccine studies, and could potentially aid the development of therapeutic antibodies and our basic understanding of other infectious diseases.

Single cell sequencing reveals heterogeneity within ovarian cancer epithelium and cancer associated stromal cells.

PubMed

Winterhoff, Boris J; Maile, Makayla; Mitra, Amit Kumar; Sebe, Attila; Bazzaro, Martina; Geller, Melissa A; Abrahante, Juan E; Klein, Molly; Hellweg, Raffaele; Mullany, Sally A; Beckman, Kenneth; Daniel, Jerry; Starr, Timothy K

2017-03-01

The purpose of this study was to determine the level of heterogeneity in high grade serous ovarian cancer (HGSOC) by analyzing RNA expression in single epithelial and cancer associated stromal cells. In addition, we explored the possibility of identifying subgroups based on pathway activation and pre-defined signatures from cancer stem cells and chemo-resistant cells. A fresh, HGSOC tumor specimen derived from ovary was enzymatically digested and depleted of immune infiltrating cells. RNA sequencing was performed on 92 single cells and 66 of these single cell datasets passed quality control checks. Sequences were analyzed using multiple bioinformatics tools, including clustering, principle components analysis, and geneset enrichment analysis to identify subgroups and activated pathways. Immunohistochemistry for ovarian cancer, stem cell and stromal markers was performed on adjacent tumor sections. Analysis of the gene expression patterns identified two major subsets of cells characterized by epithelial and stromal gene expression patterns. The epithelial group was characterized by proliferative genes including genes associated with oxidative phosphorylation and MYC activity, while the stromal group was characterized by increased expression of extracellular matrix (ECM) genes and genes associated with epithelial-to-mesenchymal transition (EMT). Neither group expressed a signature correlating with published chemo-resistant gene signatures, but many cells, predominantly in the stromal subgroup, expressed markers associated with cancer stem cells. Single cell sequencing provides a means of identifying subpopulations of cancer cells within a single patient. Single cell sequence analysis may prove to be critical for understanding the etiology, progression and drug resistance in ovarian cancer. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Complete disassociation of adult pancreas into viable single cells through cold trypsin-EDTA digestion*

PubMed Central

Li, Dan; Peng, Shi-yun; Zhang, Zhen-wu; Feng, Rui-cheng; Li, Lu; Liang, Jie; Tai, Sheng; Teng, Chun-bo

2013-01-01

The in vitro isolation and analysis of pancreatic stem/progenitor cells are necessary for understanding their properties and function; however, the preparation of high-quality single-cell suspensions from adult pancreas is prerequisite. In this study, we applied a cold trypsin-ethylenediaminetetraacetic acid (EDTA) digestion method to disassociate adult mouse pancreata into single cells. The yield of single cells and the viability of the harvested cells were much higher than those obtained via the two commonly used warm digestion methods. Flow cytometric analysis showed that the ratio of ductal or BCRP1-positive cells in cell suspensions prepared through cold digestion was consistent with that found in vivo. Cell culture tests showed that pancreatic epithelial cells prepared by cold digestion maintained proliferative capacity comparable to those derived from warm collagenase digestion. These results indicate that cold trypsin-EDTA digestion can effectively disassociate an adult mouse pancreas into viable single cells with minimal cell loss, and can be used for the isolation and analysis of pancreatic stem/progenitor cells. PMID:23825145

New insights into human primordial germ cells and early embryonic development from single-cell analysis.

PubMed

Otte, Jörg; Wruck, Wasco; Adjaye, James

2017-08-01

Human preimplantation developmental studies are difficult to accomplish due to associated ethical and moral issues. Preimplantation cells are rare and exist only in transient cell states. From a single cell, it is very challenging to analyse the origination of the heterogeneity and complexity inherent to the human body. However, recent advances in single-cell technology and data analysis have provided new insights into the process of early human development and germ cell specification. In this Review, we examine the latest single-cell datasets of human preimplantation embryos and germ cell development, compare them to bulk cell analyses, and interpret their biological implications. © 2017 Federation of European Biochemical Societies.

Quantitative High-Resolution Genomic Analysis of Single Cancer Cells

PubMed Central

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A.; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics. PMID:22140428

Single-cell analysis and sorting using droplet-based microfluidics.

PubMed

Mazutis, Linas; Gilbert, John; Ung, W Lloyd; Weitz, David A; Griffiths, Andrew D; Heyman, John A

2013-05-01

We present a droplet-based microfluidics protocol for high-throughput analysis and sorting of single cells. Compartmentalization of single cells in droplets enables the analysis of proteins released from or secreted by cells, thereby overcoming one of the major limitations of traditional flow cytometry and fluorescence-activated cell sorting. As an example of this approach, we detail a binding assay for detecting antibodies secreted from single mouse hybridoma cells. Secreted antibodies are detected after only 15 min by co-compartmentalizing single mouse hybridoma cells, a fluorescent probe and single beads coated with anti-mouse IgG antibodies in 50-pl droplets. The beads capture the secreted antibodies and, when the captured antibodies bind to the probe, the fluorescence becomes localized on the beads, generating a clearly distinguishable fluorescence signal that enables droplet sorting at ∼200 Hz as well as cell enrichment. The microfluidic system described is easily adapted for screening other intracellular, cell-surface or secreted proteins and for quantifying catalytic or regulatory activities. In order to screen ∼1 million cells, the microfluidic operations require 2-6 h; the entire process, including preparation of microfluidic devices and mammalian cells, requires 5-7 d.

Single-cell analysis and sorting using droplet-based microfluidics

PubMed Central

Mazutis, Linas; Gilbert, John; Ung, W Lloyd; Weitz, David A; Griffiths, Andrew D; Heyman, John A

2014-01-01

We present a droplet-based microfluidics protocol for high-throughput analysis and sorting of single cells. compartmentalization of single cells in droplets enables the analysis of proteins released from or secreted by cells, thereby overcoming one of the major limitations of traditional flow cytometry and fluorescence-activated cell sorting. as an example of this approach, we detail a binding assay for detecting antibodies secreted from single mouse hybridoma cells. secreted antibodies are detected after only 15 min by co-compartmentalizing single mouse hybridoma cells, a fluorescent probe and single beads coated with anti-mouse IgG antibodies in 50-pl droplets. the beads capture the secreted antibodies and, when the captured antibodies bind to the probe, the fluorescence becomes localized on the beads, generating a clearly distinguishable fluorescence signal that enables droplet sorting at ~200 Hz as well as cell enrichment. the microfluidic system described is easily adapted for screening other intracellular, cell-surface or secreted proteins and for quantifying catalytic or regulatory activities. In order to screen ~1 million cells, the microfluidic operations require 2–6 h; the entire process, including preparation of microfluidic devices and mammalian cells, requires 5–7 d. PMID:23558786

Drop-on-Demand Single Cell Isolation and Total RNA Analysis

PubMed Central

Moon, Sangjun; Kim, Yun-Gon; Dong, Lingsheng; Lombardi, Michael; Haeggstrom, Edward; Jensen, Roderick V.; Hsiao, Li-Li; Demirci, Utkan

2011-01-01

Technologies that rapidly isolate viable single cells from heterogeneous solutions have significantly contributed to the field of medical genomics. Challenges remain both to enable efficient extraction, isolation and patterning of single cells from heterogeneous solutions as well as to keep them alive during the process due to a limited degree of control over single cell manipulation. Here, we present a microdroplet based method to isolate and pattern single cells from heterogeneous cell suspensions (10% target cell mixture), preserve viability of the extracted cells (97.0±0.8%), and obtain genomic information from isolated cells compared to the non-patterned controls. The cell encapsulation process is both experimentally and theoretically analyzed. Using the isolated cells, we identified 11 stem cell markers among 1000 genes and compare to the controls. This automated platform enabling high-throughput cell manipulation for subsequent genomic analysis employs fewer handling steps compared to existing methods. PMID:21412416

Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells.

PubMed

Wu, Liang; Zhang, Xiaolong; Zhao, Zhikun; Wang, Ling; Li, Bo; Li, Guibo; Dean, Michael; Yu, Qichao; Wang, Yanhui; Lin, Xinxin; Rao, Weijian; Mei, Zhanlong; Li, Yang; Jiang, Runze; Yang, Huan; Li, Fuqiang; Xie, Guoyun; Xu, Liqin; Wu, Kui; Zhang, Jie; Chen, Jianghao; Wang, Ting; Kristiansen, Karsten; Zhang, Xiuqing; Li, Yingrui; Yang, Huanming; Wang, Jian; Hou, Yong; Xu, Xun

2015-01-01

Viral infection causes multiple forms of human cancer, and HPV infection is the primary factor in cervical carcinomas. Recent single-cell RNA-seq studies highlight the tumor heterogeneity present in most cancers, but virally induced tumors have not been studied. HeLa is a well characterized HPV+ cervical cancer cell line. We developed a new high throughput platform to prepare single-cell RNA on a nanoliter scale based on a customized microwell chip. Using this method, we successfully amplified full-length transcripts of 669 single HeLa S3 cells and 40 of them were randomly selected to perform single-cell RNA sequencing. Based on these data, we obtained a comprehensive understanding of the heterogeneity of HeLa S3 cells in gene expression, alternative splicing and fusions. Furthermore, we identified a high diversity of HPV-18 expression and splicing at the single-cell level. By co-expression analysis we identified 283 E6, E7 co-regulated genes, including CDC25, PCNA, PLK4, BUB1B and IRF1 known to interact with HPV viral proteins. Our results reveal the heterogeneity of a virus-infected cell line. It not only provides a transcriptome characterization of HeLa S3 cells at the single cell level, but is a demonstration of the power of single cell RNA-seq analysis of virally infected cells and cancers.

A microchip electrophoresis-mass spectrometric platform with double cell lysis nano-electrodes for automated single cell analysis.

PubMed

Li, Xiangtang; Zhao, Shulin; Hu, Hankun; Liu, Yi-Ming

2016-06-17

Capillary electrophoresis-based single cell analysis has become an essential approach in researches at the cellular level. However, automation of single cell analysis has been a challenge due to the difficulty to control the number of cells injected and the irreproducibility associated with cell aggregation. Herein we report the development of a new microfluidic platform deploying the double nano-electrode cell lysis technique for automated analysis of single cells with mass spectrometric detection. The proposed microfluidic chip features integration of a cell-sized high voltage zone for quick single cell lysis, a microfluidic channel for electrophoretic separation, and a nanoelectrospray emitter for ionization in MS detection. Built upon this platform, a microchip electrophoresis-mass spectrometric method (MCE-MS) has been developed for automated single cell analysis. In the method, cell introduction, cell lysis, and MCE-MS separation are computer controlled and integrated as a cycle into consecutive assays. Analysis of large numbers of individual PC-12 neuronal cells (both intact and exposed to 25mM KCl) was carried out to determine intracellular levels of dopamine (DA) and glutamic acid (Glu). It was found that DA content in PC-12 cells was higher than Glu content, and both varied from cell to cell. The ratio of intracellular DA to Glu was 4.20±0.8 (n=150). Interestingly, the ratio drastically decreased to 0.38±0.20 (n=150) after the cells are exposed to 25mM KCl for 8min, suggesting the cells released DA promptly and heavily while they released Glu at a much slower pace in response to KCl-induced depolarization. These results indicate that the proposed MCE-MS analytical platform may have a great potential in researches at the cellular level. Copyright © 2016 Elsevier B.V. All rights reserved.

Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

2016-03-01

Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

Large-Scale Femtoliter Droplet Array for Single Cell Efflux Assay of Bacteria.

PubMed

Iino, Ryota; Sakakihara, Shouichi; Matsumoto, Yoshimi; Nishino, Kunihiko

2018-01-01

Large-scale femtoliter droplet array as a platform for single cell efflux assay of bacteria is described. Device microfabrication, femtoliter droplet array formation and concomitant enclosure of single bacterial cells, fluorescence-based detection of efflux activity at the single cell level, and collection of single cells from droplet and subsequent gene analysis are described in detail.

Decoding the Regulatory Network for Blood Development from Single-Cell Gene Expression Measurements

PubMed Central

Haghverdi, Laleh; Lilly, Andrew J.; Tanaka, Yosuke; Wilkinson, Adam C.; Buettner, Florian; Macaulay, Iain C.; Jawaid, Wajid; Diamanti, Evangelia; Nishikawa, Shin-Ichi; Piterman, Nir; Kouskoff, Valerie; Theis, Fabian J.; Fisher, Jasmin; Göttgens, Berthold

2015-01-01

Here we report the use of diffusion maps and network synthesis from state transition graphs to better understand developmental pathways from single cell gene expression profiling. We map the progression of mesoderm towards blood in the mouse by single-cell expression analysis of 3,934 cells, capturing cells with blood-forming potential at four sequential developmental stages. By adapting the diffusion plot methodology for dimensionality reduction to single-cell data, we reconstruct the developmental journey to blood at single-cell resolution. Using transitions between individual cellular states as input, we develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model that recapitulates blood development. Model predictions were validated by showing that Sox7 inhibits primitive erythropoiesis, and that Sox and Hox factors control early expression of Erg. We therefore demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that control organogenesis. PMID:25664528

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.

A microfluidic approach to parallelized transcriptional profiling of single cells.

PubMed

Sun, Hao; Olsen, Timothy; Zhu, Jing; Tao, Jianguo; Ponnaiya, Brian; Amundson, Sally A; Brenner, David J; Lin, Qiao

2015-12-01

The ability to correlate single-cell genetic information with cellular phenotypes is of great importance to biology and medicine, as it holds the potential to gain insight into disease pathways that is unavailable from ensemble measurements. We present a microfluidic approach to parallelized, rapid, quantitative analysis of messenger RNA from single cells via RT-qPCR. The approach leverages an array of single-cell RT-qPCR analysis units formed by a set of parallel microchannels concurrently controlled by elastomeric pneumatic valves, thereby enabling parallelized handling and processing of single cells in a drastically simplified operation procedure using a relatively small number of microvalves. All steps for single-cell RT-qPCR, including cell isolation and immobilization, cell lysis, mRNA purification, reverse transcription and qPCR, are integrated on a single chip, eliminating the need for off-chip manual cell and reagent transfer and qPCR amplification as commonly used in existing approaches. Additionally, the approach incorporates optically transparent microfluidic components to allow monitoring of single-cell trapping without the need for molecular labeling that can potentially alter the targeted gene expression and utilizes a polycarbonate film as a barrier against evaporation to minimize the loss of reagents at elevated temperatures during the analysis. We demonstrate the utility of the approach by the transcriptional profiling for the induction of the cyclin-dependent kinase inhibitor 1a and the glyceraldehyde 3-phosphate dehydrogenase in single cells from the MCF-7 breast cancer cell line. Furthermore, the methyl methanesulfonate is employed to allow measurement of the expression of the genes in individual cells responding to a genotoxic stress.

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.

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

Single-cell PCR of genomic DNA enabled by automated single-cell printing for cell isolation.

PubMed

Stumpf, F; Schoendube, J; Gross, A; Rath, C; Niekrawietz, S; Koltay, P; Roth, G

2015-07-15

Single-cell analysis has developed into a key topic in cell biology with future applications in personalized medicine, tumor identification as well as tumor discovery (Editorial, 2013). Here we employ inkjet-like printing to isolate individual living single human B cells (Raji cell line) and load them directly into standard PCR tubes. Single cells are optically detected in the nozzle of the microfluidic piezoelectric dispenser chip to ensure printing of droplets with single cells only. The printing process has been characterized by using microbeads (10µm diameter) resulting in a single bead delivery in 27 out of 28 cases and relative positional precision of ±350µm at a printing distance of 6mm between nozzle and tube lid. Process-integrated optical imaging enabled to identify the printing failure as void droplet and to exclude it from downstream processing. PCR of truly single-cell DNA was performed without pre-amplification directly from single Raji cells with 33% success rate (N=197) and Cq values of 36.3±2.5. Additionally single cell whole genome amplification (WGA) was employed to pre-amplify the single-cell DNA by a factor of >1000. This facilitated subsequent PCR for the same gene yielding a success rate of 64% (N=33) which will allow more sophisticated downstream analysis like sequencing, electrophoresis or multiplexing. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Gold-coated polydimethylsiloxane microwells for high-throughput electrochemiluminescence analysis of intracellular glucose at single cells.

PubMed

Xia, Juan; Zhou, Junyu; Zhang, Ronggui; Jiang, Dechen; Jiang, Depeng

2018-06-04

In this communication, a gold-coated polydimethylsiloxane (PDMS) chip with cell-sized microwells was prepared through a stamping and spraying process that was applied directly for high-throughput electrochemiluminescence (ECL) analysis of intracellular glucose at single cells. As compared with the previous multiple-step fabrication of photoresist-based microwells on the electrode, the preparation process is simple and offers fresh electrode surface for higher luminescence intensity. More luminescence intensity was recorded from cell-retained microwells than that at the planar region among the microwells that was correlated with the content of intracellular glucose. The successful monitoring of intracellular glucose at single cells using this PDMS chip will provide an alternative strategy for high-throughput single-cell analysis. Graphical abstract ᅟ.

A Minimally Invasive Method for Retrieving Single Adherent Cells of Different Types from Cultures

PubMed Central

Zeng, Jia; Mohammadreza, Aida; Gao, Weimin; Merza, Saeed; Smith, Dean; Kelbauskas, Laimonas; Meldrum, Deirdre R.

2014-01-01

The field of single-cell analysis has gained a significant momentum over the last decade. Separation and isolation of individual cells is an indispensable step in almost all currently available single-cell analysis technologies. However, stress levels introduced by such manipulations remain largely unstudied. We present a method for minimally invasive retrieval of selected individual adherent cells of different types from cell cultures. The method is based on a combination of mechanical (shear flow) force and biochemical (trypsin digestion) treatment. We quantified alterations in the transcription levels of stress response genes in individual cells exposed to varying levels of shear flow and trypsinization. We report optimal temperature, RNA preservation reagents, shear force and trypsinization conditions necessary to minimize changes in the stress-related gene expression levels. The method and experimental findings are broadly applicable and can be used by a broad research community working in the field of single cell analysis. PMID:24957932

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.

DNA-barcode directed capture and electrochemical metabolic analysis of single mammalian cells on a microelectrode array.

PubMed

Douglas, Erik S; Hsiao, Sonny C; Onoe, Hiroaki; Bertozzi, Carolyn R; Francis, Matthew B; Mathies, Richard A

2009-07-21

A microdevice is developed for DNA-barcode directed capture of single cells on an array of pH-sensitive microelectrodes for metabolic analysis. Cells are modified with membrane-bound single-stranded DNA, and specific single-cell capture is directed by the complementary strand bound in the sensor area of the iridium oxide pH microelectrodes within a microfluidic channel. This bifunctional microelectrode array is demonstrated for the pH monitoring and differentiation of primary T cells and Jurkat T lymphoma cells. Single Jurkat cells exhibited an extracellular acidification rate of 11 milli-pH min(-1), while primary T cells exhibited only 2 milli-pH min(-1). This system can be used to capture non-adherent cells specifically and to discriminate between visually similar healthy and cancerous cells in a heterogeneous ensemble based on their altered metabolic properties.

DNA-barcode directed capture and electrochemical metabolic analysis of single mammalian cells on a microelectrode array

PubMed Central

Douglas, Erik S.; Hsiao, Sonny C.; Onoe, Hiroaki; Bertozzi, Carolyn R.; Francis, Matthew B.; Mathies, Richard A.

2010-01-01

A microdevice is developed for DNA-barcode directed capture of single cells on an array of pH-sensitive microelectrodes for metabolic analysis. Cells are modified with membrane-bound single-stranded DNA, and specific single-cell capture is directed by the complementary strand bound in the sensor area of the iridium oxide pH microelectrodes within a microfluidic channel. This bifunctional microelectrode array is demonstrated for the pH monitoring and differentiation of primary T cells and Jurkat T lymphoma cells. Single Jurkat cells exhibited an extracellular acidification rate of 11 milli-pH min−1, while primary T cells exhibited only 2 milli-pH min−1. This system can be used to capture non-adherent cells specifically and to discriminate between visually similar healthy and cancerous cells in a heterogeneous ensemble based on their altered metabolic properties. PMID:19568668

Single-cell regulome data analysis by SCRAT.

PubMed

Ji, Zhicheng; Zhou, Weiqiang; Ji, Hongkai

2017-09-15

Emerging single-cell technologies (e.g. single-cell ATAC-seq, DNase-seq or ChIP-seq) have made it possible to assay regulome of individual cells. Single-cell regulome data are highly sparse and discrete. Analyzing such data is challenging. User-friendly software tools are still lacking. We present SCRAT, a Single-Cell Regulome Analysis Toolbox with a graphical user interface, for studying cell heterogeneity using single-cell regulome data. SCRAT can be used to conveniently summarize regulatory activities according to different features (e.g. gene sets, transcription factor binding motif sites, etc.). Using these features, users can identify cell subpopulations in a heterogeneous biological sample, infer cell identities of each subpopulation, and discover distinguishing features such as gene sets and transcription factors that show different activities among subpopulations. SCRAT is freely available at https://zhiji.shinyapps.io/scrat as an online web service and at https://github.com/zji90/SCRAT as an R package. hji@jhu.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

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.

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

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.

Droplet Microfluidics for Compartmentalized Cell Lysis and Extension of DNA from Single-Cells

NASA Astrophysics Data System (ADS)

Zimny, Philip; Juncker, David; Reisner, Walter

Current single cell DNA analysis methods suffer from (i) bias introduced by the need for molecular amplification and (ii) limited ability to sequence repetitive elements, resulting in (iii) an inability to obtain information regarding long range genomic features. Recent efforts to circumvent these limitations rely on techniques for sensing single molecules of DNA extracted from single-cells. Here we demonstrate a droplet microfluidic approach for encapsulation and biochemical processing of single-cells inside alginate microparticles. In our approach, single-cells are first packaged inside the alginate microparticles followed by cell lysis, DNA purification, and labeling steps performed off-chip inside this microparticle system. The alginate microparticles are then introduced inside a micro/nanofluidic system where the alginate is broken down via a chelating buffer, releasing long DNA molecules which are then extended inside nanofluidic channels for analysis via standard mapping protocols.

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.

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

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.

Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation.

PubMed

Dueck, Hannah; Khaladkar, Mugdha; Kim, Tae Kyung; Spaethling, Jennifer M; Francis, Chantal; Suresh, Sangita; Fisher, Stephen A; Seale, Patrick; Beck, Sheryl G; Bartfai, Tamas; Kuhn, Bernhard; Eberwine, James; Kim, Junhyong

2015-06-09

Differentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype. This brings into question the relationship between transcriptome states and cell phenotypes. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question. We present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We develop methods to filter genes for reliable quantification and to calibrate biological variation. All cell types include genes with high variability in expression, in a tissue-specific manner. We also find evidence that single-cell variability of neuronal genes in mice is correlated with that in rats consistent with the hypothesis that levels of variation may be conserved. Single-cell RNA-sequencing data provide a unique view of transcriptome function; however, careful analysis is required in order to use single-cell RNA-sequencing measurements for this purpose. Technical variation must be considered in single-cell RNA-sequencing studies of expression variation. For a subset of genes, biological variability within each cell type appears to be regulated in order to perform dynamic functions, rather than solely molecular noise.

Image analysis driven single-cell analytics for systems microbiology.

PubMed

Balomenos, Athanasios D; Tsakanikas, Panagiotis; Aspridou, Zafiro; Tampakaki, Anastasia P; Koutsoumanis, Konstantinos P; Manolakos, Elias S

2017-04-04

Time-lapse microscopy is an essential tool for capturing and correlating bacterial morphology and gene expression dynamics at single-cell resolution. However state-of-the-art computational methods are limited in terms of the complexity of cell movies that they can analyze and lack of automation. The proposed Bacterial image analysis driven Single Cell Analytics (BaSCA) computational pipeline addresses these limitations thus enabling high throughput systems microbiology. BaSCA can segment and track multiple bacterial colonies and single-cells, as they grow and divide over time (cell segmentation and lineage tree construction) to give rise to dense communities with thousands of interacting cells in the field of view. It combines advanced image processing and machine learning methods to deliver very accurate bacterial cell segmentation and tracking (F-measure over 95%) even when processing images of imperfect quality with several overcrowded colonies in the field of view. In addition, BaSCA extracts on the fly a plethora of single-cell properties, which get organized into a database summarizing the analysis of the cell movie. We present alternative ways to analyze and visually explore the spatiotemporal evolution of single-cell properties in order to understand trends and epigenetic effects across cell generations. The robustness of BaSCA is demonstrated across different imaging modalities and microscopy types. BaSCA can be used to analyze accurately and efficiently cell movies both at a high resolution (single-cell level) and at a large scale (communities with many dense colonies) as needed to shed light on e.g. how bacterial community effects and epigenetic information transfer play a role on important phenomena for human health, such as biofilm formation, persisters' emergence etc. Moreover, it enables studying the role of single-cell stochasticity without losing sight of community effects that may drive it.

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.

Single cell elemental analysis using nuclear microscopy

NASA Astrophysics Data System (ADS)

Ren, M. Q.; Thong, P. S. P.; Kara, U.; Watt, F.

1999-04-01

The use of Particle Induced X-ray Emission (PIXE), Rutherford Backscattering Spectrometry (RBS) and Scanning Transmission Ion Microscopy (STIM) to provide quantitative elemental analysis of single cells is an area which has high potential, particularly when the trace elements such as Ca, Fe, Zn and Cu can be monitored. We describe the methodology of sample preparation for two cell types, the procedures of cell imaging using STIM, and the quantitative elemental analysis of single cells using RBS and PIXE. Recent work on single cells at the Nuclear Microscopy Research Centre,National University of Singapore has centred around two research areas: (a) Apoptosis (programmed cell death), which has been recently implicated in a wide range of pathological conditions such as cancer, Parkinson's disease etc, and (b) Malaria (infection of red blood cells by the malaria parasite). Firstly we present results on the elemental analysis of human Chang liver cells (ATTCC CCL 13) where vanadium ions were used to trigger apoptosis, and demonstrate that nuclear microscopy has the capability of monitoring vanadium loading within individual cells. Secondly we present the results of elemental changes taking place in individual mouse red blood cells which have been infected with the malaria parasite and treated with the anti-malaria drug Qinghaosu (QHS).

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

PubMed

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

2015-04-16

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

Calibrating genomic and allelic coverage bias in single-cell sequencing

PubMed Central

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

2016-01-01

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

Evaluation of the Cow Rumen Metagenome: Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Sczyrba, Alex

2018-02-13

DOE JGI's Alex Sczyrba on "Evaluation of the Cow Rumen Metagenome" and "Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Evaluation of the Cow Rumen Metagenome: Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

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

Sczyrba, Alex

2011-10-13

DOE JGI's Alex Sczyrba on "Evaluation of the Cow Rumen Metagenome" and "Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Automated single cell microbioreactor for monitoring intracellular dynamics and cell growth in free solution†

PubMed Central

Johnson-Chavarria, Eric M.; Agrawal, Utsav; Tanyeri, Melikhan; Kuhlman, Thomas E.

2014-01-01

We report an automated microfluidic-based platform for single cell analysis that allows for cell culture in free solution with the ability to control the cell growth environment. Using this approach, cells are confined by the sole action of gentle fluid flow, thereby enabling non-perturbative analysis of cell growth away from solid boundaries. In addition, the single cell microbioreactor allows for precise and time-dependent control over cell culture media, with the combined ability to observe the dynamics of non-adherent cells over long time scales. As a proof-of-principle demonstration, we used the platform to observe dynamic cell growth, gene expression, and intracellular diffusion of repressor proteins while precisely tuning the cell growth environment. Overall, this microfluidic approach enables the direct observation of cellular dynamics with exquisite control over environmental conditions, which will be useful for quantifying the behaviour of single cells in well-defined media. PMID:24836754

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

Design of a large-scale femtoliter droplet array for single-cell analysis of drug-tolerant and drug-resistant bacteria.

PubMed

Iino, Ryota; Matsumoto, Yoshimi; Nishino, Kunihiko; Yamaguchi, Akihito; Noji, Hiroyuki

2013-01-01

Single-cell analysis is a powerful method to assess the heterogeneity among individual cells, enabling the identification of very rare cells with properties that differ from those of the majority. In this Methods Article, we describe the use of a large-scale femtoliter droplet array to enclose, isolate, and analyze individual bacterial cells. As a first example, we describe the single-cell detection of drug-tolerant persisters of Pseudomonas aeruginosa treated with the antibiotic carbenicillin. As a second example, this method was applied to the single-cell evaluation of drug efflux activity, which causes acquired antibiotic resistance of bacteria. The activity of the MexAB-OprM multidrug efflux pump system from Pseudomonas aeruginosa was expressed in Escherichia coli and the effect of an inhibitor D13-9001 were assessed at the single cell level.

Analysis of single mammalian cells on-chip.

PubMed

Sims, Christopher E; Allbritton, Nancy L

2007-04-01

A goal of modern biology is to understand the molecular mechanisms underlying cellular function. The ability to manipulate and analyze single cells is crucial for this task. The advent of microengineering is providing biologists with unprecedented opportunities for cell handling and investigation on a cell-by-cell basis. For this reason, lab-on-a-chip (LOC) technologies are emerging as the next revolution in tools for biological discovery. In the current discussion, we seek to summarize the state of the art for conventional technologies in use by biologists for the analysis of single, mammalian cells, and then compare LOC devices engineered for these same single-cell studies. While a review of the technical progress is included, a major goal is to present the view point of the practicing biologist and the advances that might increase adoption by these individuals. The LOC field is expanding rapidly, and we have focused on areas of broad interest to the biology community where the technology is sufficiently far advanced to contemplate near-term application in biological experimentation. Focus areas to be covered include flow cytometry, electrophoretic analysis of cell contents, fluorescent-indicator-based analyses, cells as small volume reactors, control of the cellular microenvironment, and single-cell PCR.

Single-cell mRNA profiling reveals transcriptional heterogeneity among pancreatic circulating tumour cells.

PubMed

Lapin, Morten; Tjensvoll, Kjersti; Oltedal, Satu; Javle, Milind; Smaaland, Rune; Gilje, Bjørnar; Nordgård, Oddmund

2017-05-31

Single-cell mRNA profiling of circulating tumour cells may contribute to a better understanding of the biology of these cells and their role in the metastatic process. In addition, such analyses may reveal new knowledge about the mechanisms underlying chemotherapy resistance and tumour progression in patients with cancer. Single circulating tumour cells were isolated from patients with locally advanced or metastatic pancreatic cancer with immuno-magnetic depletion and immuno-fluorescence microscopy. mRNA expression was analysed with single-cell multiplex RT-qPCR. Hierarchical clustering and principal component analysis were performed to identify expression patterns. Circulating tumour cells were detected in 33 of 56 (59%) examined blood samples. Single-cell mRNA profiling of intact isolated circulating tumour cells revealed both epithelial-like and mesenchymal-like subpopulations, which were distinct from leucocytes. The profiled circulating tumour cells also expressed elevated levels of stem cell markers, and the extracellular matrix protein, SPARC. The expression of SPARC might correspond to an epithelial-mesenchymal transition in pancreatic circulating tumour cells. The analysis of single pancreatic circulating tumour cells identified distinct subpopulations and revealed elevated expression of transcripts relevant to the dissemination of circulating tumour cells to distant organ sites.

Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists.

PubMed

Zhu, Xun; Wolfgruber, Thomas K; Tasato, Austin; Arisdakessian, Cédric; Garmire, David G; Garmire, Lana X

2017-12-05

Single-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level. Computational methods to process scRNA-Seq data are not very accessible to bench scientists as they require a significant amount of bioinformatic skills. We have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene-expression normalization, imputation, gene filtering, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction. Granatum enables broad adoption of scRNA-Seq technology by empowering bench scientists with an easy-to-use graphical interface for scRNA-Seq data analysis. The package is freely available for research use at http://garmiregroup.org/granatum/app.

Chemical imaging of molecular changes in a hydrated single cell by dynamic secondary ion mass spectrometry and super-resolution microscopy

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

Hua, Xin; Szymanski, Craig; Wang, Zhaoying

2016-01-01

Chemical imaging of single cells is important in capturing biological dynamics. Single cell correlative imaging is realized between structured illumination microscopy (SIM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) using System for Analysis at the Liquid Vacuum Interface (SALVI), a multimodal microreactor. SIM characterized cells and guided subsequent ToF-SIMS analysis. Dynamic ToF-SIMS provided time- and space-resolved cell molecular mapping. Lipid fragments were identified in the hydrated cell membrane. Principal component analysis was used to elucidate chemical component differences among mouse lung cells that uptake zinc oxide nanoparticles. Our results provided submicron chemical spatial mapping for investigations of cell dynamics atmore » the molecular level.« less

Transcriptome In Vivo Analysis (TIVA) of spatially defined single cells in intact live mouse and human brain tissue

PubMed Central

Lovatt, Ditte; Ruble, Brittani K.; Lee, Jaehee; Dueck, Hannah; Kim, Tae Kyung; Fisher, Stephen; Francis, Chantal; Spaethling, Jennifer M.; Wolf, John A.; Grady, M. Sean; Ulyanova, Alexandra V.; Yeldell, Sean B.; Griepenburg, Julianne C.; Buckley, Peter T.; Kim, Junhyong; Sul, Jai-Yoon; Dmochowski, Ivan J.; Eberwine, James

2014-01-01

Transcriptome profiling is an indispensable tool in advancing the understanding of single cell biology, but depends upon methods capable of isolating mRNA at the spatial resolution of a single cell. Current capture methods lack sufficient spatial resolution to isolate mRNA from individual in vivo resident cells without damaging adjacent tissue. Because of this limitation, it has been difficult to assess the influence of the microenvironment on the transcriptome of individual neurons. Here, we engineered a Transcriptome In Vivo Analysis (TIVA)-tag, which upon photoactivation enables mRNA capture from single cells in live tissue. Using the TIVA-tag in combination with RNA-seq to analyze transcriptome variance among single dispersed cells and in vivo resident mouse and human neurons, we show that the tissue microenvironment shapes the transcriptomic landscape of individual cells. The TIVA methodology provides the first noninvasive approach for capturing mRNA from single cells in their natural microenvironment. PMID:24412976

Dielectrophoretic Capture and Genetic Analysis of Single Neuroblastoma Tumor Cells

PubMed Central

Carpenter, Erica L.; Rader, JulieAnn; Ruden, Jacob; Rappaport, Eric F.; Hunter, Kristen N.; Hallberg, Paul L.; Krytska, Kate; O’Dwyer, Peter J.; Mosse, Yael P.

2014-01-01

Our understanding of the diversity of cells that escape the primary tumor and seed micrometastases remains rudimentary, and approaches for studying circulating and disseminated tumor cells have been limited by low throughput and sensitivity, reliance on single parameter sorting, and a focus on enumeration rather than phenotypic and genetic characterization. Here, we utilize a highly sensitive microfluidic and dielectrophoretic approach for the isolation and genetic analysis of individual tumor cells. We employed fluorescence labeling to isolate 208 single cells from spiking experiments conducted with 11 cell lines, including 8 neuroblastoma cell lines, and achieved a capture sensitivity of 1 tumor cell per 106 white blood cells (WBCs). Sample fixation or freezing had no detectable effect on cell capture. Point mutations were accurately detected in the whole genome amplification product of captured single tumor cells but not in negative control WBCs. We applied this approach to capture 144 single tumor cells from 10 bone marrow samples of patients suffering from neuroblastoma. In this pediatric malignancy, high-risk patients often exhibit wide-spread hematogenous metastasis, but access to primary tumor can be difficult or impossible. Here, we used flow-based sorting to pre-enrich samples with tumor involvement below 0.02%. For all patients for whom a mutation in the Anaplastic Lymphoma Kinase gene had already been detected in their primary tumor, the same mutation was detected in single cells from their marrow. These findings demonstrate a novel, non-invasive, and adaptable method for the capture and genetic analysis of single tumor cells from cancer patients. PMID:25133137

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

PubMed

Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

2010-01-01

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

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.

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.

Enrichment and single-cell analysis of circulating tumor cells

PubMed Central

Song, Yanling; Tian, Tian; Shi, Yuanzhi; Liu, Wenli; Zou, Yuan; Khajvand, Tahereh; Wang, Sili; Zhu, Zhi

2017-01-01

Up to 90% of cancer-related deaths are caused by metastatic cancer. Circulating tumor cells (CTCs), a type of cancer cell that spreads through the blood after detaching from a solid tumor, are essential for the establishment of distant metastasis for a given cancer. As a new type of liquid biopsy, analysis of CTCs offers the possibility to avoid invasive tissue biopsy procedures with practical implications for diagnostics. The fundamental challenges of analyzing and profiling CTCs are the extremely low abundances of CTCs in the blood and the intrinsic heterogeneity of CTCs. Various technologies have been proposed for the enrichment and single-cell analysis of CTCs. This review aims to provide in-depth insights into CTC analysis, including various techniques for isolation of CTCs with capture methods based on physical and biochemical principles, and single-cell analysis of CTCs at the genomic, proteomic and phenotypic level, as well as current developmental trends and promising research directions. PMID:28451298

From Molecules to Cells to Organisms: Understanding Health and Disease with Multidimensional Single-Cell Methods

NASA Astrophysics Data System (ADS)

Candia, Julián

2013-03-01

The multidimensional nature of many single-cell measurements (e.g. multiple markers measured simultaneously using Fluorescence-Activated Cell Sorting (FACS) technologies) offers unprecedented opportunities to unravel emergent phenomena that are governed by the cooperative action of multiple elements across different scales, from molecules and proteins to cells and organisms. We will discuss an integrated analysis framework to investigate multicolor FACS data from different perspectives: Singular Value Decomposition to achieve an effective dimensional reduction in the data representation, machine learning techniques to separate different patient classes and improve diagnosis, as well as a novel cell-similarity network analysis method to identify cell subpopulations in an unbiased manner. Besides FACS data, this framework is versatile: in this vein, we will demonstrate an application to the multidimensional single-cell shape analysis of healthy and prematurely aged cells.

High-efficiency single cell encapsulation and size selective capture of cells in picoliter droplets based on hydrodynamic micro-vortices.

PubMed

Kamalakshakurup, Gopakumar; Lee, Abraham P

2017-12-05

Single cell analysis has emerged as a paradigm shift in cell biology to understand the heterogeneity of individual cells in a clone for pathological interrogation. Microfluidic droplet technology is a compelling platform to perform single cell analysis by encapsulating single cells inside picoliter-nanoliter (pL-nL) volume droplets. However, one of the primary challenges for droplet based single cell assays is single cell encapsulation in droplets, currently achieved either randomly, dictated by Poisson statistics, or by hydrodynamic techniques. In this paper, we present an interfacial hydrodynamic technique which initially traps the cells in micro-vortices, and later releases them one-to-one into the droplets, controlled by the width of the outer streamline that separates the vortex from the flow through the streaming passage adjacent to the aqueous-oil interface (d gap ). One-to-one encapsulation is achieved at a d gap equal to the radius of the cell, whereas complete trapping of the cells is realized at a d gap smaller than the radius of the cell. The unique feature of this technique is that it can perform 1. high efficiency single cell encapsulations and 2. size-selective capturing of cells, at low cell loading densities. Here we demonstrate these two capabilities with a 50% single cell encapsulation efficiency and size selective separation of platelets, RBCs and WBCs from a 10× diluted blood sample (WBC capture efficiency at 70%). The results suggest a passive, hydrodynamic micro-vortex based technique capable of performing high-efficiency single cell encapsulation for cell based assays.

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

PubMed

Matsumoto, Hirotaka; Kiryu, Hisanori

2016-06-08

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

Single cells for forensic DNA analysis--from evidence material to test tube.

PubMed

Brück, Simon; Evers, Heidrun; Heidorn, Frank; Müller, Ute; Kilper, Roland; Verhoff, Marcel A

2011-01-01

The purpose of this project was to develop a method that, while providing morphological quality control, allows single cells to be obtained from the surfaces of various evidence materials and be made available for DNA analysis in cases where only small amounts of cell material are present or where only mixed traces are found. With the SteREO Lumar.V12 stereomicroscope and UV unit from Zeiss, it was possible to detect and assess single epithelial cells on the surfaces of various objects (e.g., glass, plastic, metal). A digitally operated micromanipulator developed by aura optik was used to lift a single cell from the surface of evidence material and to transfer it to a conventional PCR tube or to an AmpliGrid(®) from Advalytix. The actual lifting of the cells was performed with microglobes that acted as carriers. The microglobes were held with microtweezers and were transferred to the DNA analysis receptacles along with the adhering cells. In a next step, the PCR can be carried out in this receptacle without removing the microglobe. Our method allows a single cell to be isolated directly from evidence material and be made available for forensic DNA analysis. © 2010 American Academy of Forensic Sciences.

Tunable Single-Cell Extraction for Molecular Analyses.

PubMed

Guillaume-Gentil, Orane; Grindberg, Rashel V; Kooger, Romain; Dorwling-Carter, Livie; Martinez, Vincent; Ossola, Dario; Pilhofer, Martin; Zambelli, Tomaso; Vorholt, Julia A

2016-07-14

Because of cellular heterogeneity, the analysis of endogenous molecules from single cells is of significant interest and has major implications. While micromanipulation or cell sorting followed by cell lysis is already used for subsequent molecular examinations, approaches to directly extract the content of living cells remain a challenging but promising alternative to achieving non-destructive sampling and cell-context preservation. Here, we demonstrate the quantitative extraction from single cells with spatiotemporal control using fluidic force microscopy. We further present a comprehensive analysis of the soluble molecules withdrawn from the cytoplasm or the nucleus, including the detection of enzyme activities and transcript abundances. This approach has uncovered the ability of cells to withstand extraction of up to several picoliters and opens opportunities to study cellular dynamics and cell-cell communication under physiological conditions at the single-cell level. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Voltage controlled nano-injection system for single-cell surgery

PubMed Central

Seger, R. Adam; Actis, Paolo; Penfold, Catherine; Maalouf, Michelle; Vilozny, Boaz; Pourmand, Nader

2015-01-01

Manipulation and analysis of single cells is the next frontier in understanding processes that control the function and fate of cells. Herein we describe a single-cell injection platform based on nanopipettes. The system uses scanning microscopy techniques to detect cell surfaces, and voltage pulses to deliver molecules into individual cells. As a proof of concept, we injected adherent mammalian cells with fluorescent dyes. PMID:22899383

Voltage controlled nano-injection system for single-cell surgery.

PubMed

Adam Seger, R; Actis, Paolo; Penfold, Catherine; Maalouf, Michelle; Vilozny, Boaz; Pourmand, Nader

2012-09-28

Manipulation and analysis of single cells is the next frontier in understanding processes that control the function and fate of cells. Herein we describe a single-cell injection platform based on nanopipettes. The system uses scanning microscopy techniques to detect cell surfaces, and voltage pulses to deliver molecules into individual cells. As a proof of concept, we injected adherent mammalian cells with fluorescent dyes.

Technologies for Single-Cell Isolation

PubMed Central

Gross, Andre; Schoendube, Jonas; Zimmermann, Stefan; Steeb, Maximilian; Zengerle, Roland; Koltay, Peter

2015-01-01

The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting) respectively Flow cytometry (33% usage), laser microdissection (17%), manual cell picking (17%), random seeding/dilution (15%), and microfluidics/lab-on-a-chip devices (12%) are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field. PMID:26213926

Technologies for Single-Cell Isolation.

PubMed

Gross, Andre; Schoendube, Jonas; Zimmermann, Stefan; Steeb, Maximilian; Zengerle, Roland; Koltay, Peter

2015-07-24

The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting) respectively Flow cytometry (33% usage), laser microdissection (17%), manual cell picking (17%), random seeding/dilution (15%), and microfluidics/lab-on-a-chip devices (12%) are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field.

Quantitative biology of single neurons

PubMed Central

Eberwine, James; Lovatt, Ditte; Buckley, Peter; Dueck, Hannah; Francis, Chantal; Kim, Tae Kyung; Lee, Jaehee; Lee, Miler; Miyashiro, Kevin; Morris, Jacqueline; Peritz, Tiina; Schochet, Terri; Spaethling, Jennifer; Sul, Jai-Yoon; Kim, Junhyong

2012-01-01

The building blocks of complex biological systems are single cells. Fundamental insights gained from single-cell analysis promise to provide the framework for understanding normal biological systems development as well as the limits on systems/cellular ability to respond to disease. The interplay of cells to create functional systems is not well understood. Until recently, the study of single cells has concentrated primarily on morphological and physiological characterization. With the application of new highly sensitive molecular and genomic technologies, the quantitative biochemistry of single cells is now accessible. PMID:22915636

Massively parallel single-molecule and single-cell emulsion reverse transcription polymerase chain reaction using agarose droplet microfluidics.

PubMed

Zhang, Huifa; Jenkins, Gareth; Zou, Yuan; Zhu, Zhi; Yang, Chaoyong James

2012-04-17

A microfluidic device for performing single copy, emulsion Reverse Transcription Polymerase Chain Reaction (RT-PCR) within agarose droplets is presented. A two-aqueous-inlet emulsion droplet generator was designed and fabricated to produce highly uniform monodisperse picoliter agarose emulsion droplets with RT-PCR reagents in carrier oil. Template RNA or cells were delivered from one inlet with RT-PCR reagents/cell lysis buffer delivered separately from the other. Efficient RNA/cell encapsulation and RT-PCR at the single copy level was achieved in agarose-in-oil droplets, which, after amplification, can be solidified into agarose beads for further analysis. A simple and efficient method to graft primer to the polymer matrix using 5'-acrydite primer was developed to ensure highly efficient trapping of RT-PCR products in agarose. High-throughput single RNA molecule/cell RT-PCR was demonstrated in stochastically diluted solutions. Our results indicate that single-molecule RT-PCR can be efficiently carried out in agarose matrix. Single-cell RT-PCR was successfully performed which showed a clear difference in gene expression level of EpCAM, a cancer biomarker gene, at the single-cell level between different types of cancer cells. This work clearly demonstrates for the first time, single-copy RT-PCR in agarose droplets. We believe this will open up new possibilities for viral RNA detection and single-cell transcription analysis.

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

Printing 2-dimentional droplet array for single-cell reverse transcription quantitative PCR assay with a microfluidic robot.

PubMed

Zhu, Ying; Zhang, Yun-Xia; Liu, Wen-Wen; Ma, Yan; Fang, Qun; Yao, Bo

2015-04-01

This paper describes a nanoliter droplet array-based single-cell reverse transcription quantitative PCR (RT-qPCR) assay method for quantifying gene expression in individual cells. By sequentially printing nanoliter-scale droplets on microchip using a microfluidic robot, all liquid-handling operations including cell encapsulation, lysis, reverse transcription, and quantitative PCR with real-time fluorescence detection, can be automatically achieved. The inhibition effect of cell suspension buffer on RT-PCR assay was comprehensively studied to achieve high-sensitivity gene quantification. The present system was applied in the quantitative measurement of expression level of mir-122 in single Huh-7 cells. A wide distribution of mir-122 expression in single cells from 3061 copies/cell to 79998 copies/cell was observed, showing a high level of cell heterogeneity. With the advantages of full-automation in liquid-handling, simple system structure, and flexibility in achieving multi-step operations, the present method provides a novel liquid-handling mode for single cell gene expression analysis, and has significant potentials in transcriptional identification and rare cell analysis.

Printing 2-Dimentional Droplet Array for Single-Cell Reverse Transcription Quantitative PCR Assay with a Microfluidic Robot

PubMed Central

Zhu, Ying; Zhang, Yun-Xia; Liu, Wen-Wen; Ma, Yan; Fang, Qun; Yao, Bo

2015-01-01

This paper describes a nanoliter droplet array-based single-cell reverse transcription quantitative PCR (RT-qPCR) assay method for quantifying gene expression in individual cells. By sequentially printing nanoliter-scale droplets on microchip using a microfluidic robot, all liquid-handling operations including cell encapsulation, lysis, reverse transcription, and quantitative PCR with real-time fluorescence detection, can be automatically achieved. The inhibition effect of cell suspension buffer on RT-PCR assay was comprehensively studied to achieve high-sensitivity gene quantification. The present system was applied in the quantitative measurement of expression level of mir-122 in single Huh-7 cells. A wide distribution of mir-122 expression in single cells from 3061 copies/cell to 79998 copies/cell was observed, showing a high level of cell heterogeneity. With the advantages of full-automation in liquid-handling, simple system structure, and flexibility in achieving multi-step operations, the present method provides a novel liquid-handling mode for single cell gene expression analysis, and has significant potentials in transcriptional identification and rare cell analysis. PMID:25828383

Analysis of gene expression in single live neurons.

PubMed Central

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

1992-01-01

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

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.

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

PubMed

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

2017-11-02

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

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

PubMed Central

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

2017-01-01

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

Highly Multiplexed, Single Cell Transcriptomic Analysis of T-Cells by Microfluidic PCR.

PubMed

Dominguez, Maria; Roederer, Mario; Chattopadhyay, Pratip K

2017-01-01

Recently, technologies have been developed to measure expression of 96 (or more) mRNA transcripts at once from a single cell. Here we describe methods and important considerations for use of Fluidigm's BioMark platform for multiplexed single cell gene expression. We describe how to qualify primer/probes, select genes to examine in 96-parameter panels, perform the reverse transcription/cDNA synthesis step, and operate the instrument. In addition, we describe data analysis considerations. This technology has enormous value for characterizing the heterogeneity of T-cells, thereby providing a useful tool for immune monitoring.

Single-cell high resolution melting analysis: A novel, generic, pre-implantation genetic diagnosis (PGD) method applied to cystic fibrosis (HRMA CF-PGD).

PubMed

Destouni, A; Poulou, M; Kakourou, G; Vrettou, C; Tzetis, M; Traeger-Synodinos, J; Kitsiou-Tzeli, S

2016-03-01

Institutions offering CF-PGD face the challenge of developing and optimizing single cell genotyping protocols that should cover for the extremely heterogeneous CF mutation spectrum. Here we report the development and successful clinical application of a generic CF-PGD protocol to facilitate direct detection of any CFTR nucleotide variation(s) by HRMA and simultaneous confirmation of diagnosis through haplotype analysis. A multiplex PCR was optimized supporting co-amplification of any CFTR exon-region, along with 6 closely linked STRs. Single cell genotypes were established through HRM analysis following melting of the 2nd round PCR products and were confirmed by STR haplotype analysis of the 1st PCR products. The protocol was validated pre-clinically, by testing 208 single lymphocytes, isolated from whole blood samples from 4 validation family trios. Fifteen PGD cycles were performed and 103 embryos were biopsied. In 15 clinical PGD cycles, genotypes were achieved in 88/93 (94.6%) embryo biopsy samples, of which 57/88 (64.8%) were deemed genetically suitable for embryo transfer. Amplification failed at all loci for 10/103 blastomeres biopsied from poor quality embryos. Six clinical pregnancies were achieved (2 twin, 4 singletons). PGD genotypes were confirmed following conventional amniocentesis or chorionic villus sampling in all achieved pregnancies. The single cell HRMA CF-PGD protocol described herein is a flexible, generic, low cost and robust genotyping method, which facilitates the analysis of any CFTR genotype combination. Single-cell HRMA can be beneficial to other clinical settings, for example the detection of single nucleotide variants in single cells derived from clinical tumor samples. Copyright © 2015 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

77 FR 21788 - Center for Scientific Review Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-11

... Development, Stem Cell and Myocardial Regeneration. Date: May 10, 2012. Time: 2 p.m. to 3:30 p.m. Agenda: To... for Scientific Review Special Emphasis Panel; RFA Panel: Single Cell Analysis Reviews. Date: May 8... for Scientific Review Special Emphasis Panel; RFA Panel: Single Cell Analysis Reviews. Date: May 9...

Hydrodynamic lift for single cell manipulation in a femtosecond laser fabricated optofluidic chip

NASA Astrophysics Data System (ADS)

Bragheri, Francesca; Osellame, Roberto

2017-08-01

Single cell sorting based either on fluorescence or on mechanical properties has been exploited in the last years in microfluidic devices. Hydrodynamic focusing allows increasing the efficiency of theses devices by improving the matching between the region of optical analysis and that of cell flow. Here we present a very simple solution fabricated by femtosecond laser micromachining that exploits flow laminarity in microfluidic channels to easily lift the sample flowing position to the channel portion illuminated by the optical waveguides used for single cell trapping and analysis.

Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing.

PubMed

Tang, Qin; Iyer, Sowmya; Lobbardi, Riadh; Moore, John C; Chen, Huidong; Lareau, Caleb; Hebert, Christine; Shaw, McKenzie L; Neftel, Cyril; Suva, Mario L; Ceol, Craig J; Bernards, Andre; Aryee, Martin; Pinello, Luca; Drummond, Iain A; Langenau, David M

2017-10-02

Recent advances in single-cell, transcriptomic profiling have provided unprecedented access to investigate cell heterogeneity during tissue and organ development. In this study, we used massively parallel, single-cell RNA sequencing to define cell heterogeneity within the zebrafish kidney marrow, constructing a comprehensive molecular atlas of definitive hematopoiesis and functionally distinct renal cells found in adult zebrafish. Because our method analyzed blood and kidney cells in an unbiased manner, our approach was useful in characterizing immune-cell deficiencies within DNA-protein kinase catalytic subunit ( prkdc ), interleukin-2 receptor γ a ( il2rga ), and double-homozygous-mutant fish, identifying blood cell losses in T, B, and natural killer cells within specific genetic mutants. Our analysis also uncovered novel cell types, including two classes of natural killer immune cells, classically defined and erythroid-primed hematopoietic stem and progenitor cells, mucin-secreting kidney cells, and kidney stem/progenitor cells. In total, our work provides the first, comprehensive, single-cell, transcriptomic analysis of kidney and marrow cells in the adult zebrafish. © 2017 Tang et al.

Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing

PubMed Central

Iyer, Sowmya; Lobbardi, Riadh; Chen, Huidong; Hebert, Christine; Shaw, McKenzie L.; Neftel, Cyril; Suva, Mario L.; Bernards, Andre; Aryee, Martin; Drummond, Iain A.

2017-01-01

Recent advances in single-cell, transcriptomic profiling have provided unprecedented access to investigate cell heterogeneity during tissue and organ development. In this study, we used massively parallel, single-cell RNA sequencing to define cell heterogeneity within the zebrafish kidney marrow, constructing a comprehensive molecular atlas of definitive hematopoiesis and functionally distinct renal cells found in adult zebrafish. Because our method analyzed blood and kidney cells in an unbiased manner, our approach was useful in characterizing immune-cell deficiencies within DNA–protein kinase catalytic subunit (prkdc), interleukin-2 receptor γ a (il2rga), and double-homozygous–mutant fish, identifying blood cell losses in T, B, and natural killer cells within specific genetic mutants. Our analysis also uncovered novel cell types, including two classes of natural killer immune cells, classically defined and erythroid-primed hematopoietic stem and progenitor cells, mucin-secreting kidney cells, and kidney stem/progenitor cells. In total, our work provides the first, comprehensive, single-cell, transcriptomic analysis of kidney and marrow cells in the adult zebrafish. PMID:28878000

Application of porous metal enrichment probe sampling to single cell analysis using matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS).

PubMed

Fu, Qiang; Tang, Jun; Cui, Meng; Xing, Junpeng; Liu, Zhiqiang; Liu, Shuying

2016-01-01

There is an increasing need for analyzing metabolism in a single cell, which is important to understand the nature of cellular heterogeneity, disease, growth and specialization, etc. However, single cell analysis is often challenging for the traces of samples. In the present study, porous metal enrichment probe sampling combined with matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) has been applied for in situ analysis of live onion epidemic cell. Porous probe, treated by corroding copper wire with HCl, was directly inserted into a single cell to get cell solution. A self-made linear actuator was enough to control the penetration of probe into the target cell accurately. Then samples on the tip of probe were eluted and detected by a commercial MALDI-TOF-MS directly. The formation of porous microstructure on the probe surface increased the adsorptive capacity of cell solution. The sensitivity of porous probe sampling was 6 times higher than uncorroded probes generally. This method provides a sensitive and convenient way for the sampling and detection of single cell solution. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 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.

Non-biased and efficient global amplification of a single-cell cDNA library

PubMed Central

Huang, Huan; Goto, Mari; Tsunoda, Hiroyuki; Sun, Lizhou; Taniguchi, Kiyomi; Matsunaga, Hiroko; Kambara, Hideki

2014-01-01

Analysis of single-cell gene expression promises a more precise understanding of molecular mechanisms of a living system. Most techniques only allow studies of the expressions for limited numbers of gene species. When amplification of cDNA was carried out for analysing more genes, amplification biases were frequently reported. A non-biased and efficient global-amplification method, which uses a single-cell cDNA library immobilized on beads, was developed for analysing entire gene expressions for single cells. Every step in this analysis from reverse transcription to cDNA amplification was optimized. By removing degrading excess primers, the bias due to the digestion of cDNA was prevented. Since the residual reagents, which affect the efficiency of each subsequent reaction, could be removed by washing beads, the conditions for uniform and maximized amplification of cDNAs were achieved. The differences in the amplification rates for randomly selected eight genes were within 1.5-folds, which could be negligible for most of the applications of single-cell analysis. The global amplification gives a large amount of amplified cDNA (>100 μg) from a single cell (2-pg mRNA), and that amount is enough for downstream analysis. The proposed global-amplification method was used to analyse transcript ratios of multiple cDNA targets (from several copies to several thousand copies) quantitatively. PMID:24141095

Practical, microfabrication-free device for single-cell isolation.

PubMed

Lin, Liang-I; Chao, Shih-Hui; Meldrum, Deirdre R

2009-08-21

Microfabricated devices have great potential in cell-level studies, but are not easily accessible for the broad biology community. This paper introduces the Microscale Oil-Covered Cell Array (MOCCA) as a low-cost device for high throughput single-cell analysis that can be easily produced by researchers without microengineering knowledge. Instead of using microfabricated structures to capture cells, MOCCA isolates cells in discrete aqueous droplets that are separated by oil on patterned hydrophilic areas across a relatively more hydrophobic substrate. The number of randomly seeded Escherichia coli bacteria in each discrete droplet approaches single-cell levels. The cell distribution on MOCCA is well-fit with Poisson distribution. In this pioneer study, we created an array of 900-picoliter droplets. The total time needed to seed cells in approximately 3000 droplets was less than 10 minutes. Compared to traditional microfabrication techniques, MOCCA dramatically lowers the cost of microscale cell arrays, yet enhances the fabrication and operational efficiency for single-cell analysis.

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.

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

Using a nanopore for single molecule detection and single cell transfection.

PubMed

Nelson, Edward M; Kurz, Volker; Shim, Jiwook; Timp, Winston; Timp, Gregory

2012-07-07

We assert that it is possible to trap and identify proteins, and even (conceivably) manipulate proteins secreted from a single cell (i.e. the secretome) through transfection via electroporation by exploiting the exquisite control over the electrostatic potential available in a nanopore. These capabilities may be leveraged for single cell analysis and transfection with single molecule resolution, ultimately enabling a careful scrutiny of tissue heterogeneity.

Soft-state biomicrofluidic pulse generator for single cell analysis

NASA Astrophysics Data System (ADS)

Sabounchi, Poorya; Ionescu-Zanetti, Cristian; Chen, Roger; Karandikar, Manjiree; Seo, Jeonggi; Lee, Luke P.

2006-05-01

We present the design, fabrication, and characterization of a soft-state biomicrofluidic pulse generator for single cell analysis. Hydrodynamic cell trapping via lateral microfluidic junctions allows the trapping of single cells from a bulk suspension. Microfluidic injection sites adjacent to the cell-trapping channels enable the pulsed delivery of nanoliter volumes of biochemical reagent. We demonstrated the application and removal of reagent at a frequency of 10Hz with a rise time of less than 33ms and a reagent consumption rate of 0.2nL/s. It is shown that this system operates as a low-pass filter with a cutoff frequency of 7Hz.

Application of single-cell technology in cancer research.

PubMed

Liang, Shao-Bo; Fu, Li-Wu

2017-07-01

In this review, we have outlined the application of single-cell technology in cancer research. Single-cell technology has made encouraging progress in recent years and now provides the means to detect rare cancer cells such as circulating tumor cells and cancer stem cells. We reveal how this technology has advanced the analysis of intratumor heterogeneity and tumor epigenetics, and guided individualized treatment strategies. The future prospects now are to bring single-cell technology into the clinical arena. We believe that the clinical application of single-cell technology will be beneficial in cancer diagnostics and treatment, and ultimately improve survival in cancer patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Single-cell MALDI-MS as an analytical tool for studying intrapopulation metabolic heterogeneity of unicellular organisms.

PubMed

Amantonico, Andrea; Urban, Pawel L; Fagerer, Stephan R; Balabin, Roman M; Zenobi, Renato

2010-09-01

Heterogeneity is a characteristic feature of all populations of living organisms. Here we make an attempt to validate a single-cell mass spectrometric method for detection of changes in metabolite levels occurring in populations of unicellular organisms. Selected metabolites involved in central metabolism (ADP, ATP, GTP, and UDP-Glucose) could readily be detected in single cells of Closterium acerosum by means of negative-mode matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS). The analytical capabilities of this approach were characterized using standard compounds. The method was then used to study populations of individual cells with different levels of the chosen metabolites. With principal component analysis and support vector machine algorithms, it was possible to achieve a clear separation of individual C. acerosum cells in different metabolic states. This study demonstrates the suitability of mass spectrometric analysis of metabolites in single cells to measure cell-population heterogeneity.

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.

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.

Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex.

PubMed

Pollen, Alex A; Nowakowski, Tomasz J; Shuga, Joe; Wang, Xiaohui; Leyrat, Anne A; Lui, Jan H; Li, Nianzhen; Szpankowski, Lukasz; Fowler, Brian; Chen, Peilin; Ramalingam, Naveen; Sun, Gang; Thu, Myo; Norris, Michael; Lebofsky, Ronald; Toppani, Dominique; Kemp, Darnell W; Wong, Michael; Clerkson, Barry; Jones, Brittnee N; Wu, Shiquan; Knutsson, Lawrence; Alvarado, Beatriz; Wang, Jing; Weaver, Lesley S; May, Andrew P; Jones, Robert C; Unger, Marc A; Kriegstein, Arnold R; West, Jay A A

2014-10-01

Large-scale surveys of single-cell gene expression have the potential to reveal rare cell populations and lineage relationships but require efficient methods for cell capture and mRNA sequencing. Although cellular barcoding strategies allow parallel sequencing of single cells at ultra-low depths, the limitations of shallow sequencing have not been investigated directly. By capturing 301 single cells from 11 populations using microfluidics and analyzing single-cell transcriptomes across downsampled sequencing depths, we demonstrate that shallow single-cell mRNA sequencing (~50,000 reads per cell) is sufficient for unbiased cell-type classification and biomarker identification. In the developing cortex, we identify diverse cell types, including multiple progenitor and neuronal subtypes, and we identify EGR1 and FOS as previously unreported candidate targets of Notch signaling in human but not mouse radial glia. Our strategy establishes an efficient method for unbiased analysis and comparison of cell populations from heterogeneous tissue by microfluidic single-cell capture and low-coverage sequencing of many cells.

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

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

PubMed

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

2018-02-21

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

Single-cell analysis by ICP-MS/MS as a fast tool for cellular bioavailability studies of arsenite.

PubMed

Meyer, S; López-Serrano, A; Mitze, H; Jakubowski, N; Schwerdtle, T

2018-01-24

Single-cell inductively coupled plasma mass spectrometry (SC-ICP-MS) has become a powerful and fast tool to evaluate the elemental composition at a single-cell level. In this study, the cellular bioavailability of arsenite (incubation of 25 and 50 μM for 0-48 h) has been successfully assessed by SC-ICP-MS/MS for the first time directly after re-suspending the cells in water. This procedure avoids the normally arising cell membrane permeabilization caused by cell fixation methods (e.g. methanol fixation). The reliability and feasibility of this SC-ICP-MS/MS approach with a limit of detection of 0.35 fg per cell was validated by conventional bulk ICP-MS/MS analysis after cell digestion and parallel measurement of sulfur and phosphorus.

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 Microgels: Technology, Challenges, and Applications.

PubMed

Kamperman, Tom; Karperien, Marcel; Le Gac, Séverine; Leijten, Jeroen

2018-04-12

Single-cell-laden microgels effectively act as the engineered counterpart of the smallest living building block of life: a cell within its pericellular matrix. Recent breakthroughs have enabled the encapsulation of single cells in sub-100-μm microgels to provide physiologically relevant microniches with minimal mass transport limitations and favorable pharmacokinetic properties. Single-cell-laden microgels offer additional unprecedented advantages, including facile manipulation, culture, and analysis of individual cell within 3D microenvironments. Therefore, single-cell microgel technology is expected to be instrumental in many life science applications, including pharmacological screenings, regenerative medicine, and fundamental biological research. In this review, we discuss the latest trends, technical challenges, and breakthroughs, and present our vision of the future of single-cell microgel technology and its applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Going single but not solo with podocytes: potentials, limitations, and pitfalls of single-cell analysis.

PubMed

Schiffer, Mario

2017-11-01

Single-cell RNA-sequence (RNA-seq) is a widely used tool to study biological questions in single cells. The discussed study identified 92 genes being predominantly expressed in podocytes based on a 5-fold higher expression compared with endothelial and mesangial cells. In addition to technical pitfalls, the question that is discussed in this commentary is whether results of a single-cell RNAseq study are able to deliver expression data that truly characterize a podocyte. Copyright © 2017 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Beyond the bulk: disclosing the life of single microbial cells

PubMed Central

Rosenthal, Katrin; Oehling, Verena

2017-01-01

Abstract Microbial single cell analysis has led to discoveries that are beyond what can be resolved with population-based studies. It provides a pristine view of the mechanisms that organize cellular physiology, unbiased by population heterogeneity or uncontrollable environmental impacts. A holistic description of cellular functions at the single cell level requires analytical concepts beyond the miniaturization of existing technologies, defined but uncontrolled by the biological system itself. This review provides an overview of the latest advances in single cell technologies and demonstrates their potential. Opportunities and limitations of single cell microbiology are discussed using selected application-related examples. PMID:29029257

Applications of Single-Cell Sequencing for Multiomics.

PubMed

Xu, Yungang; Zhou, Xiaobo

2018-01-01

Single-cell sequencing interrogates the sequence or chromatin information from individual cells with advanced next-generation sequencing technologies. It provides a higher resolution of cellular differences and a better understanding of the underlying genetic and epigenetic mechanisms of an individual cell in the context of its survival and adaptation to microenvironment. However, it is more challenging to perform single-cell sequencing and downstream data analysis, owing to the minimal amount of starting materials, sample loss, and contamination. In addition, due to the picogram level of the amount of nucleic acids used, heavy amplification is often needed during sample preparation of single-cell sequencing, resulting in the uneven coverage, noise, and inaccurate quantification of sequencing data. All these unique properties raise challenges in and thus high demands for computational methods that specifically fit single-cell sequencing data. We here comprehensively survey the current strategies and challenges for multiple single-cell sequencing, including single-cell transcriptome, genome, and epigenome, beginning with a brief introduction to multiple sequencing techniques for single cells.

Metabolic flux ratio analysis and cell staining suggest the existence of C4 photosynthesis in Phaeodactylum tricornutum.

PubMed

Huang, A; Liu, L; Zhao, P; Yang, C; Wang, G C

2016-03-01

Mechanisms for carbon fixation via photosynthesis in the diatom Phaeodactylum tricornutum Bohlin were studied recently but there remains a long-standing debate concerning the occurrence of C4 photosynthesis in this species. A thorough investigation of carbon metabolism and the evidence for C4 photosynthesis based on organelle partitioning was needed. In this study, we identified the flux ratios between C3 and C4 compounds in P. tricornutum using (13)C-labelling metabolic flux ratio analysis, and stained cells with various cell-permeant fluorescent probes to investigate the likely organelle partitioning required for single-cell C4 photosynthesis. Metabolic flux ratio analysis indicated the C3/C4 exchange ratios were high. Cell staining indicated organelle partitioning required for single-cell C4 photosynthesis might exist in P. tricornutum. The results of (13)C-labelling metabolic flux ratio analysis and cell staining suggest single-cell C4 photosynthesis exists in P. tricornutum. This study provides insights into photosynthesis patterns of P. tricornutum and the evidence for C4 photosynthesis based on (13)C-labelling metabolic flux ratio analysis and organelle partitioning. © 2015 The Society for Applied Microbiology.

Nanoarchaeota, Their Sulfolobales Host, and Nanoarchaeota Virus Distribution across Yellowstone National Park Hot Springs

PubMed Central

Munson-McGee, Jacob H.; Field, Erin K.; Bateson, Mary; Rooney, Colleen; Stepanauskas, Ramunas

2015-01-01

Nanoarchaeota are obligate symbionts with reduced genomes first described from marine thermal vent environments. Here, both community metagenomics and single-cell analysis revealed the presence of Nanoarchaeota in high-temperature (∼90°C), acidic (pH ≈ 2.5 to 3.0) hot springs in Yellowstone National Park (YNP) (United States). Single-cell genome analysis of two cells resulted in two nearly identical genomes, with an estimated full length of 650 kbp. Genome comparison showed that these two cells are more closely related to the recently proposed Nanobsidianus stetteri from a more neutral YNP hot spring than to the marine Nanoarchaeum equitans. Single-cell and catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) analysis of environmental hot spring samples identified the host of the YNP Nanoarchaeota as a Sulfolobales species known to inhabit the hot springs. Furthermore, we demonstrate that Nanoarchaeota are widespread in acidic to near neutral hot springs in YNP. An integrated viral sequence was also found within one Nanoarchaeota single-cell genome and further analysis of the purified viral fraction from environmental samples indicates that this is likely a virus replicating within the YNP Nanoarchaeota. PMID:26341207

Single-Cell RNA Sequencing of the Bronchial Epithelium in Smokers with Lung Cancer

DTIC Science & Technology

2017-07-01

and to discuss library preparations protocols and data analysis techniques. The goal is to develop a single cell sequencing analysis toolkit . In...Research Support LUNGevity Career Development Award What other organizations were involved as partners? Organization Name: Broad Institute 19

Pulsed Direct Current Electrospray: Enabling Systematic Analysis of Small Volume Sample by Boosting Sample Economy.

PubMed

Wei, Zhenwei; Xiong, Xingchuang; Guo, Chengan; Si, Xingyu; Zhao, Yaoyao; He, Muyi; Yang, Chengdui; Xu, Wei; Tang, Fei; Fang, Xiang; Zhang, Sichun; Zhang, Xinrong

2015-11-17

We had developed pulsed direct current electrospray ionization mass spectrometry (pulsed-dc-ESI-MS) for systematically profiling and determining components in small volume sample. Pulsed-dc-ESI utilized constant high voltage to induce the generation of single polarity pulsed electrospray remotely. This method had significantly boosted the sample economy, so as to obtain several minutes MS signal duration from merely picoliter volume sample. The elongated MS signal duration enable us to collect abundant MS(2) information on interested components in a small volume sample for systematical analysis. This method had been successfully applied for single cell metabolomics analysis. We had obtained 2-D profile of metabolites (including exact mass and MS(2) data) from single plant and mammalian cell, concerning 1034 components and 656 components for Allium cepa and HeLa cells, respectively. Further identification had found 162 compounds and 28 different modification groups of 141 saccharides in a single Allium cepa cell, indicating pulsed-dc-ESI a powerful tool for small volume sample systematical analysis.

Single-Cell RNA-Sequencing in Glioma.

PubMed

Johnson, Eli; Dickerson, Katherine L; Connolly, Ian D; Hayden Gephart, Melanie

2018-04-10

In this review, we seek to summarize the literature concerning the use of single-cell RNA-sequencing for CNS gliomas. Single-cell analysis has revealed complex tumor heterogeneity, subpopulations of proliferating stem-like cells and expanded our view of tumor microenvironment influence in the disease process. Although bulk RNA-sequencing has guided our initial understanding of glioma genetics, this method does not accurately define the heterogeneous subpopulations found within these tumors. Single-cell techniques have appealing applications in cancer research, as diverse cell types and the tumor microenvironment have important implications in therapy. High cost and difficult protocols prevent widespread use of single-cell RNA-sequencing; however, continued innovation will improve accessibility and expand our of knowledge gliomas.

Single-cell whole exome and targeted sequencing in NPM1/FLT3 positive pediatric acute myeloid leukemia.

PubMed

Walter, Christiane; Pozzorini, Christian; Reinhardt, Katarina; Geffers, Robert; Xu, Zhenyu; Reinhardt, Dirk; von Neuhoff, Nils; Hanenberg, Helmut

2018-02-01

The small portion of leukemic stem cells (LSCs) in acute myeloid leukemia (AML) present in children and adolescents is often masked by the high background of AML blasts and normal hematopoietic cells. The aim of the current study was to establish a simple workflow for reliable genetic analysis of single LSC-enriched blasts from pediatric patients. For three AMLs with mutations in nucleophosmin 1 and/or fms-like tyrosine kinase 3, we performed whole genome amplification on sorted single-cell DNA followed by whole exome sequencing (WES). The corresponding bulk bone marrow DNAs were also analyzed by WES and by targeted sequencing (TS) that included 54 genes associated with myeloid malignancies. Analysis revealed that read coverage statistics were comparable between single-cell and bulk WES data, indicating high-quality whole genome amplification. From 102 single-cell variants, 72 single nucleotide variants and insertions or deletions (70%) were consistently found in the two bulk DNA analyses. Variants reliably detected in single cells were also present in TS. However, initial screening by WES with read counts between 50-72× failed to detect rare AML subclones in the bulk DNAs. In summary, our study demonstrated that single-cell WES combined with bulk DNA TS is a promising tool set for detecting AML subclones and possibly LSCs. © 2017 Wiley Periodicals, Inc.

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.

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

PubMed

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

2016-05-31

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

Single cell transcriptomic analysis of prostate cancer cells.

PubMed

Welty, Christopher J; Coleman, Ilsa; Coleman, Roger; Lakely, Bryce; Xia, Jing; Chen, Shu; Gulati, Roman; Larson, Sandy R; Lange, Paul H; Montgomery, Bruce; Nelson, Peter S; Vessella, Robert L; Morrissey, Colm

2013-02-16

The ability to interrogate circulating tumor cells (CTC) and disseminated tumor cells (DTC) is restricted by the small number detected and isolated (typically <10). To determine if a commercially available technology could provide a transcriptomic profile of a single prostate cancer (PCa) cell, we clonally selected and cultured a single passage of cell cycle synchronized C4-2B PCa cells. Ten sets of single, 5-, or 10-cells were isolated using a micromanipulator under direct visualization with an inverted microscope. Additionally, two groups of 10 individual DTC, each isolated from bone marrow of 2 patients with metastatic PCa were obtained. RNA was amplified using the WT-Ovation™ One-Direct Amplification System. The amplified material was hybridized on a 44K Whole Human Gene Expression Microarray. A high stringency threshold, a mean Alexa Fluor® 3 signal intensity above 300, was used for gene detection. Relative expression levels were validated for select genes using real-time PCR (RT-qPCR). Using this approach, 22,410, 20,423, and 17,009 probes were positive on the arrays from 10-cell pools, 5-cell pools, and single-cells, respectively. The sensitivity and specificity of gene detection on the single-cell analyses were 0.739 and 0.972 respectively when compared to 10-cell pools, and 0.814 and 0.979 respectively when compared to 5-cell pools, demonstrating a low false positive rate. Among 10,000 randomly selected pairs of genes, the Pearson correlation coefficient was 0.875 between the single-cell and 5-cell pools and 0.783 between the single-cell and 10-cell pools. As expected, abundant transcripts in the 5- and 10-cell samples were detected by RT-qPCR in the single-cell isolates, while lower abundance messages were not. Using the same stringency, 16,039 probes were positive on the patient single-cell arrays. Cluster analysis showed that all 10 DTC grouped together within each patient. A transcriptomic profile can be reliably obtained from a single cell using commercially available technology. As expected, fewer amplified genes are detected from a single-cell sample than from pooled-cell samples, however this method can be used to reliably obtain a transcriptomic profile from DTC isolated from the bone marrow of patients with PCa.

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.

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.

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.

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.

Cryo-imaging of fluorescently labeled single cells in a mouse

NASA Astrophysics Data System (ADS)

Steyer, Grant J.; Roy, Debashish; Salvado, Olivier; Stone, Meredith E.; Wilson, David L.

2009-02-01

We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryoimaging system consists of a fluorescence microscope, robotic imaging positioner, customized cryostat, PC-based control system, and visualization/analysis software. The system alternates between sectioning (10-40 μm) and imaging, collecting color brightfield and fluorescent blockface image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells, GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation parameters were found [uT : heart (267 +/- 47.6 μm), liver (218 +/- 27.1 μm), brain (161 +/- 27.4 μm)] to be within the range of estimates in the literature. "Next image" processing removed subsurface fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and analysis of 200 microsphere images in the brain gave 97+/-2% reduction of subsurface fluorescence. Fluorescent signals were determined to arise from single cells based upon geometric and integrated intensity measurements. Next image processing greatly improved axial resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells with connected component analysis by up to 24%. Analysis of image volumes identified metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere distribution correlated with blood flow patterns. We developed and evaluated cryo-imaging to provide single-cell detection of fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB), micron-scale, fluorescence, and bright field image data. Here we describe our image preprocessing, analysis, and visualization techniques. Processing improves axial resolution, reduces subsurface fluorescence by 97%, and enables single cell detection and counting. High quality 3D volume renderings enable us to evaluate cell distribution patterns. Applications include the myriad of biomedical experiments using fluorescent reporter gene and exogenous fluorophore labeling of cells in applications such as stem cell regenerative medicine, cancer, tissue engineering, etc.

Single-Cell Sequencing Technology in Oncology: Applications for Clinical Therapies and Research.

PubMed

Ye, Baixin; Gao, Qingping; Zeng, Zhi; Stary, Creed M; Jian, Zhihong; Xiong, Xiaoxing; Gu, Lijuan

2016-01-01

Cellular heterogeneity is a fundamental characteristic of many cancers. A lack of cellular homogeneity contributes to difficulty in designing targeted oncological therapies. Therefore, the development of novel methods to determine and characterize oncologic cellular heterogeneity is a critical next step in the development of novel cancer therapies. Single-cell sequencing (SCS) technology has been recently employed for analyzing the genetic polymorphisms of individual cells at the genome-wide level. SCS requires (1) precise isolation of the single cell of interest; (2) isolation and amplification of genetic material; and (3) descriptive analysis of genomic, transcriptomic, and epigenomic data. In addition to targeted analysis of single cells isolated from tumor biopsies, SCS technology may be applied to circulating tumor cells, which may aid in predicting tumor progression and metastasis. In this paper, we provide an overview of SCS technology and review the current literature on the potential application of SCS to clinical oncology and research.

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.

Time-resolved, single-cell analysis of induced and programmed cell death via non-invasive propidium iodide and counterstain perfusion.

PubMed

Krämer, Christina E M; Wiechert, Wolfgang; Kohlheyer, Dietrich

2016-09-01

Conventional propidium iodide (PI) staining requires the execution of multiple steps prior to analysis, potentially affecting assay results as well as cell vitality. In this study, this multistep analysis method has been transformed into a single-step, non-toxic, real-time method via live-cell imaging during perfusion with 0.1 μM PI inside a microfluidic cultivation device. Dynamic PI staining was an effective live/dead analytical tool and demonstrated consistent results for single-cell death initiated by direct or indirect triggers. Application of this method for the first time revealed the apparent antibiotic tolerance of wild-type Corynebacterium glutamicum cells, as indicated by the conversion of violet fluorogenic calcein acetoxymethyl ester (CvAM). Additional implementation of this method provided insight into the induced cell lysis of Escherichia coli cells expressing a lytic toxin-antitoxin module, providing evidence for non-lytic cell death and cell resistance to toxin production. Finally, our dynamic PI staining method distinguished necrotic-like and apoptotic-like cell death phenotypes in Saccharomyces cerevisiae among predisposed descendants of nutrient-deprived ancestor cells using PO-PRO-1 or green fluorogenic calcein acetoxymethyl ester (CgAM) as counterstains. The combination of single-cell cultivation, fluorescent time-lapse imaging, and PI perfusion facilitates spatiotemporally resolved observations that deliver new insights into the dynamics of cellular behaviour.

Microfluidics cell sample preparation for analysis: Advances in efficient cell enrichment and precise single cell capture

PubMed Central

Bian, Shengtai; Cheng, Yinuo; Shi, Guanya; Liu, Peng; Ye, Xiongying

2017-01-01

Single cell analysis has received increasing attention recently in both academia and clinics, and there is an urgent need for effective upstream cell sample preparation. Two extremely challenging tasks in cell sample preparation—high-efficiency cell enrichment and precise single cell capture—have now entered into an era full of exciting technological advances, which are mostly enabled by microfluidics. In this review, we summarize the category of technologies that provide new solutions and creative insights into the two tasks of cell manipulation, with a focus on the latest development in the recent five years by highlighting the representative works. By doing so, we aim both to outline the framework and to showcase example applications of each task. In most cases for cell enrichment, we take circulating tumor cells (CTCs) as the target cells because of their research and clinical importance in cancer. For single cell capture, we review related technologies for many kinds of target cells because the technologies are supposed to be more universal to all cells rather than CTCs. Most of the mentioned technologies can be used for both cell enrichment and precise single cell capture. Each technology has its own advantages and specific challenges, which provide opportunities for researchers in their own area. Overall, these technologies have shown great promise and now evolve into real clinical applications. PMID:28217240

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.

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.

Study of living single cells in culture: automated recognition of cell behavior.

PubMed

Bodin, P; Papin, S; Meyer, C; Travo, P

1988-07-01

An automated system capable of analyzing the behavior, in real time, of single living cells in culture, in a noninvasive and nondestructive way, has been developed. A large number of cell positions in single culture dishes were recorded using a computer controlled, robotized microscope. During subsequent observations, binary images obtained from video image analysis of the microscope visual field allowed the identification of the recorded cells. These cells could be revisited automatically every few minutes. Long-term studies of the behavior of cells make possible the analysis of cellular locomotary and mitotic activities as well as determination of cell shape (chosen from a defined library) for several hours or days in a fully automated way with observations spaced up to 30 minutes. Short-term studies of the behavior of cells permit the study, in a semiautomatic way, of acute effects of drugs (5 to 15 minutes) on changes of surface area and length of cells.

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

Photocleavable DNA Barcoding Antibodies for Multiplexed Protein Analysis in Single Cells.

PubMed

Ullal, Adeeti V; Weissleder, Ralph

2015-01-01

We describe a DNA-barcoded antibody sensing technique for single cell protein analysis in which the barcodes are photocleaved and digitally detected without amplification steps (Ullal et al., Sci Transl Med 6:219, 2014). After photocleaving the unique ~70 mer DNA barcodes we use a fluorescent hybridization technology for detection, similar to what is commonly done for nucleic acid readouts. This protocol offers a simple method for multiplexed protein detection using 100+ antibodies and can be performed on clinical samples as well as single cells.

Proximity-Based Differential Single-Cell Analysis of the Niche to Identify Stem/Progenitor Cell Regulators.

PubMed

Silberstein, Lev; Goncalves, Kevin A; Kharchenko, Peter V; Turcotte, Raphael; Kfoury, Youmna; Mercier, Francois; Baryawno, Ninib; Severe, Nicolas; Bachand, Jacqueline; Spencer, Joel A; Papazian, Ani; Lee, Dongjun; Chitteti, Brahmananda Reddy; Srour, Edward F; Hoggatt, Jonathan; Tate, Tiffany; Lo Celso, Cristina; Ono, Noriaki; Nutt, Stephen; Heino, Jyrki; Sipilä, Kalle; Shioda, Toshihiro; Osawa, Masatake; Lin, Charles P; Hu, Guo-Fu; Scadden, David T

2016-10-06

Physiological stem cell function is regulated by secreted factors produced by niche cells. In this study, we describe an unbiased approach based on the differential single-cell gene expression analysis of mesenchymal osteolineage cells close to, and further removed from, hematopoietic stem/progenitor cells (HSPCs) to identify candidate niche factors. Mesenchymal cells displayed distinct molecular profiles based on their relative location. We functionally examined, among the genes that were preferentially expressed in proximal cells, three secreted or cell-surface molecules not previously connected to HSPC biology-the secreted RNase angiogenin, the cytokine IL18, and the adhesion molecule Embigin-and discovered that all of these factors are HSPC quiescence regulators. Therefore, our proximity-based differential single-cell approach reveals molecular heterogeneity within niche cells and can be used to identify novel extrinsic stem/progenitor cell regulators. Similar approaches could also be applied to other stem cell/niche pairs to advance the understanding of microenvironmental regulation of stem cell function. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Characteristics of allelic gene expression in human brain cells from single-cell RNA-seq data analysis.

PubMed

Zhao, Dejian; Lin, Mingyan; Pedrosa, Erika; Lachman, Herbert M; Zheng, Deyou

2017-11-10

Monoallelic expression of autosomal genes has been implicated in human psychiatric disorders. However, there is a paucity of allelic expression studies in human brain cells at the single cell and genome wide levels. In this report, we reanalyzed a previously published single-cell RNA-seq dataset from several postmortem human brains and observed pervasive monoallelic expression in individual cells, largely in a random manner. Examining single nucleotide variants with a predicted functional disruption, we found that the "damaged" alleles were overall expressed in fewer brain cells than their counterparts, and at a lower level in cells where their expression was detected. We also identified many brain cell type-specific monoallelically expressed genes. Interestingly, many of these cell type-specific monoallelically expressed genes were enriched for functions important for those brain cell types. In addition, function analysis showed that genes displaying monoallelic expression and correlated expression across neuronal cells from different individual brains were implicated in the regulation of synaptic function. Our findings suggest that monoallelic gene expression is prevalent in human brain cells, which may play a role in generating cellular identity and neuronal diversity and thus increasing the complexity and diversity of brain cell functions.

Expanding the horizons for single-cell applications on lab-on-a-chip devices.

PubMed

Kim, Soo Hyeon; Fourmy, Dominique; Fujii, Teruo

2012-01-01

Stochastic events in gene expression, protein synthesis, and metabolite synthesis or degradation lead to cellular heterogeneity essential to life. In a tissue as we see in organs, there is strong heterogeneity among the constituting cells critical to its function. Thus, there exists a strong demand to develop new micro/nanosystems that would enable us to conduct single-cell analysis. This field is rapidly growing, as exemplified below with recent emerging technologies that now reveal sensitive single-cell "omics" analysis. We describe in the review some of the most promising technologies that will certainly transform our view of biology in the near future.

Multifunctional picoliter droplet manipulation platform and its application in single cell analysis.

PubMed

Gu, Shu-Qing; Zhang, Yun-Xia; Zhu, Ying; Du, Wen-Bin; Yao, Bo; Fang, Qun

2011-10-01

We developed an automated and multifunctional microfluidic platform based on DropLab to perform flexible generation and complex manipulations of picoliter-scale droplets. Multiple manipulations including precise droplet generation, sequential reagent merging, and multistep solid-phase extraction for picoliter-scale droplets could be achieved in the present platform. The system precision in generating picoliter-scale droplets was significantly improved by minimizing the thermo-induced fluctuation of flow rate. A novel droplet fusion technique based on the difference of droplet interfacial tensions was developed without the need of special microchannel networks or external devices. It enabled sequential addition of reagents to droplets on demand for multistep reactions. We also developed an effective picoliter-scale droplet splitting technique with magnetic actuation. The difficulty in phase separation of magnetic beads from picoliter-scale droplets due to the high interfacial tension was overcome using ferromagnetic particles to carry the magnetic beads to pass through the phase interface. With this technique, multistep solid-phase extraction was achieved among picoliter-scale droplets. The present platform had the ability to perform complex multistep manipulations to picoliter-scale droplets, which is particularly required for single cell analysis. Its utility and potentials in single cell analysis were preliminarily demonstrated in achieving high-efficiency single-cell encapsulation, enzyme activity assay at the single cell level, and especially, single cell DNA purification based on solid-phase extraction.

High-content analysis of single cells directly assembled on CMOS sensor based on color imaging.

PubMed

Tanaka, Tsuyoshi; Saeki, Tatsuya; Sunaga, Yoshihiko; Matsunaga, Tadashi

2010-12-15

A complementary metal oxide semiconductor (CMOS) image sensor was applied to high-content analysis of single cells which were assembled closely or directly onto the CMOS sensor surface. The direct assembling of cell groups on CMOS sensor surface allows large-field (6.66 mm×5.32 mm in entire active area of CMOS sensor) imaging within a second. Trypan blue-stained and non-stained cells in the same field area on the CMOS sensor were successfully distinguished as white- and blue-colored images under white LED light irradiation. Furthermore, the chemiluminescent signals of each cell were successfully visualized as blue-colored images on CMOS sensor only when HeLa cells were placed directly on the micro-lens array of the CMOS sensor. Our proposed approach will be a promising technique for real-time and high-content analysis of single cells in a large-field area based on color imaging. Copyright © 2010 Elsevier B.V. All rights reserved.

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.

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

Label-free cell-cycle analysis by high-throughput quantitative phase time-stretch imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mok, Aaron T. Y.; Lee, Kelvin C. M.; Wong, Kenneth K. Y.; Tsia, Kevin K.

2018-02-01

Biophysical properties of cells could complement and correlate biochemical markers to characterize a multitude of cellular states. Changes in cell size, dry mass and subcellular morphology, for instance, are relevant to cell-cycle progression which is prevalently evaluated by DNA-targeted fluorescence measurements. Quantitative-phase microscopy (QPM) is among the effective biophysical phenotyping tools that can quantify cell sizes and sub-cellular dry mass density distribution of single cells at high spatial resolution. However, limited camera frame rate and thus imaging throughput makes QPM incompatible with high-throughput flow cytometry - a gold standard in multiparametric cell-based assay. Here we present a high-throughput approach for label-free analysis of cell cycle based on quantitative-phase time-stretch imaging flow cytometry at a throughput of > 10,000 cells/s. Our time-stretch QPM system enables sub-cellular resolution even at high speed, allowing us to extract a multitude (at least 24) of single-cell biophysical phenotypes (from both amplitude and phase images). Those phenotypes can be combined to track cell-cycle progression based on a t-distributed stochastic neighbor embedding (t-SNE) algorithm. Using multivariate analysis of variance (MANOVA) discriminant analysis, cell-cycle phases can also be predicted label-free with high accuracy at >90% in G1 and G2 phase, and >80% in S phase. We anticipate that high throughput label-free cell cycle characterization could open new approaches for large-scale single-cell analysis, bringing new mechanistic insights into complex biological processes including diseases pathogenesis.

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

PubMed

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

2018-04-05

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

The role of nanotechnology in single-cell detection: a review.

PubMed

Wang, Changling; Zhang, Yuxiang; Xia, Mingdian; Zhu, Xingxi; Qi, Shitao; Shen, Huaqiang; Liu, Tiebing; Tang, Liming

2014-10-01

Biological processes in single cells, such as signal transduction, DNA duplication, and protein synthesis and trafficking, occur in subcellular compartments at nanoscale level. Achieving high spatial-temporal resolution, high sensitivity, and high specificity in single-cell detection poses a great challenge. Nanotechnology, which has been widely applied in the fields of medicine, electronics, biomaterials, and energy production, has the potential to provide solutions for single-cell detection. Here we present a review of the use of nanotechnology in single-cell detection over the past two decades. First, we review the main areas of scientific interest, including morphology, ion concentration, DNA, RNA, protein, intracellular temperature, elements, and mechanical properties. Second, four categories of application of nanotechnology to single-cell detection are described: nanomanipulation, nanodevices, nanomaterials as labels, and nano Secondary ion mass spectrometry. Finally, the prospects and future trends in single-cell detection and analysis are discussed.

Chemistry and Biology in Femtoliter and Picoliter Volume Droplets

PubMed Central

Chiu, Daniel T.; Lorenz, Robert M.

2009-01-01

Conspectus The basic unit of any biological system is the cell, and malfunctions at the single-cell level can result in devastating diseases; in cancer metastasis, for example, a single cell seeds the formation of a distant tumor. Although tiny, a cell is a highly heterogeneous and compartmentalized structure: proteins, lipids, RNA, and small-molecule metabolites constantly traffic among intracellular organelles. Gaining detailed information about the spatiotemporal distribution of these biomolecules is crucial to our understanding of cellular function and dysfunction. To access this information, we need sensitive tools that are capable of extracting comprehensive biochemical information from single cells and subcellular organelles. In this Account, we outline our approach and highlight our progress towards mapping the spatiotemporal organization of information flow in single cells. Our technique is centered on the use of femtoliter- and picoliter-sized droplets as nanolabs for manipulating single cells and subcellular compartments. We have developed a single-cell nanosurgical technique for isolating select subcellular structures from live cells, a capability that is needed for the high-resolution manipulation and chemical analysis of single cells. Our microfluidic approaches for generating single femtoliter-sized droplets on demand include both pressure and electric field methods; we have also explored a design for the on-demand generation of multiple aqueous droplets to increase throughput. Droplet formation is only the first step in a sequence that requires manipulation, fusion, transport, and analysis. Optical approaches provide the most convenient and precise control over the formed droplets with our technology platform; we describe aqueous droplet manipulation with optical vortex traps, which enable the remarkable ability to dynamically “tune” the concentration of the contents. Integration of thermoelectric manipulations with these techniques affords further control. The amount of chemical information that can be gleaned from single cells and organelles is critically dependent on the methods available for analyzing droplet contents. We describe three techniques we have developed: (i) droplet encapsulation, rapid cell lysis, and fluorescence-based single-cell assays, (ii) physical sizing of the subcellular organelles and nanoparticles in droplets, and (iii) capillary electrophoresis (CE) analysis of droplet contents. For biological studies, we are working to integrate the different components of our technology into a robust, automated device; we are also addressing an anticipated need for higher throughput. With progress in these areas, we hope to cement our technique as a new tool for studying single cells and organelles with unprecedented molecular detail. PMID:19260732

Single cell digital polymerase chain reaction on self-priming compartmentalization chip

PubMed Central

Zhu, Qiangyuan; Qiu, Lin; Xu, Yanan; Li, Guang; Mu, Ying

2017-01-01

Single cell analysis provides a new framework for understanding biology and disease, however, an absolute quantification of single cell gene expression still faces many challenges. Microfluidic digital polymerase chain reaction (PCR) provides a unique method to absolutely quantify the single cell gene expression, but only limited devices are developed to analyze a single cell with detection variation. This paper describes a self-priming compartmentalization (SPC) microfluidic digital polymerase chain reaction chip being capable of performing single molecule amplification from single cell. The chip can be used to detect four single cells simultaneously with 85% of sample digitization. With the optimized protocol for the SPC chip, we first tested the ability, precision, and sensitivity of our SPC digital PCR chip by assessing β-actin DNA gene expression in 1, 10, 100, and 1000 cells. And the reproducibility of the SPC chip is evaluated by testing 18S rRNA of single cells with 1.6%–4.6% of coefficient of variation. At last, by detecting the lung cancer related genes, PLAU gene expression of A549 cells at the single cell level, the single cell heterogeneity was demonstrated. So, with the power-free, valve-free SPC chip, the gene copy number of single cells can be quantified absolutely with higher sensitivity, reduced labor time, and reagent. We expect that this chip will enable new studies for biology and disease. PMID:28191267

Single cell digital polymerase chain reaction on self-priming compartmentalization chip.

PubMed

Zhu, Qiangyuan; Qiu, Lin; Xu, Yanan; Li, Guang; Mu, Ying

2017-01-01

Single cell analysis provides a new framework for understanding biology and disease, however, an absolute quantification of single cell gene expression still faces many challenges. Microfluidic digital polymerase chain reaction (PCR) provides a unique method to absolutely quantify the single cell gene expression, but only limited devices are developed to analyze a single cell with detection variation. This paper describes a self-priming compartmentalization (SPC) microfluidic digital polymerase chain reaction chip being capable of performing single molecule amplification from single cell. The chip can be used to detect four single cells simultaneously with 85% of sample digitization. With the optimized protocol for the SPC chip, we first tested the ability, precision, and sensitivity of our SPC digital PCR chip by assessing β-actin DNA gene expression in 1, 10, 100, and 1000 cells. And the reproducibility of the SPC chip is evaluated by testing 18S rRNA of single cells with 1.6%-4.6% of coefficient of variation. At last, by detecting the lung cancer related genes, PLAU gene expression of A549 cells at the single cell level, the single cell heterogeneity was demonstrated. So, with the power-free, valve-free SPC chip, the gene copy number of single cells can be quantified absolutely with higher sensitivity, reduced labor time, and reagent. We expect that this chip will enable new studies for biology and disease.

A single-cell analysis platform for electrochemiluminescent detection of platelets adhesion to endothelial cells based on Au@DL-ZnCQDs nanoprobes.

PubMed

Long, Dongping; Shang, Yunfei; Qiu, Youyi; Zhou, Bin; Yang, Peihui

2018-04-15

A novel single-cell analysis platform (SCA) was developed for the investigation of platelets adhesion to single human umbilical vein endothelial cell (HUVEC) via using the adhesion molecule (E-selectin) on the damaged HUVEC as the marker site, and integrating electrochemiluminescence (ECL) with the ultrasensitive Au@DL-ZnCQDs nanoprobes. The Au@DL-ZnCQDs nanocomposite, a kind of double layer zinc-coadsorbed carbon quantum dot (ZnCQDs) core-shell nanoprobe, was firstly constructed by using gold nanoparticles (AuNPs) as the core to load with ZnCQDs and then the citrate-modified silver nanoparticles (AgNPs) as the bridge to link AuNPs-ZnCQDs with ZnCQDs to form the core-shell with double layer ZnCQDs (DL-ZnCQDs) nanoprobe, revealed a 10-fold signal amplification. The H 2 O 2 -induced oxidative damage HUVECs were utilized as the cellular model on which anti-E-selectin functionalized nanoprobes specially recognized E-selectin, the SCA showed that the ECL signals decreased with platelets adhesion to single HUVEC. The proposed SCA could effectively and dynamically monitor the adhesion between single HUVEC and platelets in the absence and presence of collagen activation, moreover, be able to quantitatively detect the number of platelets adhesion to single HUVEC, and show a good analytical performance with linear range from 1 to 15 platelets. In contrast, the HUVEC was down-regulated the expression of adhesion molecules by treating with quercetin inhibitor, and the SCA also exhibited the feasibility for analysis of platelets adhesion to single HUVEC. Therefore, the single-cell analysis platform provided a novel and promising protocol for analysis of the single intercellular adhesion, and it will be beneficial to elucidate the pathogenesis of cardiovascular diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Single-cell RNA-seq analysis unveils a prevalent epithelial/mesenchymal hybrid state during mouse organogenesis.

PubMed

Dong, Ji; Hu, Yuqiong; Fan, Xiaoying; Wu, Xinglong; Mao, Yunuo; Hu, Boqiang; Guo, Hongshan; Wen, Lu; Tang, Fuchou

2018-03-14

Organogenesis is crucial for proper organ formation during mammalian embryonic development. However, the similarities and shared features between different organs and the cellular heterogeneity during this process at single-cell resolution remain elusive. We perform single-cell RNA sequencing analysis of 1916 individual cells from eight organs and tissues of E9.5 to E11.5 mouse embryos, namely, the forebrain, hindbrain, skin, heart, somite, lung, liver, and intestine. Based on the regulatory activities rather than the expression patterns, all cells analyzed can be well classified into four major groups with epithelial, mesodermal, hematopoietic, and neuronal identities. For different organs within the same group, the similarities and differences of their features and developmental paths are revealed and reconstructed. We identify mutual interactions between epithelial and mesenchymal cells and detect epithelial cells with prevalent mesenchymal features during organogenesis, which are similar to the features of intermediate epithelial/mesenchymal cells during tumorigenesis. The comprehensive transcriptome at single-cell resolution profiled in our study paves the way for future mechanistic studies of the gene-regulatory networks governing mammalian organogenesis.

Quantitative refractive index distribution of single cell by combining phase-shifting interferometry and AFM imaging.

PubMed

Zhang, Qinnan; Zhong, Liyun; Tang, Ping; Yuan, Yingjie; Liu, Shengde; Tian, Jindong; Lu, Xiaoxu

2017-05-31

Cell refractive index, an intrinsic optical parameter, is closely correlated with the intracellular mass and concentration. By combining optical phase-shifting interferometry (PSI) and atomic force microscope (AFM) imaging, we constructed a label free, non-invasive and quantitative refractive index of single cell measurement system, in which the accurate phase map of single cell was retrieved with PSI technique and the cell morphology with nanoscale resolution was achieved with AFM imaging. Based on the proposed AFM/PSI system, we achieved quantitative refractive index distributions of single red blood cell and Jurkat cell, respectively. Further, the quantitative change of refractive index distribution during Daunorubicin (DNR)-induced Jurkat cell apoptosis was presented, and then the content changes of intracellular biochemical components were achieved. Importantly, these results were consistent with Raman spectral analysis, indicating that the proposed PSI/AFM based refractive index system is likely to become a useful tool for intracellular biochemical components analysis measurement, and this will facilitate its application for revealing cell structure and pathological state from a new perspective.

iSBatch: a batch-processing platform for data analysis and exploration of live-cell single-molecule microscopy images and other hierarchical datasets.

PubMed

Caldas, Victor E A; Punter, Christiaan M; Ghodke, Harshad; Robinson, Andrew; van Oijen, Antoine M

2015-10-01

Recent technical advances have made it possible to visualize single molecules inside live cells. Microscopes with single-molecule sensitivity enable the imaging of low-abundance proteins, allowing for a quantitative characterization of molecular properties. Such data sets contain information on a wide spectrum of important molecular properties, with different aspects highlighted in different imaging strategies. The time-lapsed acquisition of images provides information on protein dynamics over long time scales, giving insight into expression dynamics and localization properties. Rapid burst imaging reveals properties of individual molecules in real-time, informing on their diffusion characteristics, binding dynamics and stoichiometries within complexes. This richness of information, however, adds significant complexity to analysis protocols. In general, large datasets of images must be collected and processed in order to produce statistically robust results and identify rare events. More importantly, as live-cell single-molecule measurements remain on the cutting edge of imaging, few protocols for analysis have been established and thus analysis strategies often need to be explored for each individual scenario. Existing analysis packages are geared towards either single-cell imaging data or in vitro single-molecule data and typically operate with highly specific algorithms developed for particular situations. Our tool, iSBatch, instead allows users to exploit the inherent flexibility of the popular open-source package ImageJ, providing a hierarchical framework in which existing plugins or custom macros may be executed over entire datasets or portions thereof. This strategy affords users freedom to explore new analysis protocols within large imaging datasets, while maintaining hierarchical relationships between experiments, samples, fields of view, cells, and individual molecules.

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

High-recovery visual identification and single-cell retrieval of circulating tumor cells for genomic analysis using a dual-technology platform integrated with automated immunofluorescence staining.

PubMed

Campton, Daniel E; Ramirez, Arturo B; Nordberg, Joshua J; Drovetto, Nick; Clein, Alisa C; Varshavskaya, Paulina; Friemel, Barry H; Quarre, Steve; Breman, Amy; Dorschner, Michael; Blau, Sibel; Blau, C Anthony; Sabath, Daniel E; Stilwell, Jackie L; Kaldjian, Eric P

2015-05-06

Circulating tumor cells (CTCs) are malignant cells that have migrated from solid cancers into the blood, where they are typically present in rare numbers. There is great interest in using CTCs to monitor response to therapies, to identify clinically actionable biomarkers, and to provide a non-invasive window on the molecular state of a tumor. Here we characterize the performance of the AccuCyte®--CyteFinder® system, a comprehensive, reproducible and highly sensitive platform for collecting, identifying and retrieving individual CTCs from microscopic slides for molecular analysis after automated immunofluorescence staining for epithelial markers. All experiments employed a density-based cell separation apparatus (AccuCyte) to separate nucleated cells from the blood and transfer them to microscopic slides. After staining, the slides were imaged using a digital scanning microscope (CyteFinder). Precisely counted model CTCs (mCTCs) from four cancer cell lines were spiked into whole blood to determine recovery rates. Individual mCTCs were removed from slides using a single-cell retrieval device (CytePicker™) for whole genome amplification and subsequent analysis by PCR and Sanger sequencing, whole exome sequencing, or array-based comparative genomic hybridization. Clinical CTCs were evaluated in blood samples from patients with different cancers in comparison with the CellSearch® system. AccuCyte--CyteFinder presented high-resolution images that allowed identification of mCTCs by morphologic and phenotypic features. Spike-in mCTC recoveries were between 90 and 91%. More than 80% of single-digit spike-in mCTCs were identified and even a single cell in 7.5 mL could be found. Analysis of single SKBR3 mCTCs identified presence of a known TP53 mutation by both PCR and whole exome sequencing, and confirmed the reported karyotype of this cell line. Patient sample CTC counts matched or exceeded CellSearch CTC counts in a small feasibility cohort. The AccuCyte--CyteFinder system is a comprehensive and sensitive platform for identification and characterization of CTCs that has been applied to the assessment of CTCs in cancer patient samples as well as the isolation of single cells for genomic analysis. It thus enables accurate non-invasive monitoring of CTCs and evolving cancer biology for personalized, molecularly-guided cancer treatment.

Advancements in the application of NanoSIMS and Raman microspectroscopy to investigate the activity of microbial cells in soils

DOE PAGES

Eichorst, Stephanie A.; Strasser, Florian; Woyke, Tanja; ...

2015-08-31

The combined approach of incubating environmental samples with stable isotope-labeled substrates followed by single-cell analyses through high-resolution secondary ion mass spectrometry (NanoSIMS) or Raman microspectroscopy provides insights into the in situ function of microorganisms. This approach has found limited application in soils presumably due to the dispersal of microbial cells in a large background of particles. We developed a pipeline for the efficient preparation of cell extracts from soils for subsequent single-cell methods by combining cell detachment with separation of cells and soil particles followed by cell concentration. The procedure was evaluated by examining its influence on cell recoveries andmore » microbial community composition across two soils. This approach generated a cell fraction with considerably reduced soil particle load and of sufficient small size to allow single-cell analysis by NanoSIMS, as shown when detecting active N2-fixing and cellulose-responsive microorganisms via 15N2 and 13C-UL-cellulose incubations, respectively. The same procedure was also applicable for Raman microspectroscopic analyses of soil microorganisms, assessed via microcosm incubations with a 13C-labeled carbon source and deuterium oxide (D2O, a general activity marker). Lastly, the described sample preparation procedure enables single-cell analysis of soil microorganisms using NanoSIMS and Raman microspectroscopy, but should also facilitate single-cell sorting and sequencing.« less

Single-Cell Analysis of the Impact of Host Cell Heterogeneity on Infection with Foot-and-Mouth Disease Virus.

PubMed

Xin, Xiu; Wang, Hailong; Han, Lingling; Wang, Mingzhen; Fang, Hui; Hao, Yao; Li, Jiadai; Zhang, Hu; Zheng, Congyi; Shen, Chao

2018-05-01

Viral infection and replication are affected by host cell heterogeneity, but the mechanisms underlying the effects remain unclear. Using single-cell analysis, we investigated the effects of host cell heterogeneity, including cell size, inclusion, and cell cycle, on foot-and-mouth disease virus (FMDV) infection (acute and persistent infections) and replication. We detected various viral genome replication levels in FMDV-infected cells. Large cells and cells with a high number of inclusions generated more viral RNA copies and viral protein and a higher proportion of infectious cells than other cells. Additionally, we found that the viral titer was 10- to 100-fold higher in cells in G 2 /M than those in other cell cycle phases and identified a strong correlation between cell size, inclusion, and cell cycle heterogeneity, which all affected the infection and replication of FMDV. Furthermore, we demonstrated that host cell heterogeneity influenced the adsorption of FMDV due to differences in the levels of FMDV integrin receptors expression. Collectively, these results further our understanding of the evolution of a virus in a single host cell. IMPORTANCE It is important to understand how host cell heterogeneity affects viral infection and replication. Using single-cell analysis, we found that viral genome replication levels exhibited dramatic variability in foot-and-mouth disease virus (FMDV)-infected cells. We also found a strong correlation between heterogeneity in cell size, inclusion number, and cell cycle status and that all of these characteristics affect the infection and replication of FMDV. Moreover, we found that host cell heterogeneity influenced the viral adsorption as differences in the levels of FMDV integrin receptors' expression. This study provided new ideas for the studies of correlation between FMDV infection mechanisms and host cells. Copyright © 2018 American Society for Microbiology.

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

PubMed

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

2016-08-01

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

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

Activity and interactions of methane seep microorganisms assessed by parallel transcription and FISH-NanoSIMS analyses

PubMed Central

Dekas, Anne E; Connon, Stephanie A; Chadwick, Grayson L; Trembath-Reichert, Elizabeth; Orphan, Victoria J

2016-01-01

To characterize the activity and interactions of methanotrophic archaea (ANME) and Deltaproteobacteria at a methane-seeping mud volcano, we used two complimentary measures of microbial activity: a community-level analysis of the transcription of four genes (16S rRNA, methyl coenzyme M reductase A (mcrA), adenosine-5′-phosphosulfate reductase α-subunit (aprA), dinitrogenase reductase (nifH)), and a single-cell-level analysis of anabolic activity using fluorescence in situ hybridization coupled to nanoscale secondary ion mass spectrometry (FISH-NanoSIMS). Transcript analysis revealed that members of the deltaproteobacterial groups Desulfosarcina/Desulfococcus (DSS) and Desulfobulbaceae (DSB) exhibit increased rRNA expression in incubations with methane, suggestive of ANME-coupled activity. Direct analysis of anabolic activity in DSS cells in consortia with ANME by FISH-NanoSIMS confirmed their dependence on methanotrophy, with no 15NH4+ assimilation detected without methane. In contrast, DSS and DSB cells found physically independent of ANME (i.e., single cells) were anabolically active in incubations both with and without methane. These single cells therefore comprise an active ‘free-living' population, and are not dependent on methane or ANME activity. We investigated the possibility of N2 fixation by seep Deltaproteobacteria and detected nifH transcripts closely related to those of cultured diazotrophic Deltaproteobacteria. However, nifH expression was methane-dependent. 15N2 incorporation was not observed in single DSS cells, but was detected in single DSB cells. Interestingly, 15N2 incorporation in single DSB cells was methane-dependent, raising the possibility that DSB cells acquired reduced 15N products from diazotrophic ANME while spatially coupled, and then subsequently dissociated. With this combined data set we address several outstanding questions in methane seep microbial ecosystems and highlight the benefit of measuring microbial activity in the context of spatial associations. PMID:26394007

Activity and interactions of methane seep microorganisms assessed by parallel transcription and FISH-NanoSIMS analyses

DOE PAGES

Dekas, Anne E.; Connon, Stephanie A.; Chadwick, Grayson L.; ...

2015-09-22

To characterize the activity and interactions of methanotrophic archaea (ANME) and Deltaproteo-bacteria at a methane-seeping mud volcano, we used two complimentary measures of microbial activity: a community-level analysis of the transcription of four genes (16S rRNA, methyl coenzyme M reductase A (mcrA), adenosine-5'-phosphosulfate reductase α-subunit (aprA), dinitrogenase reductase (nifH)), and a single-cell-level analysis of anabolic activity using fluorescence in situ hybridization coupled to nanoscale secondary ion mass spectrometry (FISH-NanoSIMS). Transcript analysis revealed that members of the deltaproteobacterial groups Desulfosarcina/Desulfococcus (DSS) and Desulfobulbaceae (DSB) exhibit increased rRNA expression in incubations with methane, suggestive of ANME-coupled activity. Direct analysis of anabolic activity in DSS cells in consortia with ANME by FISH-NanoSIMS confirmed their dependence on methanotrophy, with no 15NHmore » $$+\\atop{4}$$ assimilation detected without methane. In contrast, DSS and DSB cells found physically independent of ANME (i.e., single cells) were anabolically active in incubations both with and without methane. These single cells therefore comprise an active ‘free-living’ population, and are not dependent on methane or ANME activity. We investigated the possibility of N 2 fixation by seep Deltaproteobacteria and detected nifH transcripts closely related to those of cultured diazotrophic Deltaproteobacteria. However, nifH expression was methane-dependent. 15N 2 incorporation was not observed in single DSS cells, but was detected in single DSB cells. Interestingly, 15N 2 incorporation in single DSB cells was methane-dependent, raising the possibility that DSB cells acquired reduced 15N products from diazotrophic ANME while spatially coupled, and then subsequently dissociated. In conclusion, with this combined data set we address several outstanding questions in methane seep microbial ecosystems and highlight the benefit of measuring microbial activity in the context of spatial associations.« less

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 Analysis Using Hyperspectral Imaging Modalities.

PubMed

Mehta, Nishir; Shaik, Shahensha; Devireddy, Ram; Gartia, Manas Ranjan

2018-02-01

Almost a decade ago, hyperspectral imaging (HSI) was employed by the NASA in satellite imaging applications such as remote sensing technology. This technology has since been extensively used in the exploration of minerals, agricultural purposes, water resources, and urban development needs. Due to recent advancements in optical re-construction and imaging, HSI can now be applied down to micro- and nanometer scales possibly allowing for exquisite control and analysis of single cell to complex biological systems. This short review provides a description of the working principle of the HSI technology and how HSI can be used to assist, substitute, and validate traditional imaging technologies. This is followed by a description of the use of HSI for biological analysis and medical diagnostics with emphasis on single-cell analysis using HSI.

Rotation of single live mammalian cells using dynamic holographic optical tweezers

NASA Astrophysics Data System (ADS)

Bin Cao; Kelbauskas, Laimonas; Chan, Samantha; Shetty, Rishabh M.; Smith, Dean; Meldrum, Deirdre R.

2017-05-01

We report on a method for rotating single mammalian cells about an axis perpendicular to the optical system axis through the imaging plane using dynamic holographic optical tweezers (HOTs). Two optical traps are created on the opposite edges of a mammalian cell and are continuously transitioned through the imaging plane along the circumference of the cell in opposite directions, thus providing the torque to rotate the cell in a controlled fashion. The method enables a complete 360° rotation of live single mammalian cells with spherical or near-to spherical shape in 3D space, and represents a useful tool suitable for the single cell analysis field, including tomographic imaging.

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

Single-cell Transcriptome Study as Big Data

PubMed Central

Yu, Pingjian; Lin, Wei

2016-01-01

The rapid growth of single-cell RNA-seq studies (scRNA-seq) demands efficient data storage, processing, and analysis. Big-data technology provides a framework that facilitates the comprehensive discovery of biological signals from inter-institutional scRNA-seq datasets. The strategies to solve the stochastic and heterogeneous single-cell transcriptome signal are discussed in this article. After extensively reviewing the available big-data applications of next-generation sequencing (NGS)-based studies, we propose a workflow that accounts for the unique characteristics of scRNA-seq data and primary objectives of single-cell studies. PMID:26876720

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.

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.

ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data

PubMed Central

Gardeux, Vincent; David, Fabrice P. A.; Shajkofci, Adrian; Schwalie, Petra C.; Deplancke, Bart

2017-01-01

Abstract Motivation Single-cell RNA-sequencing (scRNA-seq) allows whole transcriptome profiling of thousands of individual cells, enabling the molecular exploration of tissues at the cellular level. Such analytical capacity is of great interest to many research groups in the world, yet these groups often lack the expertise to handle complex scRNA-seq datasets. Results We developed a fully integrated, web-based platform aimed at the complete analysis of scRNA-seq data post genome alignment: from the parsing, filtering and normalization of the input count data files, to the visual representation of the data, identification of cell clusters, differentially expressed genes (including cluster-specific marker genes), and functional gene set enrichment. This Automated Single-cell Analysis Pipeline (ASAP) combines a wide range of commonly used algorithms with sophisticated visualization tools. Compared with existing scRNA-seq analysis platforms, researchers (including those lacking computational expertise) are able to interact with the data in a straightforward fashion and in real time. Furthermore, given the overlap between scRNA-seq and bulk RNA-seq analysis workflows, ASAP should conceptually be broadly applicable to any RNA-seq dataset. As a validation, we demonstrate how we can use ASAP to simply reproduce the results from a single-cell study of 91 mouse cells involving five distinct cell types. Availability and implementation The tool is freely available at asap.epfl.ch and R/Python scripts are available at github.com/DeplanckeLab/ASAP. Contact bart.deplancke@epfl.ch Supplementary information Supplementary data are available at Bioinformatics online. PMID:28541377

ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data.

PubMed

Gardeux, Vincent; David, Fabrice P A; Shajkofci, Adrian; Schwalie, Petra C; Deplancke, Bart

2017-10-01

Single-cell RNA-sequencing (scRNA-seq) allows whole transcriptome profiling of thousands of individual cells, enabling the molecular exploration of tissues at the cellular level. Such analytical capacity is of great interest to many research groups in the world, yet these groups often lack the expertise to handle complex scRNA-seq datasets. We developed a fully integrated, web-based platform aimed at the complete analysis of scRNA-seq data post genome alignment: from the parsing, filtering and normalization of the input count data files, to the visual representation of the data, identification of cell clusters, differentially expressed genes (including cluster-specific marker genes), and functional gene set enrichment. This Automated Single-cell Analysis Pipeline (ASAP) combines a wide range of commonly used algorithms with sophisticated visualization tools. Compared with existing scRNA-seq analysis platforms, researchers (including those lacking computational expertise) are able to interact with the data in a straightforward fashion and in real time. Furthermore, given the overlap between scRNA-seq and bulk RNA-seq analysis workflows, ASAP should conceptually be broadly applicable to any RNA-seq dataset. As a validation, we demonstrate how we can use ASAP to simply reproduce the results from a single-cell study of 91 mouse cells involving five distinct cell types. The tool is freely available at asap.epfl.ch and R/Python scripts are available at github.com/DeplanckeLab/ASAP. bart.deplancke@epfl.ch. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Single-Cell Analysis of Human Pancreas Reveals Transcriptional Signatures of Aging and Somatic Mutation Patterns.

PubMed

Enge, Martin; Arda, H Efsun; Mignardi, Marco; Beausang, John; Bottino, Rita; Kim, Seung K; Quake, Stephen R

2017-10-05

As organisms age, cells accumulate genetic and epigenetic errors that eventually lead to impaired organ function or catastrophic transformation such as cancer. Because aging reflects a stochastic process of increasing disorder, cells in an organ will be individually affected in different ways, thus rendering bulk analyses of postmitotic adult cells difficult to interpret. Here, we directly measure the effects of aging in human tissue by performing single-cell transcriptome analysis of 2,544 human pancreas cells from eight donors spanning six decades of life. We find that islet endocrine cells from older donors display increased levels of transcriptional noise and potential fate drift. By determining the mutational history of individual cells, we uncover a novel mutational signature in healthy aging endocrine cells. Our results demonstrate the feasibility of using single-cell RNA sequencing (RNA-seq) data from primary cells to derive insights into genetic and transcriptional processes that operate on aging human tissue. Copyright © 2017 Elsevier Inc. All rights reserved.

Scientist, Single Cell Analysis Facility | Center for Cancer Research

Cancer.gov

The Cancer Research Technology Program (CRTP) develops and implements emerging technology, cancer biology expertise and research capabilities to accomplish NCI research objectives.  The CRTP is an outward-facing, multi-disciplinary hub purposed to enable the external cancer research community and provides dedicated support to NCI’s intramural Center for Cancer Research (CCR).  The dedicated units provide electron microscopy, protein characterization, protein expression, optical microscopy and nextGen sequencing. These research efforts are an integral part of CCR at the Frederick National Laboratory for Cancer Research (FNLCR).  CRTP scientists also work collaboratively with intramural NCI investigators to provide research technologies and expertise. KEY ROLES AND RESPONSIBILITIES We are seeking a highly motivated Scientist II to join the newly established Single Cell Analysis Facility (SCAF) of the Center for Cancer Research (CCR) at NCI. The SCAF will house state of the art single cell sequencing technologies including 10xGenomics Chromium, BD Genomics Rhapsody, DEPPArray, and other emerging single cell technologies. The Scientist: Will interact with close to 200 laboratories within the CCR to design and carry out single cell experiments for cancer research Will work on single cell isolation/preparation from various tissues and cells and related NexGen sequencing library preparation Is expected to author publications in peer reviewed scientific journals

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

A robust method to analyze copy number alterations of less than 100 kb in single cells using oligonucleotide array CGH.

PubMed

Möhlendick, Birte; Bartenhagen, Christoph; Behrens, Bianca; Honisch, Ellen; Raba, Katharina; Knoefel, Wolfram T; Stoecklein, Nikolas H

2013-01-01

Comprehensive genome wide analyses of single cells became increasingly important in cancer research, but remain to be a technically challenging task. Here, we provide a protocol for array comparative genomic hybridization (aCGH) of single cells. The protocol is based on an established adapter-linker PCR (WGAM) and allowed us to detect copy number alterations as small as 56 kb in single cells. In addition we report on factors influencing the success of single cell aCGH downstream of the amplification method, including the characteristics of the reference DNA, the labeling technique, the amount of input DNA, reamplification, the aCGH resolution, and data analysis. In comparison with two other commercially available non-linear single cell amplification methods, WGAM showed a very good performance in aCGH experiments. Finally, we demonstrate that cancer cells that were processed and identified by the CellSearch® System and that were subsequently isolated from the CellSearch® cartridge as single cells by fluorescence activated cell sorting (FACS) could be successfully analyzed using our WGAM-aCGH protocol. We believe that even in the era of next-generation sequencing, our single cell aCGH protocol will be a useful and (cost-) effective approach to study copy number alterations in single cells at resolution comparable to those reported currently for single cell digital karyotyping based on next generation sequencing data.

Microfluidic Impedance Flow Cytometry Enabling High-Throughput Single-Cell Electrical Property Characterization

PubMed Central

Chen, Jian; Xue, Chengcheng; Zhao, Yang; Chen, Deyong; Wu, Min-Hsien; Wang, Junbo

2015-01-01

This article reviews recent developments in microfluidic impedance flow cytometry for high-throughput electrical property characterization of single cells. Four major perspectives of microfluidic impedance flow cytometry for single-cell characterization are included in this review: (1) early developments of microfluidic impedance flow cytometry for single-cell electrical property characterization; (2) microfluidic impedance flow cytometry with enhanced sensitivity; (3) microfluidic impedance and optical flow cytometry for single-cell analysis and (4) integrated point of care system based on microfluidic impedance flow cytometry. We examine the advantages and limitations of each technique and discuss future research opportunities from the perspectives of both technical innovation and clinical applications. PMID:25938973

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

PubMed Central

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

2017-01-01

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

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.

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.

Validation of high-throughput single cell analysis methodology.

PubMed

Devonshire, Alison S; Baradez, Marc-Olivier; Morley, Gary; Marshall, Damian; Foy, Carole A

2014-05-01

High-throughput quantitative polymerase chain reaction (qPCR) approaches enable profiling of multiple genes in single cells, bringing new insights to complex biological processes and offering opportunities for single cell-based monitoring of cancer cells and stem cell-based therapies. However, workflows with well-defined sources of variation are required for clinical diagnostics and testing of tissue-engineered products. In a study of neural stem cell lines, we investigated the performance of lysis, reverse transcription (RT), preamplification (PA), and nanofluidic qPCR steps at the single cell level in terms of efficiency, precision, and limit of detection. We compared protocols using a separate lysis buffer with cell capture directly in RT-PA reagent. The two methods were found to have similar lysis efficiencies, whereas the direct RT-PA approach showed improved precision. Digital PCR was used to relate preamplified template copy numbers to Cq values and reveal where low-quality signals may affect the analysis. We investigated the impact of calibration and data normalization strategies as a means of minimizing the impact of inter-experimental variation on gene expression values and found that both approaches can improve data comparability. This study provides validation and guidance for the application of high-throughput qPCR workflows for gene expression profiling of single cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Visualization and quantitative analysis of extrachromosomal telomere-repeat DNA in individual human cells by Halo-FISH

PubMed Central

Komosa, Martin; Root, Heather; Meyn, M. Stephen

2015-01-01

Current methods for characterizing extrachromosomal nuclear DNA in mammalian cells do not permit single-cell analysis, are often semi-quantitative and frequently biased toward the detection of circular species. To overcome these limitations, we developed Halo-FISH to visualize and quantitatively analyze extrachromosomal DNA in single cells. We demonstrate Halo-FISH by using it to analyze extrachromosomal telomere-repeat (ECTR) in human cells that use the Alternative Lengthening of Telomeres (ALT) pathway(s) to maintain telomere lengths. We find that GM847 and VA13 ALT cells average ∼80 detectable G/C-strand ECTR DNA molecules/nucleus, while U2OS ALT cells average ∼18 molecules/nucleus. In comparison, human primary and telomerase-positive cells contain <5 ECTR DNA molecules/nucleus. ECTR DNA in ALT cells exhibit striking cell-to-cell variations in number (<20 to >300), range widely in length (<1 to >200 kb) and are composed of primarily G- or C-strand telomere-repeat DNA. Halo-FISH enables, for the first time, the simultaneous analysis of ECTR DNA and chromosomal telomeres in a single cell. We find that ECTR DNA comprises ∼15% of telomere-repeat DNA in GM847 and VA13 cells, but <4% in U2OS cells. In addition to its use in ALT cell analysis, Halo-FISH can facilitate the study of a wide variety of extrachromosomal DNA in mammalian cells. PMID:25662602

Flow analysis of human chromosome sets by means of mixing-stirring device

NASA Astrophysics Data System (ADS)

Zenin, Valeri V.; Aksenov, Nicolay D.; Shatrova, Alla N.; Klopov, Nicolay V.; Cram, L. Scott; Poletaev, Andrey I.

1997-05-01

A new mixing and stirring device (MSD) was used to perform flow karyotype analysis of single human mitotic chromosomes analyzed so as to maintain the identity of chromosomes derived from the same cell. An improved method for cell preparation and intracellular staining of chromosomes was developed. The method includes enzyme treatment, incubation with saponin and separation of prestained cells from debris on a sucrose gradient. Mitotic cells are injected one by one in the MSD which is located inside the flow chamber where cells are ruptured, thereby releasing chromosomes. The set of chromosomes proceeds to flow in single file fashion to the point of analysis. The device works in a stepwise manner. The concentration of cells in the sample must be kept low to ensure that only one cell at a time enters the breaking chamber. Time-gated accumulation of data in listmode files makes it possible to separate chromosome sets comprising of single cells. The software that was developed classifies chromosome sets according to different criteria: total number of chromosomes, overall DNA content in the set, and the number of chromosomes of certain types. This approach combines the high performance of flow cytometry with the advantages of image analysis. Examples obtained with different human cell lines are presented.

Mass cytometry: a highly multiplexed single-cell technology for advancing drug development.

PubMed

Atkuri, Kondala R; Stevens, Jeffrey C; Neubert, Hendrik

2015-02-01

Advanced single-cell analysis technologies (e.g., mass cytometry) that help in multiplexing cellular measurements in limited-volume primary samples are critical in bridging discovery efforts to successful drug approval. Mass cytometry is the state-of-the-art technology in multiparametric single-cell analysis. Mass cytometers (also known as cytometry by time-of-flight or CyTOF) combine the cellular analysis principles of traditional fluorescence-based flow cytometry with the selectivity and quantitative power of inductively coupled plasma-mass spectrometry. Standard flow cytometry is limited in the number of parameters that can be measured owing to the overlap in signal when detecting fluorescently labeled antibodies. Mass cytometry uses antibodies tagged to stable isotopes of rare earth metals, which requires minimal signal compensation between the different metal tags. This unique feature enables researchers to seamlessly multiplex up to 40 independent measurements on single cells. In this overview we first present an overview of mass cytometry and compare it with traditional flow cytometry. We then discuss the emerging and potential applications of CyTOF technology in the pharmaceutical industry, including quantitative and qualitative deep profiling of immune cells and their applications in assessing drug immunogenicity, extensive mapping of signaling networks in single cells, cell surface receptor quantification and multiplexed internalization kinetics, multiplexing sample analysis by barcoding, and establishing cell ontologies on the basis of phenotype and/or function. We end with a discussion of the anticipated impact of this technology on drug development lifecycle with special emphasis on the utility of mass cytometry in deciphering a drug's pharmacokinetics and pharmacodynamics relationship. Copyright © 2014 by The American Society for Pharmacology and Experimental Therapeutics.

Numerical Simulations of the Digital Microfluidic Manipulation of Single Microparticles.

PubMed

Lan, Chuanjin; Pal, Souvik; Li, Zhen; Ma, Yanbao

2015-09-08

Single-cell analysis techniques have been developed as a valuable bioanalytical tool for elucidating cellular heterogeneity at genomic, proteomic, and cellular levels. Cell manipulation is an indispensable process for single-cell analysis. Digital microfluidics (DMF) is an important platform for conducting cell manipulation and single-cell analysis in a high-throughput fashion. However, the manipulation of single cells in DMF has not been quantitatively studied so far. In this article, we investigate the interaction of a single microparticle with a liquid droplet on a flat substrate using numerical simulations. The droplet is driven by capillary force generated from the wettability gradient of the substrate. Considering the Brownian motion of microparticles, we utilize many-body dissipative particle dynamics (MDPD), an off-lattice mesoscopic simulation technique, in this numerical study. The manipulation processes (including pickup, transport, and drop-off) of a single microparticle with a liquid droplet are simulated. Parametric studies are conducted to investigate the effects on the manipulation processes from the droplet size, wettability gradient, wetting properties of the microparticle, and particle-substrate friction coefficients. The numerical results show that the pickup, transport, and drop-off processes can be precisely controlled by these parameters. On the basis of the numerical results, a trap-free delivery of a hydrophobic microparticle to a destination on the substrate is demonstrated in the numerical simulations. The numerical results not only provide a fundamental understanding of interactions among the microparticle, the droplet, and the substrate but also demonstrate a new technique for the trap-free immobilization of single hydrophobic microparticles in the DMF design. Finally, our numerical method also provides a powerful design and optimization tool for the manipulation of microparticles in DMF systems.

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.

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.

Development of Magnetic Nanomaterials and Devices for Biological Applications

DTIC Science & Technology

2007-10-30

analysis. Suitable crystals for the X-ray diffraction analysis were grown as dark red plates from a saturated hexane solution of [ Co3 (CO)9CCH3] at 4 ºC...Commercially available magnetic nanoparticles are suitable for cell separation where a large number of particles are used to separate a single cell...from a sample. The magnetic moment of these particles is not high enough to enable the separation of single antigen molecules using a single particle

Single cell analysis in native tissue: Quantification of the retinoid content of hepatic stellate cells

NASA Astrophysics Data System (ADS)

Galler, Kerstin; Requardt, Robert Pascal; Glaser, Uwe; Markwart, Robby; Bocklitz, Thomas; Bauer, Michael; Popp, Jürgen; Neugebauer, Ute

2016-04-01

Hepatic stellate cells (HSCs) are retinoid storing cells in the liver: The retinoid content of those cells changes depending on nutrition and stress level. There are also differences with regard to a HSC’s anatomical position in the liver. Up to now, retinoid levels were only accessible from bulk measurements of tissue homogenates or cell extracts. Unfortunately, they do not account for the intercellular variability. Herein, Raman spectroscopy relying on excitation by the minimally destructive wavelength 785 nm is introduced for the assessment of the retinoid state of single HSCs in freshly isolated, unprocessed murine liver lobes. A quantitative estimation of the cellular retinoid content is derived. Implications of the retinoid content on hepatic health state are reported. The Raman-based results are integrated with histological assessments of the tissue samples. This spectroscopic approach enables single cell analysis regarding an important cellular feature in unharmed tissue.

Single cell analysis in native tissue: Quantification of the retinoid content of hepatic stellate cells

PubMed Central

Galler, Kerstin; Requardt, Robert Pascal; Glaser, Uwe; Markwart, Robby; Bocklitz, Thomas; Bauer, Michael; Popp, Jürgen; Neugebauer, Ute

2016-01-01

Hepatic stellate cells (HSCs) are retinoid storing cells in the liver: The retinoid content of those cells changes depending on nutrition and stress level. There are also differences with regard to a HSC’s anatomical position in the liver. Up to now, retinoid levels were only accessible from bulk measurements of tissue homogenates or cell extracts. Unfortunately, they do not account for the intercellular variability. Herein, Raman spectroscopy relying on excitation by the minimally destructive wavelength 785 nm is introduced for the assessment of the retinoid state of single HSCs in freshly isolated, unprocessed murine liver lobes. A quantitative estimation of the cellular retinoid content is derived. Implications of the retinoid content on hepatic health state are reported. The Raman-based results are integrated with histological assessments of the tissue samples. This spectroscopic approach enables single cell analysis regarding an important cellular feature in unharmed tissue. PMID:27063397

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.

Direct digestion of proteins in living cells into peptides for proteomic analysis.

PubMed

Chen, Qi; Yan, Guoquan; Gao, Mingxia; Zhang, Xiangmin

2015-01-01

To analyze the proteome of an extremely low number of cells or even a single cell, we established a new method of digesting whole cells into mass-spectrometry-identifiable peptides in a single step within 2 h. Our sampling method greatly simplified the processes of cell lysis, protein extraction, protein purification, and overnight digestion, without compromising efficiency. We used our method to digest hundred-scale cells. As far as we know, there is no report of proteome analysis starting directly with as few as 100 cells. We identified an average of 109 proteins from 100 cells, and with three replicates, the number of proteins rose to 204. Good reproducibility was achieved, showing stability and reliability of the method. Gene Ontology analysis revealed that proteins in different cellular compartments were well represented.

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.

Single cell analysis of voltage-gated potassium channels that determines neuronal types of rat hypothalamic paraventricular nucleus neurons.

PubMed

Lee, S K; Lee, S; Shin, S Y; Ryu, P D; Lee, S Y

2012-03-15

The hypothalamic paraventricular nucleus (PVN), a site for the integration of both the neuroendocrine and autonomic systems, has heterogeneous cell composition. These neurons are classified into type I and type II neurons based on their electrophysiological properties. In the present study, we investigated the molecular identification of voltage-gated K+ (Kv) channels, which determines a distinctive characteristic of type I PVN neurons, by means of single-cell reverse transcription-polymerase chain reaction (RT-PCR) along with slice patch clamp recordings. In order to determine the mRNA expression profiles, firstly, the PVN neurons of male rats were classified into type I and type II neurons, and then, single-cell RT-PCR and single-cell real-time RT-PCR analysis were performed using the identical cell. The single-cell RT-PCR analysis revealed that Kv1.2, Kv1.3, Kv1.4, Kv4.1, Kv4.2, and Kv4.3 were expressed both in type I and in type II neurons, and several Kv channels were co-expressed in a single PVN neuron. However, we found that the expression densities of Kv4.2 and Kv4.3 were significantly higher in type I neurons than in type II neurons. Taken together, several Kv channels encoding A-type K+ currents are present both in type I and in type II neurons, and among those, Kv4.2 and Kv4.3 are the major Kv subunits responsible for determining the distinct electrophysiological properties. Thus these 2 Kv subunits may play important roles in determining PVN cell types and regulating PVN neuronal excitability. This study further provides key molecular mechanisms for differentiating type I and type II PVN neurons. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

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.

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

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-type quantitative proteomic and ionomic analysis of epidermal bladder cells from the halophyte model plant Mesembryanthemum crystallinum to identify salt-responsive proteins.

PubMed

Barkla, Bronwyn J; Vera-Estrella, Rosario; Raymond, Carolyn

2016-05-10

Epidermal bladder cells (EBC) are large single-celled, specialized, and modified trichomes found on the aerial parts of the halophyte Mesembryanthemum crystallinum. Recent development of a simple but high throughput technique to extract the contents from these cells has provided an opportunity to conduct detailed single-cell-type analyses of their molecular characteristics at high resolution to gain insight into the role of these cells in the salt tolerance of the plant. In this study, we carry out large-scale complementary quantitative proteomic studies using both a label (DIGE) and label-free (GeLC-MS) approach to identify salt-responsive proteins in the EBC extract. Additionally we perform an ionomics analysis (ICP-MS) to follow changes in the amounts of 27 different elements. Using these methods, we were able to identify 54 proteins and nine elements that showed statistically significant changes in the EBC from salt-treated plants. GO enrichment analysis identified a large number of transport proteins but also proteins involved in photosynthesis, primary metabolism and Crassulacean acid metabolism (CAM). Validation of results by western blot, confocal microscopy and enzyme analysis helped to strengthen findings and further our understanding into the role of these specialized cells. As expected EBC accumulated large quantities of sodium, however, the most abundant element was chloride suggesting the sequestration of this ion into the EBC vacuole is just as important for salt tolerance. This single-cell type omics approach shows that epidermal bladder cells of M. crystallinum are metabolically active modified trichomes, with primary metabolism supporting cell growth, ion accumulation, compatible solute synthesis and CAM. Data are available via ProteomeXchange with identifier PXD004045.

PCR amplification and genetic analysis in a microwell cell culturing chip.

PubMed

Lindström, Sara; Hammond, Maria; Brismar, Hjalmar; Andersson-Svahn, Helene; Ahmadian, Afshin

2009-12-21

We have previously described a microwell chip designed for high throughput, long-term single-cell culturing and clonal analysis in individual wells providing a controlled way of studying high numbers of individual adherent or non-adherent cells. Here we present a method for the genetic analysis of cells cultured on-chip by PCR and minisequencing, demonstrated using two human adherent cell lines: one wild type and one with a single-base mutation in the p53 gene. Five wild type or mutated cells were seeded per well (in a defined set of wells, each holding 500 nL of culture medium) in a 672-microwell chip. The cell chip was incubated overnight, or cultured for up to five days, depending on the desired colony size, after which the cells were lysed and subjected to PCR directly in the wells. PCR products were detected, in the wells, using a biotinylated primer and a fluorescently labelled primer, allowing the products to be captured on streptavidin-coated magnetic beads and detected by a fluorescence microscope. In addition, to enable genetic analysis by minisequencing, the double-stranded PCR products were denatured and the immobilized strands were kept in the wells by applying a magnetic field from the bottom of the wells while the wells were washed, a minisequencing reaction mixture was added, and after incubation in appropriate conditions the expected genotypes were detected in the investigated microwells, simultaneously, by an array scanner. We anticipate that the technique could be used in mutation frequency screening, providing the ability to correlate cells' proliferative heterogeneity to their genetic heterogeneity, in hundreds of samples simultaneously. The presented method of single-cell culture and DNA amplification thus offers a potentially powerful alternative to single-cell PCR, with advantageous robustness and sensitivity.

High-throughput microfluidics to control and measure signaling dynamics in single yeast cells

PubMed Central

Hansen, Anders S.; Hao, Nan; O'Shea, Erin K.

2015-01-01

Microfluidics coupled to quantitative time-lapse fluorescence microscopy is transforming our ability to control, measure, and understand signaling dynamics in single living cells. Here we describe a pipeline that incorporates multiplexed microfluidic cell culture, automated programmable fluid handling for cell perturbation, quantitative time-lapse microscopy, and computational analysis of time-lapse movies. We illustrate how this setup can be used to control the nuclear localization of the budding yeast transcription factor Msn2. Using this protocol, we generate oscillations of Msn2 localization and measure the dynamic gene expression response of individual genes in single cells. The protocol allows a single researcher to perform up to 20 different experiments in a single day, whilst collecting data for thousands of single cells. Compared to other protocols, the present protocol is relatively easy to adopt and higher-throughput. The protocol can be widely used to control and monitor single-cell signaling dynamics in other signal transduction systems in microorganisms. PMID:26158443

Noninvasive prenatal diagnosis for single gene disorders.

PubMed

Allen, Stephanie; Young, Elizabeth; Bowns, Benjamin

2017-04-01

Noninvasive prenatal diagnosis for single gene disorders is coming to fruition in its clinical utility. The presence of cell-free DNA in maternal plasma has been recognized for many years, and a number of applications have developed from this. Noninvasive prenatal diagnosis for single gene disorders has lagged behind due to complexities of technology development, lack of investment and the need for validation samples for rare disorders. Publications are emerging demonstrating a variety of technical approaches and feasibility of clinical application. Techniques for analysis of cell-free DNA including digital PCR, next-generation sequencing and relative haplotype dosage have been used most often for assay development. Analysis of circulating fetal cells in the maternal blood is still being investigated as a viable alternative and more recently transcervical trophoblast cells. Studies exploring ethical and social issues are generally positive but raise concerns around the routinization of prenatal testing. Further work is necessary to make testing available to all patients with a pregnancy at risk of a single gene disorder, and it remains to be seen if the development of more powerful technologies such as isolation and analysis of single cells will shift the emphasis of noninvasive prenatal diagnosis. As testing becomes possible for a wider range of conditions, more ethical questions will become relevant.

Oufti: An integrated software package for high-accuracy, high-throughput quantitative microscopy analysis

PubMed Central

Paintdakhi, Ahmad; Parry, Bradley; Campos, Manuel; Irnov, Irnov; Elf, Johan; Surovtsev, Ivan; Jacobs-Wagner, Christine

2016-01-01

Summary With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today’s single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals, and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis, and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills. PMID:26538279

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

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.

TLM-Tracker: software for cell segmentation, tracking and lineage analysis in time-lapse microscopy movies.

PubMed

Klein, Johannes; Leupold, Stefan; Biegler, Ilona; Biedendieck, Rebekka; Münch, Richard; Jahn, Dieter

2012-09-01

Time-lapse imaging in combination with fluorescence microscopy techniques enable the investigation of gene regulatory circuits and uncovered phenomena like culture heterogeneity. In this context, computational image processing for the analysis of single cell behaviour plays an increasing role in systems biology and mathematical modelling approaches. Consequently, we developed a software package with graphical user interface for the analysis of single bacterial cell behaviour. A new software called TLM-Tracker allows for the flexible and user-friendly interpretation for the segmentation, tracking and lineage analysis of microbial cells in time-lapse movies. The software package, including manual, tutorial video and examples, is available as Matlab code or executable binaries at http://www.tlmtracker.tu-bs.de.

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

Nanochannel Electroporation as a Platform for Living Cell Interrogation in Acute Myeloid Leukemia.

PubMed

Zhao, Xi; Huang, Xiaomeng; Wang, Xinmei; Wu, Yun; Eisfeld, Ann-Kathrin; Schwind, Sebastian; Gallego-Perez, Daniel; Boukany, Pouyan E; Marcucci, Guido I; Lee, Ly James

2015-12-01

A living cell interrogation platform based on nanochannel electroporation is demonstrated with analysis of RNAs in single cells. This minimally invasive process is based on individual cells and allows both multi-target analysis and stimulus-response analysis by sequential deliveries. The unique platform possesses a great potential to the comprehensive and lysis-free nucleic acid analysis on rare or hard-to-transfect cells.

UV Decontamination of MDA Reagents for Single Cell Genomics

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

Lee, Janey; Tighe, Damon; Sczyrba, Alexander

2011-03-18

Single cell genomics, the amplification and sequencing of genomes from single cells, can provide a glimpse into the genetic make-up and thus life style of the vast majority of uncultured microbial cells, making it an immensely powerful and increasingly popular tool. This is accomplished by use of multiple displacement amplification (MDA), which can generate billions of copies of a single bacterial genome producing microgram-range DNA required for shotgun sequencing. Here, we address a key challenge inherent to this approach and propose a solution for the improved recovery of single cell genomes. While DNA-free reagents for the amplification of a singlemore » cell genome are a prerequisite for successful single cell sequencing and analysis, DNA contamination has been detected in various reagents, which poses a considerable challenge. Our study demonstrates the effect of UV irradiation in efficient elimination of exogenous contaminant DNA found in MDA reagents, while maintaining Phi29 activity. Consequently, we also find that increased UV exposure to Phi29 does not adversely affect genome coverage of MDA amplified single cells. While additional challenges in single cell genomics remain to be resolved, the proposed methodology is relatively quick and simple and we believe that its application will be of high value for future single cell sequencing projects.« less

Tomographic flow cytometry assisted by intelligent wavefronts analysis

NASA Astrophysics Data System (ADS)

Merola, F.; Memmolo, P.; Miccio, L.; Mugnano, M.; Ferraro, P.

2017-06-01

High-throughput single-cell analysis is a challenging target for implementing advanced biomedical applications. An excellent candidate for this aim is label-free tomographic phase microscopy. However, in-line tomography is very difficult to be implemented in practice, as it requires complex setup for rotating the sample and/or illuminate the cell along numerous directions [1]. We exploit random rolling of cells while they are flowing along a microfluidic channel demonstrating that it is possible to obtain in-line phase-contrast tomography by adopting strategies for intelligent wavefronts analysis thus obtaining complete retrieval of both 3D-position and orientation of rotating cells [2]. Thus, by numerical wavefront analysis a-priori knowledge of such information is no longer needed. This approach makes continuos-flow cyto-tomography suitable for practical operation in real-world, single-cell analysis and with substantial simplification of the optical system avoiding any mechanical/optical scanning of light source. Demonstration is given for different classes of biosamples, red-blood-cells (RBCs), diatom algae and fibroblast cells [3]. Accurate characterization of each type of cells is reported despite their very different nature and materials content, thus showing the proposed method can be extended, by adopting two alternate strategies of wavefront-analysis, to many classes of cells. In particular, for RBCs we furnish important parameters as 3D morphology, Corpuscular Hemoglobin (CH), Volume (V), and refractive index (RI) for each single cell in the total population [3]. This could open a new route in blood disease diagnosis, for example for the isolation and characterization of "foreign" cells in the blood stream, the so called Circulating Tumor Cells (CTC), early manifestation of metastasis.

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.

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).

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.

Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia

PubMed Central

Wang, Lili; Fan, Jean; Francis, Joshua M.; Georghiou, George; Hergert, Sarah; Li, Shuqiang; Gambe, Rutendo; Zhou, Chensheng W.; Yang, Chunxiao; Xiao, Sheng; Cin, Paola Dal; Bowden, Michaela; Kotliar, Dylan; Shukla, Sachet A.; Brown, Jennifer R.; Neuberg, Donna; Alessi, Dario R.; Zhang, Cheng-Zhong; Kharchenko, Peter V.; Livak, Kenneth J.; Wu, Catherine J.

2017-01-01

Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype–phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy. PMID:28679620

Single-cell genetic analysis validates cytopathological identification of circulating cancer cells in patients with clear cell renal cell carcinoma.

PubMed

Broncy, Lucile; Njima, Basma Ben; Méjean, Arnaud; Béroud, Christophe; Romdhane, Khaled Ben; Ilie, Marius; Hofman, Veronique; Muret, Jane; Hofman, Paul; Bouhamed, Habiba Chaabouni; Paterlini-Bréchot, And Patrizia

2018-04-13

Circulating Rare Cells (CRC) are non-haematological cells circulating in blood. They include Circulating Cancer Cells (CCC) and cells with uncertain malignant features (CRC-UMF) according to cytomorphology. Clear cell renal cell carcinomas frequently bear a mutated Von Hippel-Lindau (VHL) gene. To match blind genetic analysis of CRC and tumor samples with CRC cytopathological diagnosis. 29/30 patients harboured CRC (20 harboured CCC, 29 CRC-UMF) and 25/29 patients carried VHL mutations in their tumour. 205 single CRC (64 CCC, 141 CRC-UMF) provided genetic data. 57/57 CCC and 104/125 CRC-UMF from the 25 patients with VHL-mutated tumor carried the same VHL mutation detected in the tumor. Seven CCC and 16 CRC-UMF did not carry VHL mutations but were found in patients with wild-type VHL tumor tissue. All the CCC and 83,2% (104/125) of the CRC-UMF were found to carry the same VHL mutation identified in the corresponding tumorous tissue, validating cytopathological identification of CCC in patients with clear cell renal cell carcinoma. The blood of 30 patients with clear cell renal cell carcinoma was treated by ISET ® for CRC isolation, cytopathology and single-cell VHL mutations analysis, performed blindly and compared to VHL mutations of corresponding tumor tissues and leukocytes.

Single-cell multiplexed cytokine profiling of CD19 CAR-T cells reveals a diverse landscape of polyfunctional antigen-specific response.

PubMed

Xue, Qiong; Bettini, Emily; Paczkowski, Patrick; Ng, Colin; Kaiser, Alaina; McConnell, Timothy; Kodrasi, Olja; Quigley, Máire F; Heath, James; Fan, Rong; Mackay, Sean; Dudley, Mark E; Kassim, Sadik H; Zhou, Jing

2017-11-21

It remains challenging to characterize the functional attributes of chimeric antigen receptor (CAR)-engineered T cell product targeting CD19 related to potency and immunotoxicity ex vivo, despite promising in vivo efficacy in patients with B cell malignancies. We employed a single-cell, 16-plex cytokine microfluidics device and new analysis techniques to evaluate the functional profile of CD19 CAR-T cells upon antigen-specific stimulation. CAR-T cells were manufactured from human PBMCs transfected with the lentivirus encoding the CD19-BB-z transgene and expanded with anti-CD3/anti-CD28 coated beads. The enriched CAR-T cells were stimulated with anti-CAR or control IgG beads, stained with anti-CD4 RPE and anti-CD8 Alexa Fluor 647 antibodies, and incubated for 16 h in a single-cell barcode chip (SCBC). Each SCBC contains ~12,000 microchambers, covered with a glass slide that was pre-patterned with a complete copy of a 16-plex antibody array. Protein secretions from single CAR-T cells were captured and subsequently analyzed using proprietary software and new visualization methods. We demonstrate a new method for single-cell profiling of CD19 CAR-T pre-infusion products prepared from 4 healthy donors. CAR-T single cells exhibited a marked heterogeneity of cytokine secretions and polyfunctional (2+ cytokine) subsets specific to anti-CAR bead stimulation. The breadth of responses includes anti-tumor effector (Granzyme B, IFN-γ, MIP-1α, TNF-α), stimulatory (GM-CSF, IL-2, IL-8), regulatory (IL-4, IL-13, IL-22), and inflammatory (IL-6, IL-17A) functions. Furthermore, we developed two new bioinformatics tools for more effective polyfunctional subset visualization and comparison between donors. Single-cell, multiplexed, proteomic profiling of CD19 CAR-T product reveals a diverse landscape of immune effector response of CD19 CAR-T cells to antigen-specific challenge, providing a new platform for capturing CAR-T product data for correlative analysis. Additionally, such high dimensional data requires new visualization methods to further define precise polyfunctional response differences in these products. The presented biomarker capture and analysis system provides a more sensitive and comprehensive functional assessment of CAR-T pre-infusion products and may provide insights into the safety and efficacy of CAR-T cell therapy.

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.

Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level

NASA Astrophysics Data System (ADS)

Swiers, Gemma; Baumann, Claudia; O'Rourke, John; Giannoulatou, Eleni; Taylor, Stephen; Joshi, Anagha; Moignard, Victoria; Pina, Cristina; Bee, Thomas; Kokkaliaris, Konstantinos D.; Yoshimoto, Momoko; Yoder, Mervin C.; Frampton, Jon; Schroeder, Timm; Enver, Tariq; Göttgens, Berthold; de Bruijn, Marella F. T. R.

2013-12-01

Haematopoietic stem cells (HSCs) are the founding cells of the adult haematopoietic system, born during ontogeny from a specialized subset of endothelium, the haemogenic endothelium (HE) via an endothelial-to-haematopoietic transition (EHT). Although recently imaged in real time, the underlying mechanism of EHT is still poorly understood. We have generated a Runx1 +23 enhancer-reporter transgenic mouse (23GFP) for the prospective isolation of HE throughout embryonic development. Here we perform functional analysis of over 1,800 and transcriptional analysis of 268 single 23GFP+ HE cells to explore the onset of EHT at the single-cell level. We show that initiation of the haematopoietic programme occurs in cells still embedded in the endothelial layer, and is accompanied by a previously unrecognized early loss of endothelial potential before HSCs emerge. Our data therefore provide important insights on the timeline of early haematopoietic commitment.

Single-nucleus RNA-seq of differentiating human myoblasts reveals the extent of fate heterogeneity

PubMed Central

Zeng, Weihua; Jiang, Shan; Kong, Xiangduo; El-Ali, Nicole; Ball, Alexander R.; Ma, Christopher I-Hsing; Hashimoto, Naohiro; Yokomori, Kyoko; Mortazavi, Ali

2016-01-01

Myoblasts are precursor skeletal muscle cells that differentiate into fused, multinucleated myotubes. Current single-cell microfluidic methods are not optimized for capturing very large, multinucleated cells such as myotubes. To circumvent the problem, we performed single-nucleus transcriptome analysis. Using immortalized human myoblasts, we performed RNA-seq analysis of single cells (scRNA-seq) and single nuclei (snRNA-seq) and found them comparable, with a distinct enrichment for long non-coding RNAs (lncRNAs) in snRNA-seq. We then compared snRNA-seq of myoblasts before and after differentiation. We observed the presence of mononucleated cells (MNCs) that remained unfused and analyzed separately from multi-nucleated myotubes. We found that while the transcriptome profiles of myoblast and myotube nuclei are relatively homogeneous, MNC nuclei exhibited significant heterogeneity, with the majority of them adopting a distinct mesenchymal state. Primary transcripts for microRNAs (miRNAs) that participate in skeletal muscle differentiation were among the most differentially expressed lncRNAs, which we validated using NanoString. Our study demonstrates that snRNA-seq provides reliable transcriptome quantification for cells that are otherwise not amenable to current single-cell platforms. Our results further indicate that snRNA-seq has unique advantage in capturing nucleus-enriched lncRNAs and miRNA precursors that are useful in mapping and monitoring differential miRNA expression during cellular differentiation. PMID:27566152

The Mechanics of Single Cell and Collective Migration of Tumor Cells

PubMed Central

Lintz, Marianne; Muñoz, Adam; Reinhart-King, Cynthia A.

2017-01-01

Metastasis is a dynamic process in which cancer cells navigate the tumor microenvironment, largely guided by external chemical and mechanical cues. Our current understanding of metastatic cell migration has relied primarily on studies of single cell migration, most of which have been performed using two-dimensional (2D) cell culture techniques and, more recently, using three-dimensional (3D) scaffolds. However, the current paradigm focused on single cell movements is shifting toward the idea that collective migration is likely one of the primary modes of migration during metastasis of many solid tumors. Not surprisingly, the mechanics of collective migration differ significantly from single cell movements. As such, techniques must be developed that enable in-depth analysis of collective migration, and those for examining single cell migration should be adopted and modified to study collective migration to allow for accurate comparison of the two. In this review, we will describe engineering approaches for studying metastatic migration, both single cell and collective, and how these approaches have yielded significant insight into the mechanics governing each process. PMID:27814431

DTWscore: differential expression and cell clustering analysis for time-series single-cell RNA-seq data.

PubMed

Wang, Zhuo; Jin, Shuilin; Liu, Guiyou; Zhang, Xiurui; Wang, Nan; Wu, Deliang; Hu, Yang; Zhang, Chiping; Jiang, Qinghua; Xu, Li; Wang, Yadong

2017-05-23

The development of single-cell RNA sequencing has enabled profound discoveries in biology, ranging from the dissection of the composition of complex tissues to the identification of novel cell types and dynamics in some specialized cellular environments. However, the large-scale generation of single-cell RNA-seq (scRNA-seq) data collected at multiple time points remains a challenge to effective measurement gene expression patterns in transcriptome analysis. We present an algorithm based on the Dynamic Time Warping score (DTWscore) combined with time-series data, that enables the detection of gene expression changes across scRNA-seq samples and recovery of potential cell types from complex mixtures of multiple cell types. The DTWscore successfully classify cells of different types with the most highly variable genes from time-series scRNA-seq data. The study was confined to methods that are implemented and available within the R framework. Sample datasets and R packages are available at https://github.com/xiaoxiaoxier/DTWscore .

A droplet-based heterogeneous immunoassay for screening single cells secreting antigen-specific antibodies.

PubMed

Akbari, Samin; Pirbodaghi, Tohid

2014-09-07

High throughput heterogeneous immunoassays that screen antigen-specific antibody secreting cells are essential to accelerate monoclonal antibody discovery for therapeutic applications. Here, we introduce a heterogeneous single cell immunoassay based on alginate microparticles as permeable cell culture chambers. Using a microfluidic device, we encapsulated single antibody secreting cells in 35-40 μm diameter alginate microbeads. We functionalized the alginate to capture the secreted antibodies inside the microparticles, enabling single cell analysis and preventing the cross-talk between the neighboring encapsulated cells. We demonstrated non-covalent functionalization of alginate microparticles by adding three secondary antibodies to the alginate solution to form high molecular weight complexes that become trapped in the porous nanostructure of alginate and capture the secreted antibodies. We screened anti-TNF-alpha antibody-secreting cells from a mixture of antibody-secreting cells.

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

Visualization of IAV Genomes at the Single-Cell Level.

PubMed

Wang, Dan; Ma, Wenjun

2017-10-01

Different influenza A viruses (IAVs) infect the same cell in a host, and can subsequently produce new viruses through genome reassortment. By combining padlock probe RNA labeling with a single-cell analysis, a new approach effectively captures IAV genome trafficking and defines a time window for genome reassortment from same-cell coinfections. Copyright © 2017 Elsevier Ltd. All rights reserved.

Origins of cell-to-cell bioprocessing diversity and implications of the extracellular environment revealed at the single-cell level

DOE PAGES

Vasdekis, A. E.; Silverman, A. M.; Stephanopoulos, G.

2015-12-14

We probed the lipid expression dynamics of the oleaginous yeast Yarrowia Lipolytica. We observed that neutral lipid expression is sporadic. By performing single-cell analysis, we found that such noise emanates from the metabolic reaction level. Our results provide an alternative insight into the regulation and phenotypic variability of lipogenesis.

Micromagnetic Cancer Cell Immobilization and Release for Real-Time Single Cell Analysis

NASA Astrophysics Data System (ADS)

Jaiswal, Devina; Rad, Armin Tahmasbi; Nieh, Mu-Ping; Claffey, Kevin P.; Hoshino, Kazunori

2017-04-01

Understanding the interaction of live cells with macromolecules is crucial for designing efficient therapies. Considering the functional heterogeneity found in cancer cells, real-time single cell analysis is necessary to characterize responses. In this study, we have designed and fabricated a microfluidic channel with patterned micromagnets which can temporarily immobilize the cells during analysis and release them after measurements. The microchannel is composed of plain coverslip top and bottom panels to facilitate easy microscopic observation and undisturbed application of analytes to the cells. Cells labeled with functionalized magnetic beads were immobilized in the device with an efficiency of 90.8±3.6%. Since the micromagnets are made of soft magnetic material (Ni), they released cells when external magnetic field was turned off from the channel. This allows the reuse of the channel for a new sample. As a model drug analysis, the immobilized breast cancer cells (MCF7) were exposed to fluorescent lipid nanoparticles and association and dissociation were measured through fluorescence analysis. Two concentrations of nanoparticles, 0.06 μg/ml and 0.08 μg/ml were tested and time lapse images were recorded and analyzed. The microfluidic device was able to provide a microenvironment for sample analysis, making it an efficient platform for real-time analysis.

Quantitative Single-Cell mRNA Analysis in Hydrogel Beads.

PubMed

Rakszewska, Agata; Stolper, Rosa J; Kolasa, Anna B; Piruska, Aigars; Huck, Wilhelm T S

2016-06-01

In recent years, technologies capable of analyzing single cells have emerged that are transforming many fields of biological research. Herein we report how DNA-functionalized hydrogel beads can serve as a matrix to capture mRNA from lysed single cells. mRNA quantification free of pre-amplification bias is ensured by using padlock probes and rolling circle amplification followed by hybridization with fluorescent probes. The number of transcripts in individual cells is assessed by simply counting fluorescent dots inside gel beads. The method extends the potential of existing techniques and provides a general platform for capturing molecules of interest from single cells. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Single-Cell mRNA-Seq Using the Fluidigm C1 System and Integrated Fluidics Circuits.

PubMed

Gong, Haibiao; Do, Devin; Ramakrishnan, Ramesh

2018-01-01

Single-cell mRNA-seq is a valuable tool to dissect expression profiles and to understand the regulatory network of genes. Microfluidics is well suited for single-cell analysis owing both to the small volume of the reaction chambers and easiness of automation. Here we describe the workflow of single-cell mRNA-seq using C1 IFC, which can isolate and process up to 96 cells. Both on-chip procedure (lysis, reverse transcription, and preamplification PCR) and off-chip sequencing library preparation protocols are described. The workflow generates full-length mRNA information, which is more valuable compared to 3' end counting method for many applications.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells.

PubMed

Stylianidou, Stella; Brennan, Connor; Nissen, Silas B; Kuwada, Nathan J; Wiggins, Paul A

2016-11-01

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution. © 2016 John Wiley & Sons Ltd.

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.

Carbon Nanotube Based Devices for Intracellular Analysis

NASA Astrophysics Data System (ADS)

Singhal, Riju Mohan

Scientific investigations on individual cells have gained increasing attention in recent years as efforts are being made to understand cellular functioning in complex processes, such as cell division during embryonic development, and owing to realization of heterogeneity amongst a population of a single cell type (for instance, certain individual cancer cells being immune to chemotherapy). Therefore devices enabling electrochemical detection, spectroscopy, optical observations, and separation techniques, along with cell piercing and fluid transfer capabilities at the intra-cellular level, are required. Glass pipettes have conventionally been used for single cell interrogation, however their poor mechanical properties and an intrusive conical geometry have led to limited precision and frequent cell damage or death, justifying research efforts to develop novel, non-intrusive cell probes. Carbon nanotubes (CNTs) are known for their superior physical properties and tunable chemical structure. They possess a high aspect ratio and offer minimally invasive thin carbon walls and tubular geometry. Moreover, possibility of chemical functionalization of CNTs enables multi-functional probes. In this dissertation, novel nanofluidic instruments that have nanostructured carbon tips will be presented along with techniques that utilize the exceptional physical properties of carbon nanotubes, to take miniature biomedical instrumentation to the next level. New methods for fabricating the probes were rigorously developed and their operation was extensively studied. The devices were mechanically robust and were used to inject liquids to a single cell, detect electrochemical signals and enable surface enhanced Raman spectroscopy (SERS) while inducing minimal harm to the cell. Particular attention was focused on the CVD process-which was used to deposit carbon, fluid flow through the nanotubes, and separation of chemical species (atto-liter chromatography) at the nanometer scale that would potentially lead to the highly sought after "selective component extraction" and analysis from a single cell. These multi-functional devices therefore provide a picture of the physiological state of a living cell and function as endoscopes for single cell analysis.

Single-Cell Isolation of Circulating Tumor Cells from Whole Blood by Lateral Magnetophoretic Microseparation and Microfluidic Dispensing.

PubMed

Kim, Jinho; Cho, Hyungseok; Han, Song-I; Han, Ki-Ho

2016-05-03

This paper introduces a single-cell isolation technology for circulating tumor cells (CTCs) using a microfluidic device (the "SIM-Chip"). The SIM-Chip comprises a lateral magnetophoretic microseparator and a microdispenser as a two-step cascade platform. First, CTCs were enriched from whole blood by the lateral magnetophoretic microseparator based on immunomagnetic nanobeads. Next, the enriched CTCs were electrically identified by single-cell impedance cytometer and isolated as single cells using the microshooter. Using 200 μL of whole blood spiked with 50 MCF7 breast cancer cells, the analysis demonstrated that the single-cell isolation efficiency of the SIM-Chip was 82.4%, and the purity of the isolated MCF7 cells with respect to WBCs was 92.45%. The data also showed that the WBC depletion rate of the SIM-Chip was 2.5 × 10(5) (5.4-log). The recovery rates were around 99.78% for spiked MCF7 cells ranging in number from 10 to 90. The isolated single MCF7 cells were intact and could be used for subsequent downstream genetic assays, such as RT-PCR. Single-cell culture evaluation of the proliferation of MCF7 cells isolated by the SIM-Chip showed that 84.1% of cells at least doubled in 5 days. Consequently, the SIM-Chip could be used for single-cell isolation of rare target cells from whole blood with high purity and recovery without cell damage.

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

Droplet barcoding for single cell transcriptomics applied to embryonic stem cells

PubMed Central

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

2015-01-01

Summary 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 LIF withdrawal. The reproducibility of these high-throughput single cell data allowed us to deconstruct cell populations and infer gene expression relationships. PMID:26000487

Molecular profiling of single circulating tumor cells from lung cancer patients.

PubMed

Park, Seung-Min; Wong, Dawson J; Ooi, Chin Chun; Kurtz, David M; Vermesh, Ophir; Aalipour, Amin; Suh, Susie; Pian, Kelsey L; Chabon, Jacob J; Lee, Sang Hun; Jamali, Mehran; Say, Carmen; Carter, Justin N; Lee, Luke P; Kuschner, Ware G; Schwartz, Erich J; Shrager, Joseph B; Neal, Joel W; Wakelee, Heather A; Diehn, Maximilian; Nair, Viswam S; Wang, Shan X; Gambhir, Sanjiv S

2016-12-27

Circulating tumor cells (CTCs) are established cancer biomarkers for the "liquid biopsy" of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non-small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.

An automated image analysis framework for segmentation and division plane detection of single live Staphylococcus aureus cells which can operate at millisecond sampling time scales using bespoke Slimfield microscopy

NASA Astrophysics Data System (ADS)

Wollman, Adam J. M.; Miller, Helen; Foster, Simon; Leake, Mark C.

2016-10-01

Staphylococcus aureus is an important pathogen, giving rise to antimicrobial resistance in cell strains such as Methicillin Resistant S. aureus (MRSA). Here we report an image analysis framework for automated detection and image segmentation of cells in S. aureus cell clusters, and explicit identification of their cell division planes. We use a new combination of several existing analytical tools of image analysis to detect cellular and subcellular morphological features relevant to cell division from millisecond time scale sampled images of live pathogens at a detection precision of single molecules. We demonstrate this approach using a fluorescent reporter GFP fused to the protein EzrA that localises to a mid-cell plane during division and is involved in regulation of cell size and division. This image analysis framework presents a valuable platform from which to study candidate new antimicrobials which target the cell division machinery, but may also have more general application in detecting morphologically complex structures of fluorescently labelled proteins present in clusters of other types of cells.

Single-Cell Electric Lysis on an Electroosmotic-Driven Microfluidic Chip with Arrays of Microwells

PubMed Central

Jen, Chun-Ping; Amstislavskaya, Tamara G.; Liu, Ya-Hui; Hsiao, Ju-Hsiu; Chen, Yu-Hung

2012-01-01

Accurate analysis at the single-cell level has become a highly attractive tool for investigating cellular content. An electroosmotic-driven microfluidic chip with arrays of 30-μm-diameter microwells was developed for single-cell electric lysis in the present study. The cellular occupancy in the microwells when the applied voltage was 5 V (82.4%) was slightly higher than that at an applied voltage of 10 V (81.8%). When the applied voltage was increased to 15 V, the cellular occupancy in the microwells dropped to 64.3%. More than 50% of the occupied microwells contain individual cells. The results of electric lysis experiments at the single-cell level indicate that the cells were gradually lysed as the DC voltage of 30 V was applied; the cell was fully lysed after 25 s. Single-cell electric lysis was demonstrated in the proposed microfluidic chip, which is suitable for high-throughput cell lysis. PMID:22969331

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.

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells.

PubMed

Han, Kyung Yeon; Kim, Kyu-Tae; Joung, Je-Gun; Son, Dae-Soon; Kim, Yeon Jeong; Jo, Areum; Jeon, Hyo-Jeong; Moon, Hui-Sung; Yoo, Chang Eun; Chung, Woosung; Eum, Hye Hyeon; Kim, Sangmin; Kim, Hong Kwan; Lee, Jeong Eon; Ahn, Myung-Ju; Lee, Hae-Ock; Park, Donghyun; Park, Woong-Yang

2018-01-01

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level. © 2018 Han et al.; Published by Cold Spring Harbor Laboratory Press.

SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells

PubMed Central

Han, Kyung Yeon; Kim, Kyu-Tae; Joung, Je-Gun; Son, Dae-Soon; Kim, Yeon Jeong; Jo, Areum; Jeon, Hyo-Jeong; Moon, Hui-Sung; Yoo, Chang Eun; Chung, Woosung; Eum, Hye Hyeon; Kim, Sangmin; Kim, Hong Kwan; Lee, Jeong Eon; Ahn, Myung-Ju; Lee, Hae-Ock; Park, Donghyun; Park, Woong-Yang

2018-01-01

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level. PMID:29208629

Linnorm: improved statistical analysis for single cell RNA-seq expression data

PubMed Central

Yip, Shun H.; Wang, Panwen; Kocher, Jean-Pierre A.; Sham, Pak Chung

2017-01-01

Abstract Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy. PMID:28981748

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

PubMed

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

2018-06-01

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

INVESTIGATION OF DNA REPAIR BY SISTER CHROMATID EXCHANGE (SCE) ANALYSIS AND THE ALKALINE SINGLE CELL GEL ASSAY (SCG) IN MAMMALIAN GO-LYMPHOCYTES AFTER IN VITRO EXPOSURE TO ETHYLENE OXIDE (EO)

EPA Science Inventory

Investigation ofDNA Repair by Sister Chromatid Exchange (SCE) Analysis and the Alkaline Single Cell Gel Assay (SCG) in Mammalian Go-Lymphocytes after In Vitro Exposure to Ethylene Oxide (EO).

EO is a large volume chemical used primarily as an intermediate in manufacturing...

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

Gene Expression in Single Cells Isolated from the CWR-R1 Prostate Cancer Cell Line and Human Prostate Tissue Based on the Side Population Phenotype.

PubMed

Gangavarapu, Kalyan J; Miller, Austin; Huss, Wendy J

2016-09-01

Defining biological signals at the single cell level can identify cancer initiating driver mutations. Techniques to isolate single cells such as microfluidics sorting and magnetic capturing systems have limitations such as: high cost, labor intense, and the requirement of a large number of cells. Therefore, the goal of our current study is to identify a cost and labor effective, reliable, and reproducible technique that allows single cell isolation for analysis to promote regular laboratory use, including standard reverse transcription PCR (RT-PCR). In the current study, we utilized single prostate cells isolated from the CWR-R1 prostate cancer cell line and human prostate clinical specimens, based on the ATP binding cassette (ABC) transporter efflux of dye cycle violet (DCV), side population assay. Expression of four genes: ABCG2; Aldehyde dehydrogenase1A1 (ALDH1A1); androgen receptor (AR); and embryonic stem cell marker, Oct-4, were determined. Results from the current study in the CWR-R1 cell line showed ABCG2 and ALDH1A1 gene expression in 67% of single side population cells and in 17% or 100% of non-side population cells respectively. Studies using single cells isolated from clinical specimens showed that the Oct-4 gene is detected in only 22% of single side population cells and in 78% of single non-side population cells. Whereas, AR gene expression is in 100% single side population and non-side population cells isolated from the same human prostate clinical specimen. These studies show that performing RT-PCR on single cells isolated by FACS can be successfully conducted to determine gene expression in single cells from cell lines and enzymatically digested tissue. While these studies provide a simple yes/no expression readout, the more sensitive quantitative RT-PCR would be able to provide even more information if necessary.

Gene Expression in Single Cells Isolated from the CWR-R1 Prostate Cancer Cell Line and Human Prostate Tissue Based on the Side Population Phenotype

PubMed Central

Gangavarapu, Kalyan J; Miller, Austin; Huss, Wendy J

2016-01-01

Defining biological signals at the single cell level can identify cancer initiating driver mutations. Techniques to isolate single cells such as microfluidics sorting and magnetic capturing systems have limitations such as: high cost, labor intense, and the requirement of a large number of cells. Therefore, the goal of our current study is to identify a cost and labor effective, reliable, and reproducible technique that allows single cell isolation for analysis to promote regular laboratory use, including standard reverse transcription PCR (RT-PCR). In the current study, we utilized single prostate cells isolated from the CWR-R1 prostate cancer cell line and human prostate clinical specimens, based on the ATP binding cassette (ABC) transporter efflux of dye cycle violet (DCV), side population assay. Expression of four genes: ABCG2; Aldehyde dehydrogenase1A1 (ALDH1A1); androgen receptor (AR); and embryonic stem cell marker, Oct-4, were determined. Results from the current study in the CWR-R1 cell line showed ABCG2 and ALDH1A1 gene expression in 67% of single side population cells and in 17% or 100% of non-side population cells respectively. Studies using single cells isolated from clinical specimens showed that the Oct-4 gene is detected in only 22% of single side population cells and in 78% of single non-side population cells. Whereas, AR gene expression is in 100% single side population and non-side population cells isolated from the same human prostate clinical specimen. These studies show that performing RT-PCR on single cells isolated by FACS can be successfully conducted to determine gene expression in single cells from cell lines and enzymatically digested tissue. While these studies provide a simple yes/no expression readout, the more sensitive quantitative RT-PCR would be able to provide even more information if necessary. PMID:27785389

Development of Nano/Micro Probes for Femtoliter Volume and Single Cell Measurements

NASA Astrophysics Data System (ADS)

Gao, Yang

Single cell analysis has recently emerged as an important field of biomedical re- search. It is now clear that heterogeneity of cell metabolism functions in complex biological systems is correlated to changes in biological function and disease processes. A variety of nano/micro probes were developed to enable investigation of cells properties such as membrane stiffness, pH value. However, very few designs were focused on single cell metabolic function studies. There is a critical need for technologies that provide analysis of heterogeneity of cell metabolic functions, especially on metabolism. Nevertheless, the few existing approaches suffer from fundamental defects and need to be improved. This work focused on developing nano/micro probes that are suitable for single cell functionality investigation. Both types of probes are designed to measure cell-to-cell/time-to-time heterogeneity in metabolic functions over a long period of time. Lab-made carbon nanoprobes were developed especially for electro-physiological measurement. The unique structure of the carbon nanoprobes makes them suitable for important intracellular applications like trans-membrane potential measurements and various electrochemical measurement for cell function studies. While it is important of have ability to carry out intracellular measure, there are also occasions where the information of a cell as a whole is collected. One of the most important indicator of a cells metabolic functions is cell respiration rate/oxygen consumption rate. A micro-perfusion based multi-functional single cell sensing probe was the developed to carry out measurements on cell as a whole. Formed by a double-barrel theta pipette, the perfusion flow enables the direct measurement of the metabolic flux for example oxygen consumption rate. In conclusion, this work developed nano/micro-probes as novel single cell investigation tools. The data acquired from these tools could provide valuable assistance on applications including cell metabolism studies, cancer diagnoses, and therapy evaluations.

DAPNe with micro-capillary separatory chemistry-coupled to MALDI-MS for the analysis of polar and non-polar lipid metabolism in one cell

NASA Astrophysics Data System (ADS)

Hamilton, Jason S.; Aguilar, Roberto; Petros, Robby A.; Verbeck, Guido F.

2017-05-01

The cellular metabolome is considered to be a representation of cellular phenotype and cellular response to changes to internal or external events. Methods to expand the coverage of the expansive physiochemical properties that makeup the metabolome currently utilize multi-step extractions and chromatographic separations prior to chemical detection, leading to lengthy analysis times. In this study, a single-step procedure for the extraction and separation of a sample using a micro-capillary as a separatory funnel to achieve analyte partitioning within an organic/aqueous immiscible solvent system is described. The separated analytes are then spotted for MALDI-MS imaging and distribution ratios are calculated. Initially, the method is applied to standard mixtures for proof of partitioning. The extraction of an individual cell is non-reproducible; therefore, a broad chemical analysis of metabolites is necessary and will be illustrated with the one-cell analysis of a single Snu-5 gastric cancer cell taken from a cellular suspension. The method presented here shows a broad partitioning dynamic range as a single-step method for lipid analysis demonstrating a decrease in ion suppression often present in MALDI analysis of lipids.

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

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.

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.

Modeling Bi-modality Improves Characterization of Cell Cycle on Gene Expression in Single Cells

PubMed Central

Danaher, Patrick; Finak, Greg; Krouse, Michael; Wang, Alice; Webster, Philippa; Beechem, Joseph; Gottardo, Raphael

2014-01-01

Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome. PMID:25032992

Ecology of uncultured Prochlorococcus clades revealed through single-cell genomics and biogeographic analysis

PubMed Central

Malmstrom, Rex R; Rodrigue, Sébastien; Huang, Katherine H; Kelly, Libusha; Kern, Suzanne E; Thompson, Anne; Roggensack, Sara; Berube, Paul M; Henn, Matthew R; Chisholm, Sallie W

2013-01-01

Prochlorococcus is the numerically dominant photosynthetic organism throughout much of the world's oceans, yet little is known about the ecology and genetic diversity of populations inhabiting tropical waters. To help close this gap, we examined natural Prochlorococcus communities in the tropical Pacific Ocean using a single-cell whole-genome amplification and sequencing. Analysis of the gene content of just 10 single cells from these waters added 394 new genes to the Prochlorococcus pan-genome—that is, genes never before seen in a Prochlorococcus cell. Analysis of marker genes, including the ribosomal internal transcribed sequence, from dozens of individual cells revealed several representatives from two uncultivated clades of Prochlorococcus previously identified as HNLC1 and HNLC2. While the HNLC clades can dominate Prochlorococcus communities under certain conditions, their overall geographic distribution was highly restricted compared with other clades of Prochlorococcus. In the Atlantic and Pacific oceans, these clades were only found in warm waters with low Fe and high inorganic P levels. Genomic analysis suggests that at least one of these clades thrives in low Fe environments by scavenging organic-bound Fe, a process previously unknown in Prochlorococcus. Furthermore, the capacity to utilize organic-bound Fe appears to have been acquired horizontally and may be exchanged among other clades of Prochlorococcus. Finally, one of the single Prochlorococcus cells sequenced contained a partial genome of what appears to be a prophage integrated into the genome. PMID:22895163

Live single cell functional phenotyping in droplet nano-liter reactors

NASA Astrophysics Data System (ADS)

Konry, Tania; Golberg, Alexander; Yarmush, Martin

2013-11-01

While single cell heterogeneity is present in all biological systems, most studies cannot address it due to technical limitations. Here we describe a nano-liter droplet microfluidic-based approach for stimulation and monitoring of surfaceand secreted markers of live single immune dendritic cells (DCs) as well as monitoring the live T cell/DC interaction. This nano-liter in vivo simulating microenvironment allows delivering various stimuli reagents to each cell and appropriate gas exchanges which are necessary to ensure functionality and viability of encapsulated cells. Labeling bioassay and microsphere sensors were integrated into nano-liter reaction volume of the droplet to monitor live single cell surface markers and secretion analysis in the time-dependent fashion. Thus live cell stimulation, secretion and surface monitoring can be obtained simultaneously in distinct microenvironment, which previously was possible using complicated and multi-step in vitro and in vivo live-cell microscopy, together with immunological studies of the outcome secretion of cellular function.

Single-cell technologies to study the immune system.

PubMed

Proserpio, Valentina; Mahata, Bidesh

2016-02-01

The immune system is composed of a variety of cells that act in a coordinated fashion to protect the organism against a multitude of different pathogens. The great variability of existing pathogens corresponds to a similar high heterogeneity of the immune cells. The study of individual immune cells, the fundamental unit of immunity, has recently transformed from a qualitative microscopic imaging to a nearly complete quantitative transcriptomic analysis. This shift has been driven by the rapid development of multiple single-cell technologies. These new advances are expected to boost the detection of less frequent cell types and transient or intermediate cell states. They will highlight the individuality of each single cell and greatly expand the resolution of current available classifications and differentiation trajectories. In this review we discuss the recent advancement and application of single-cell technologies, their limitations and future applications to study the immune system. © 2015 The Authors. Immunology Published by John Wiley & Sons Ltd.

Single cell adhesion force measurement for cell viability identification using an AFM cantilever-based micro putter

NASA Astrophysics Data System (ADS)

Shen, Yajing; Nakajima, Masahiro; Kojima, Seiji; Homma, Michio; Kojima, Masaru; Fukuda, Toshio

2011-11-01

Fast and sensitive cell viability identification is a key point for single cell analysis. To address this issue, this paper reports a novel single cell viability identification method based on the measurement of single cell shear adhesion force using an atomic force microscopy (AFM) cantilever-based micro putter. Viable and nonviable yeast cells are prepared and put onto three kinds of substrate surfaces, i.e. tungsten probe, gold and ITO substrate surfaces. A micro putter is fabricated from the AFM cantilever by focused ion beam etching technique. The spring constant of the micro putter is calibrated using the nanomanipulation approach. The shear adhesion force between the single viable or nonviable cell and each substrate is measured using the micro putter based on the nanorobotic manipulation system inside an environmental scanning electron microscope. The adhesion force is calculated based on the deflection of the micro putter beam. The results show that the adhesion force of the viable cell to the substrate is much larger than that of the nonviable cell. This identification method is label free, fast, sensitive and can give quantitative results at the single cell level.

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.

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.

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.

Primary Cell Culture of Live Neurosurgically Resected Aged Adult Human Brain Cells and Single Cell Transcriptomics.

PubMed

Spaethling, Jennifer M; Na, Young-Ji; Lee, Jaehee; Ulyanova, Alexandra V; Baltuch, Gordon H; Bell, Thomas J; Brem, Steven; Chen, H Isaac; Dueck, Hannah; Fisher, Stephen A; Garcia, Marcela P; Khaladkar, Mugdha; Kung, David K; Lucas, Timothy H; O'Rourke, Donald M; Stefanik, Derek; Wang, Jinhui; Wolf, John A; Bartfai, Tamas; Grady, M Sean; Sul, Jai-Yoon; Kim, Junhyong; Eberwine, James H

2017-01-17

Investigation of human CNS disease and drug effects has been hampered by the lack of a system that enables single-cell analysis of live adult patient brain cells. We developed a culturing system, based on a papain-aided procedure, for resected adult human brain tissue removed during neurosurgery. We performed single-cell transcriptomics on over 300 cells, permitting identification of oligodendrocytes, microglia, neurons, endothelial cells, and astrocytes after 3 weeks in culture. Using deep sequencing, we detected over 12,000 expressed genes, including hundreds of cell-type-enriched mRNAs, lncRNAs and pri-miRNAs. We describe cell-type- and patient-specific transcriptional hierarchies. Single-cell transcriptomics on cultured live adult patient derived cells is a prime example of the promise of personalized precision medicine. Because these cells derive from subjects ranging in age into their sixties, this system permits human aging studies previously possible only in rodent systems. Copyright © 2017 The Author(s). Published by Elsevier Inc. 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.

Comparison of the clinical efficacy between single-agent and dual-agent concurrent chemoradiotherapy in the treatment of unresectable esophageal squamous cell carcinoma: a multicenter retrospective analysis.

PubMed

Li, Jie; Gong, Youling; Diao, Peng; Huang, Qingmei; Wen, Yixue; Lin, Binwei; Cai, Hongwei; Tian, Honggang; He, Bing; Ji, Lanlan; Guo, Ping; Miao, Jidong; Du, Xiaobo

2018-01-22

Some Chinese patients with esophageal squamous cell carcinomaare often treated with single-agent concurrent chemoradiotherapy. However, no results have been reported from randomized controlled clinical trials comparing single-agent with double-agent concurrent chemoradiotherapy. It therefore remains unclear whether these regimens are equally clinically effective. In this study, we retrospectively analyzed and compared the therapeutic effects of single-agent and double-agent concurrent chemoradiotherapy in patients with unresectable esophageal squamous cell carcinoma. This study enrolled 168 patients who received definitive concurrent chemoradiotherapy for locally advanced unresectable esophageal squamous carcinoma at 10 hospitals between 2010 and 2015. We evaluated survival time and toxicity. The Kaplan-Meier method was used to estimate survival data. The log-rank test was used in univariate analysis A Cox proportional hazards regression model was used to conduct a multivariate analysis of the effects of prognostic factors on survival. In this study, 100 (59.5%) and 68 patients (40.5%) received single-agent and dual-agent combination chemoradiotherapy, respectively. The estimate 5-year progression-free survival (PFS) rate and overall survival (OS) rate of dual-agent therapy was higher than that of single-agent therapy (52.5% and 40.9%, 78.2% and 60.7%, respectively), but there were no significant differences (P = 0.367 and 0.161, respectively). Multivariate analysis showed that sex, age,and radiotherapy dose had no significant effects on OS or PFS. Only disease stage was associated with OS and PFS in the multivariable analysis (P = 0.006 and 0.003, respectively). In dual-agent group, the incidence of acute toxicity and the incidence of 3 and4 grade toxicity were higher than single-agent group. The 5-year PFS and OS rates of dual-agent therapy were higher than those of single-agent concurrent chemoradiotherapy for patients with unresectable esophageal squamous cell carcinoma; however, there were no significant differences in univariate analysis and multivariable analysis. Single-agent concurrent chemotherapy had less toxicity than a double-drug regimen. Therefore, we suggest that single therapis not inferior to dual therapy y. In the future, we aim to confirm our hypothesis through a prospective randomized study.

Single cell and single molecule techniques for the analysis of the epigenome

NASA Astrophysics Data System (ADS)

Wallin, Christopher Benjamin

Epigenetic regulation is a critical biological process for the health and development of a cell. Epigenetic regulation is facilitated by covalent modifications to the underlying DNA and chromatin proteins. A fundamental understanding of these epigenetic modifications and their associated interactions at the molecular scale is necessary to explain phenomena including cellular identity, stem cell plasticity, and neoplastic transformation. It is widely known that abnormal epigenetic profiles have been linked to many diseases, most notably cancer. While the field of epigenetics has progressed rapidly with conventional techniques, significant advances remain to be made with respect to combinatoric analysis of epigenetic marks and single cell epigenetics. Therefore, in this dissertation, I will discuss our development of devices and methodologies to address these pertinent issues. First, we designed a preparatory polydimethylsiloxane (PDMS) microdevice for the extraction, purification, and stretching of human chromosomal DNA and chromatin from small cell populations down to a single cell. The valveless device captures cells by size exclusion within the micropillars, entraps the DNA or chromatin in the micropillars after cell lysis, purifies away the cellular debris, and fluorescently labels the DNA and/or chromatin all within a single reaction chamber. With the device, we achieve nearly 100% extraction efficiency of the DNA. The device is also used for in-channel immunostaining of chromatin followed by downstream single molecule chromatin analysis in nanochannels (SCAN). Second, using multi-color, time-correlated single molecule measurements in nanochannels, simultaneous coincidence detection of 2 epigenetic marks is demonstrated. Coincidence detection of 3 epigenetic marks is also established using a pulsed interleaved excitation scheme. With these two promising results, genome-wide quantification of epigenetic marks was pursued. Unfortunately, quantitative SCAN never materialized. Reasons for this, including poor signal to background, are explained in detail. Third, development of mobility-SCAN, an analytical technique for measuring and analyzing single molecules based on their fluorescent signature and their electrophoretic mobility in nanochannels is described. We use the technique to differentiate biomolecules from complex mixtures and derive parameters such as diffusion coefficients and effective charges. Finally, the device is used to detect binding interactions of various complexes similar to affinity capillary electrophoresis, but on a single molecule level. Fourth, we conclude by briefly discussing SCAN-sort, a technique to sort individual chromatin molecules based on their fluorescent emissions for further downstream analysis such as DNA sequencing. We demonstrate a 2-fold enrichment of chromatin from sorting and discuss possible system modifications for better performance in the future.

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

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.

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.

Precision toxicology based on single cell sequencing: an evolving trend in toxicological evaluations and mechanism exploration.

PubMed

Zhang, Boyang; Huang, Kunlun; Zhu, Liye; Luo, Yunbo; Xu, Wentao

2017-07-01

In this review, we introduce a new concept, precision toxicology: the mode of action of chemical- or drug-induced toxicity can be sensitively and specifically investigated by isolating a small group of cells or even a single cell with typical phenotype of interest followed by a single cell sequencing-based analysis. Precision toxicology can contribute to the better detection of subtle intracellular changes in response to exogenous substrates, and thus help researchers find solutions to control or relieve the toxicological effects that are serious threats to human health. We give examples for single cell isolation and recommend laser capture microdissection for in vivo studies and flow cytometric sorting for in vitro studies. In addition, we introduce the procedures for single cell sequencing and describe the expected application of these techniques to toxicological evaluations and mechanism exploration, which we believe will become a trend in toxicology.

Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing.

PubMed

Renthal, William

2018-01-01

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

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

Explanation for excessive DNA single-strand breaks and endogenous repair foci in pluripotent mouse embryonic stem cells.

PubMed

Banáth, J P; Bañuelos, C A; Klokov, D; MacPhail, S M; Lansdorp, P M; Olive, P L

2009-05-01

Pluripotent mouse embryonic stem cells (mES cells) exhibit approximately 100 large gammaH2AX repair foci in the absence of measurable numbers of DNA double-strand breaks. Many of these cells also show excessive numbers of DNA single-strand breaks (>10,000 per cell) when analyzed using the alkaline comet assay. To understand the reasons for these unexpected observations, various methods for detecting DNA strand breaks were applied to wild-type mES cells and to mES cells lacking H2AX, ATM, or DNA-PKcs. H2AX phosphorylation and expression of other repair complexes were measured using flow and image analysis of antibody-stained cells. Results indicate that high numbers of endogenous gammaH2AX foci and single-strand breaks in pluripotent mES cells do not require ATM or DNA-PK kinase activity and appear to be associated with global chromatin decondensation rather than pre-existing DNA damage. This will limit applications of gammaH2AX foci analysis in mES cells to relatively high levels of initial or residual DNA damage. Excessive numbers of single-strand breaks in the alkaline comet assay can be explained by the vulnerability of replicating chromatin in mES cells to osmotic shock. This suggests that caution is needed in interpreting results with the alkaline comet assay when applied to certain cell types or after treatment with agents that make chromatin vulnerable to osmotic changes. Differentiation of mES cells caused a reduction in histone acetylation, gammaH2AX foci intensity, and DNA single-strand breakage, providing a link between chromatin structural organization, excessive gammaH2AX foci, and sensitivity of replicating mES cell chromatin to osmotic shock.

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

PubMed Central

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

2018-01-01

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

Multi-level characterization of balanced inhibitory-excitatory cortical neuron network derived from human pluripotent stem cells.

PubMed

Nadadhur, Aishwarya G; Emperador Melero, Javier; Meijer, Marieke; Schut, Desiree; Jacobs, Gerbren; Li, Ka Wan; Hjorth, J J Johannes; Meredith, Rhiannon M; Toonen, Ruud F; Van Kesteren, Ronald E; Smit, August B; Verhage, Matthijs; Heine, Vivi M

2017-01-01

Generation of neuronal cultures from induced pluripotent stem cells (hiPSCs) serve the studies of human brain disorders. However we lack neuronal networks with balanced excitatory-inhibitory activities, which are suitable for single cell analysis. We generated low-density networks of hPSC-derived GABAergic and glutamatergic cortical neurons. We used two different co-culture models with astrocytes. We show that these cultures have balanced excitatory-inhibitory synaptic identities using confocal microscopy, electrophysiological recordings, calcium imaging and mRNA analysis. These simple and robust protocols offer the opportunity for single-cell to multi-level analysis of patient hiPSC-derived cortical excitatory-inhibitory networks; thereby creating advanced tools to study disease mechanisms underlying neurodevelopmental disorders.

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

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

Microfluidic immunocapture of circulating pancreatic cells using parallel EpCAM and MUC1 capture: characterization, optimization and downstream analysis.

PubMed

Thege, Fredrik I; Lannin, Timothy B; Saha, Trisha N; Tsai, Shannon; Kochman, Michael L; Hollingsworth, Michael A; Rhim, Andrew D; Kirby, Brian J

2014-05-21

We have developed and optimized a microfluidic device platform for the capture and analysis of circulating pancreatic cells (CPCs) and pancreatic circulating tumor cells (CTCs). Our platform uses parallel anti-EpCAM and cancer-specific mucin 1 (MUC1) immunocapture in a silicon microdevice. Using a combination of anti-EpCAM and anti-MUC1 capture in a single device, we are able to achieve efficient capture while extending immunocapture beyond single marker recognition. We also have detected a known oncogenic KRAS mutation in cells spiked in whole blood using immunocapture, RNA extraction, RT-PCR and Sanger sequencing. To allow for downstream single-cell genetic analysis, intact nuclei were released from captured cells by using targeted membrane lysis. We have developed a staining protocol for clinical samples, including standard CTC markers; DAPI, cytokeratin (CK) and CD45, and a novel marker of carcinogenesis in CPCs, mucin 4 (MUC4). We have also demonstrated a semi-automated approach to image analysis and CPC identification, suitable for clinical hypothesis generation. Initial results from immunocapture of a clinical pancreatic cancer patient sample show that parallel capture may capture more of the heterogeneity of the CPC population. With this platform, we aim to develop a diagnostic biomarker for early pancreatic carcinogenesis and patient risk stratification.

Single cell dual adherent-suspension co-culture micro-environment for studying tumor-stromal interactions with functionally selected cancer stem-like cells.

PubMed

Chen, Yu-Chih; Zhang, Zhixiong; Fouladdel, Shamileh; Deol, Yadwinder; Ingram, Patrick N; McDermott, Sean P; Azizi, Ebrahim; Wicha, Max S; Yoon, Euisik

2016-08-07

Considerable evidence suggests that cancer stem-like cells (CSCs) are critical in tumor pathogenesis, but their rarity and transience has led to much controversy about their exact nature. Although CSCs can be functionally identified using dish-based tumorsphere assays, it is difficult to handle and monitor single cells in dish-based approaches; single cell-based microfluidic approaches offer better control and reliable single cell derived sphere formation. However, like normal stem cells, CSCs are heavily regulated by their microenvironment, requiring tumor-stromal interactions for tumorigenic and proliferative behaviors. To enable single cell derived tumorsphere formation within a stromal microenvironment, we present a dual adherent/suspension co-culture device, which combines a suspension environment for single-cell tumorsphere assays and an adherent environment for co-culturing stromal cells in close proximity by selectively patterning polyHEMA in indented microwells. By minimizing dead volume and improving cell capture efficiency, the presented platform allows for the use of small numbers of cells (<100 cells). As a proof of concept, we co-cultured single T47D (breast cancer) cells and primary cancer associated fibroblasts (CAF) on-chip for 14 days to monitor sphere formation and growth. Compared to mono-culture, co-cultured T47D have higher tumorigenic potential (sphere formation rate) and proliferation rates (larger sphere size). Furthermore, 96-multiplexed single-cell transcriptome analyses were performed to compare the gene expression of co-cultured and mono-cultured T47D cells. Phenotypic changes observed in co-culture correlated with expression changes in genes associated with proliferation, apoptotic suppression, tumorigenicity and even epithelial-to-mesechymal transition. Combining the presented platform with single cell transcriptome analysis, we successfully identified functional CSCs and investigated the phenotypic and transcriptome effects induced by tumor-stromal interactions.

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

PubMed

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

2016-08-01

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

Single-cell transcriptional analysis of normal, aberrant, and malignant hematopoiesis in zebrafish.

PubMed

Moore, Finola E; Garcia, Elaine G; Lobbardi, Riadh; Jain, Esha; Tang, Qin; Moore, John C; Cortes, Mauricio; Molodtsov, Aleksey; Kasheta, Melissa; Luo, Christina C; Garcia, Amaris J; Mylvaganam, Ravi; Yoder, Jeffrey A; Blackburn, Jessica S; Sadreyev, Ruslan I; Ceol, Craig J; North, Trista E; Langenau, David M

2016-05-30

Hematopoiesis culminates in the production of functionally heterogeneous blood cell types. In zebrafish, the lack of cell surface antibodies has compelled researchers to use fluorescent transgenic reporter lines to label specific blood cell fractions. However, these approaches are limited by the availability of transgenic lines and fluorescent protein combinations that can be distinguished. Here, we have transcriptionally profiled single hematopoietic cells from zebrafish to define erythroid, myeloid, B, and T cell lineages. We also used our approach to identify hematopoietic stem and progenitor cells and a novel NK-lysin 4(+) cell type, representing a putative cytotoxic T/NK cell. Our platform also quantified hematopoietic defects in rag2(E450fs) mutant fish and showed that these fish have reduced T cells with a subsequent expansion of NK-lysin 4(+) cells and myeloid cells. These data suggest compensatory regulation of the innate immune system in rag2(E450fs) mutant zebrafish. Finally, analysis of Myc-induced T cell acute lymphoblastic leukemia showed that cells are arrested at the CD4(+)/CD8(+) cortical thymocyte stage and that a subset of leukemia cells inappropriately reexpress stem cell genes, including bmi1 and cmyb In total, our experiments provide new tools and biological insights into single-cell heterogeneity found in zebrafish blood and leukemia. © 2016 Moore et al.

Single-cell transcriptional analysis of normal, aberrant, and malignant hematopoiesis in zebrafish

PubMed Central

Garcia, Elaine G.; Lobbardi, Riadh; Jain, Esha; Tang, Qin; Moore, John C.; Cortes, Mauricio; Molodtsov, Aleksey; Kasheta, Melissa; Luo, Christina C.; Garcia, Amaris J.; Mylvaganam, Ravi; Yoder, Jeffrey A.; Blackburn, Jessica S.; Sadreyev, Ruslan I.; Ceol, Craig J.; North, Trista E.

2016-01-01

Hematopoiesis culminates in the production of functionally heterogeneous blood cell types. In zebrafish, the lack of cell surface antibodies has compelled researchers to use fluorescent transgenic reporter lines to label specific blood cell fractions. However, these approaches are limited by the availability of transgenic lines and fluorescent protein combinations that can be distinguished. Here, we have transcriptionally profiled single hematopoietic cells from zebrafish to define erythroid, myeloid, B, and T cell lineages. We also used our approach to identify hematopoietic stem and progenitor cells and a novel NK-lysin 4+ cell type, representing a putative cytotoxic T/NK cell. Our platform also quantified hematopoietic defects in rag2E450fs mutant fish and showed that these fish have reduced T cells with a subsequent expansion of NK-lysin 4+ cells and myeloid cells. These data suggest compensatory regulation of the innate immune system in rag2E450fs mutant zebrafish. Finally, analysis of Myc-induced T cell acute lymphoblastic leukemia showed that cells are arrested at the CD4+/CD8+ cortical thymocyte stage and that a subset of leukemia cells inappropriately reexpress stem cell genes, including bmi1 and cmyb. In total, our experiments provide new tools and biological insights into single-cell heterogeneity found in zebrafish blood and leukemia. PMID:27139488

Analysis of Thermal Losses for a Variety of Single-Junction Photovoltaic Cells: An Interesting Means of Thermoelectric Heat Recovery

NASA Astrophysics Data System (ADS)

Lorenzi, Bruno; Acciarri, Maurizio; Narducci, Dario

2015-06-01

Exploitation of solar energy conversion has become a fundamental aspect of satisfying a growing demand for energy. Thus, improvement of the efficiency of conversion in photovoltaic (PV) devices is highly desirable to further promote this source. Because it is well known that the most relevant efficiency constraint, especially for single-junction solar cells, is unused heat within the device, hybrid thermo-photovoltaic systems seem promising . Among several hybrid solutions proposed in the literature, coupling of thermoelectric and PV devices seems one of the most interesting. Taking full advantage of this technology requires proper definition and analysis of the thermal losses occurring in PV cells. In this communication we propose a novel analysis of such losses, decoupling source-dependent and absorber-dependent losses. This analysis enables an evaluation of the actual recoverable amount of energy, depending on the absorber used in the PV cell. It shows that for incoming solar irradiation of , and depending on the choice of material, the maximum available thermal power ranges from (for single-crystal silicon) to (for amorphous silicon).

Volumetric Stress-Strain Analysis of Optohydrodynamically Suspended Biological Cells

PubMed Central

Liang, Yu; Saha, Asit K.

2011-01-01

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

Single-cell multimodal profiling reveals cellular epigenetic heterogeneity.

PubMed

Cheow, Lih Feng; Courtois, Elise T; Tan, Yuliana; Viswanathan, Ramya; Xing, Qiaorui; Tan, Rui Zhen; Tan, Daniel S W; Robson, Paul; Loh, Yuin-Han; Quake, Stephen R; Burkholder, William F

2016-10-01

Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present a method to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. We used this targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, to assess primary lung adenocarcinomas and human fibroblasts undergoing reprogramming by profiling epigenetic variation among cell types identified through genotyping and transcriptional analysis.

ACVP-05: Virus Genetic Analysis from Cell-Free Plasma, Virally Infected Cells or Tissues and Cultured Supernatant Via Single Genome Amplification and Direct Sequencing | Frederick National Laboratory for Cancer Research

Cancer.gov

The Viral Evolution Core within the AIDS and Cancer Virus Program will extract viral RNA/DNA from cell-free or cell-associated samples. Complementary (cDNA) will be generated as needed, and cDNA or DNA will be diluted to a single copy prior to nested

Stationary nanoliter droplet array with a substrate of choice for single adherent/nonadherent cell incubation and analysis.

PubMed

Shemesh, Jonathan; Ben Arye, Tom; Avesar, Jonathan; Kang, Joo H; Fine, Amir; Super, Michael; Meller, Amit; Ingber, Donald E; Levenberg, Shulamit

2014-08-05

Microfluidic water-in-oil droplets that serve as separate, chemically isolated compartments can be applied for single-cell analysis; however, to investigate encapsulated cells effectively over prolonged time periods, an array of droplets must remain stationary on a versatile substrate for optimal cell compatibility. We present here a platform of unique geometry and substrate versatility that generates a stationary nanodroplet array by using wells branching off a main microfluidic channel. These droplets are confined by multiple sides of a nanowell and are in direct contact with a biocompatible substrate of choice. The device is operated by a unique and reversed loading procedure that eliminates the need for fine pressure control or external tubing. Fluorocarbon oil isolates the droplets and provides soluble oxygen for the cells. By using this approach, the metabolic activity of single adherent cells was monitored continuously over time, and the concentration of viable pathogens in blood-derived samples was determined directly by measuring the number of colony-formed droplets. The method is simple to operate, requires a few microliters of reagent volume, is portable, is reusable, and allows for cell retrieval. This technology may be particularly useful for multiplexed assays for which prolonged and simultaneous visual inspection of many isolated single adherent or nonadherent cells is required.

Stationary nanoliter droplet array with a substrate of choice for single adherent/nonadherent cell incubation and analysis

PubMed Central

Shemesh, Jonathan; Ben Arye, Tom; Avesar, Jonathan; Kang, Joo H.; Fine, Amir; Super, Michael; Meller, Amit; Ingber, Donald E.; Levenberg, Shulamit

2014-01-01

Microfluidic water-in-oil droplets that serve as separate, chemically isolated compartments can be applied for single-cell analysis; however, to investigate encapsulated cells effectively over prolonged time periods, an array of droplets must remain stationary on a versatile substrate for optimal cell compatibility. We present here a platform of unique geometry and substrate versatility that generates a stationary nanodroplet array by using wells branching off a main microfluidic channel. These droplets are confined by multiple sides of a nanowell and are in direct contact with a biocompatible substrate of choice. The device is operated by a unique and reversed loading procedure that eliminates the need for fine pressure control or external tubing. Fluorocarbon oil isolates the droplets and provides soluble oxygen for the cells. By using this approach, the metabolic activity of single adherent cells was monitored continuously over time, and the concentration of viable pathogens in blood-derived samples was determined directly by measuring the number of colony-formed droplets. The method is simple to operate, requires a few microliters of reagent volume, is portable, is reusable, and allows for cell retrieval. This technology may be particularly useful for multiplexed assays for which prolonged and simultaneous visual inspection of many isolated single adherent or nonadherent cells is required. PMID:25053808

Visible micro-Raman spectroscopy of single human mammary epithelial cells exposed to x-ray radiation.

PubMed

Delfino, Ines; Perna, Giuseppe; Lasalvia, Maria; Capozzi, Vito; Manti, Lorenzo; Camerlingo, Carlo; Lepore, Maria

2015-03-01

A micro-Raman spectroscopy investigation has been performed in vitro on single human mammary epithelial cells after irradiation by graded x-ray doses. The analysis by principal component analysis (PCA) and interval-PCA (i-PCA) methods has allowed us to point out the small differences in the Raman spectra induced by irradiation. This experimental approach has enabled us to delineate radiation-induced changes in protein, nucleic acid, lipid, and carbohydrate content. In particular, the dose dependence of PCA and i-PCA components has been analyzed. Our results have confirmed that micro-Raman spectroscopy coupled to properly chosen data analysis methods is a very sensitive technique to detect early molecular changes at the single-cell level following exposure to ionizing radiation. This would help in developing innovative approaches to monitor radiation cancer radiotherapy outcome so as to reduce the overall radiation dose and minimize damage to the surrounding healthy cells, both aspects being of great importance in the field of radiation therapy.

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

Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types.

PubMed

van Unen, Vincent; Höllt, Thomas; Pezzotti, Nicola; Li, Na; Reinders, Marcel J T; Eisemann, Elmar; Koning, Frits; Vilanova, Anna; Lelieveldt, Boudewijn P F

2017-11-23

Mass cytometry allows high-resolution dissection of the cellular composition of the immune system. However, the high-dimensionality, large size, and non-linear structure of the data poses considerable challenges for the data analysis. In particular, dimensionality reduction-based techniques like t-SNE offer single-cell resolution but are limited in the number of cells that can be analyzed. Here we introduce Hierarchical Stochastic Neighbor Embedding (HSNE) for the analysis of mass cytometry data sets. HSNE constructs a hierarchy of non-linear similarities that can be interactively explored with a stepwise increase in detail up to the single-cell level. We apply HSNE to a study on gastrointestinal disorders and three other available mass cytometry data sets. We find that HSNE efficiently replicates previous observations and identifies rare cell populations that were previously missed due to downsampling. Thus, HSNE removes the scalability limit of conventional t-SNE analysis, a feature that makes it highly suitable for the analysis of massive high-dimensional data sets.

TESTING AND PERFORMANCE ANALYSIS OF NASA 5 CM BY 5 CM BI-SUPPORTED SOLID OXIDE ELECTROLYSIS CELLS OPERATED IN BOTH FUEL CELL AND STEAM ELECTROLYSIS MODES

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

R. C. O'Brien; J. E. O'Brien; C. M. Stoots

A series of 5 cm by 5 cm bi-supported Solid Oxide Electrolysis Cells (SOEC) were produced by NASA for the Idaho National Laboratory (INL) and tested under the INL High Temperature Steam Electrolysis program. The results from the experimental demonstration of cell operation for both hydrogen production and operation as fuel cells is presented. An overview of the cell technology, test apparatus and performance analysis is also provided. The INL High Temperature Steam Electrolysis laboratory has developed significant test infrastructure in support of single cell and stack performance analyses. An overview of the single cell test apparatus is presented. Themore » test data presented in this paper is representative of a first batch of NASA's prototypic 5 cm by 5 cm SOEC single cells. Clearly a significant relationship between the operational current density and cell degradation rate is evident. While the performance of these cells was lower than anticipated, in-house testing at NASA Glenn has yielded significantly higher performance and lower degradation rates with subsequent production batches of cells. Current post-test microstructure analyses of the cells tested at INL will be published in a future paper. Modification to cell compositions and cell reduction techniques will be altered in the next series of cells to be delivered to INL with the aim to decrease the cell degradation rate while allowing for higher operational current densities to be sustained. Results from the testing of new batches of single cells will be presented in a future paper.« less

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.

Quantitative Cell Cycle Analysis Based on an Endogenous All-in-One Reporter for Cell Tracking and Classification.

PubMed

Zerjatke, Thomas; Gak, Igor A; Kirova, Dilyana; Fuhrmann, Markus; Daniel, Katrin; Gonciarz, Magdalena; Müller, Doris; Glauche, Ingmar; Mansfeld, Jörg

2017-05-30

Cell cycle kinetics are crucial to cell fate decisions. Although live imaging has provided extensive insights into this relationship at the single-cell level, the limited number of fluorescent markers that can be used in a single experiment has hindered efforts to link the dynamics of individual proteins responsible for decision making directly to cell cycle progression. Here, we present fluorescently tagged endogenous proliferating cell nuclear antigen (PCNA) as an all-in-one cell cycle reporter that allows simultaneous analysis of cell cycle progression, including the transition into quiescence, and the dynamics of individual fate determinants. We also provide an image analysis pipeline for automated segmentation, tracking, and classification of all cell cycle phases. Combining the all-in-one reporter with labeled endogenous cyclin D1 and p21 as prime examples of cell-cycle-regulated fate determinants, we show how cell cycle and quantitative protein dynamics can be simultaneously extracted to gain insights into G1 phase regulation and responses to perturbations. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Single cell-based analysis of torenia petal pigments by a combination of ArF excimer laser micro sampling and nano-high performance liquid chromatography (HPLC)-mass spectrometry.

PubMed

Kajiyama, Shin'ichiro; Harada, Kazuo; Fukusaki, Eiichiro; Kobayashi, Akio

2006-12-01

The molecular constituents of the petal pigments of the Torenia plant (Torenia hybrida) were analyzed on a single-cell basis by a combination of newly developed laser-microsampling and nano-flow liquid chromatography-electro spray ionization mass spectrometry (LC-ESIMS) techniques. Our method should provide a facile method for obtaining precise metabolic profiles of each cell in a single plant tissue.

Single molecule analysis of B cell receptor motion during signaling activation

NASA Astrophysics Data System (ADS)

Rey Suarez, Ivan; Koo, Peter; Zhou, Shu; Wheatley, Brittany; Song, Wenxia; Mochrie, Simon; Upadhyaya, Arpita

B cells are an essential part of the adaptive immune system. They patrol the body for signs of infection in the form of antigen on the surface of antigen presenting cells. B cell receptor (BCR) binding to antigen induces a signaling cascade that leads to B cell activation and spreading. During activation, BCR form signaling microclusters that later coalesce as the cell contracts. We have studied the dynamics of BCRs on activated murine primary B cells using single particle tracking. The tracks are analyzed using perturbation expectation-maximization (pEM), a systems-level analysis, which allows identification of different short-time diffusive states from single molecule tracks. We identified four dominant diffusive states, two of which correspond to BCRs interacting with signaling molecules. For wild-type cells, the number of BCR in signaling states increases as the cell spreads and then decreases during cell contraction. In contrast, cells lacking the actin regulatory protein, N-WASP, are unable to contract and BCRs remain in the signaling states for longer times. These observations indicate that actin cytoskeleton dynamics modulate BCR diffusion and clustering. Our results provide novel information regarding the timescale of interaction between BCR and signaling molecules.

Selective digestion of Ba2+/Ca2+ alginate gel microdroplets for single-cell handling

NASA Astrophysics Data System (ADS)

Odaka, Masao; Hattori, Akihiro; Matsuura, Kenji; Yasuda, Kenji

2018-06-01

Cells encapsuled by polymer microdroplets are an effective platform for the identification and separation of individual cells for single-cell-based analysis. However, a key challenge is to maintain and release the captured cells in the microdroplets selectively, nondestructively, and noninvasively. We developed a simple method of encapsulating cells in alginate microdroplets having different digestion characteristics. Cells were diluted with an alginate polymer of sol state and encapsulated into microdroplets with Ba2+ and Ca2+ by a spray method. When a chelating buffer was applied, alginate gel microdroplets were digested according to the difference in chelating efficiency of linkage-divalent cations; hence, two types of alginate microdroplets were formed. Moreover, we examined the capability of the alginate gel to exchange linkage-divalent cations and found that both Ca2+ exchange in Ba-alginate microdroplets and Ba2+ exchange in Ca-alginate microdroplets occurred. These results indicate that the potential applications of a mixture of alginate microdroplets with different divalent cations control the selective digestion of microdroplets to improve the high-throughput, high-content microdroplet-based separation, analysis, or storage of single cells.

RNA-Seq analysis to capture the transcriptome landscape of a single cell

PubMed Central

Tang, Fuchou; Barbacioru, Catalin; Nordman, Ellen; Xu, Nanlan; Bashkirov, Vladimir I; Lao, Kaiqin; Surani, M. Azim

2013-01-01

We describe here a protocol for digital transcriptome analysis in a single mouse blastomere using a deep sequencing approach. An individual blastomere was first isolated and put into lysate buffer by mouth pipette. Reverse transcription was then performed directly on the whole cell lysate. After this, the free primers were removed by Exonuclease I and a poly(A) tail was added to the 3′ end of the first-strand cDNA by Terminal Deoxynucleotidyl Transferase. Then the single cell cDNAs were amplified by 20 plus 9 cycles of PCR. Then 100-200 ng of these amplified cDNAs were used to construct a sequencing library. The sequencing library can be used for deep sequencing using the SOLiD system. Compared with the cDNA microarray technique, our assay can capture up to 75% more genes expressed in early embryos. The protocol can generate deep sequencing libraries within 6 days for 16 single cell samples. PMID:20203668

Linnorm: improved statistical analysis for single cell RNA-seq expression data.

PubMed

Yip, Shun H; Wang, Panwen; Kocher, Jean-Pierre A; Sham, Pak Chung; Wang, Junwen

2017-12-15

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

Oligonucleotide arrays vs. metaphase-comparative genomic hybridisation and BAC arrays for single-cell analysis: first applications to preimplantation genetic diagnosis for Robertsonian translocation carriers.

PubMed

Ramos, Laia; del Rey, Javier; Daina, Gemma; García-Aragonés, Manel; Armengol, Lluís; Fernandez-Encinas, Alba; Parriego, Mònica; Boada, Montserrat; Martinez-Passarell, Olga; Martorell, Maria Rosa; Casagran, Oriol; Benet, Jordi; Navarro, Joaquima

2014-01-01

Comprehensive chromosome analysis techniques such as metaphase-Comparative Genomic Hybridisation (CGH) and array-CGH are available for single-cell analysis. However, while metaphase-CGH and BAC array-CGH have been widely used for Preimplantation Genetic Diagnosis, oligonucleotide array-CGH has not been used in an extensive way. A comparison between oligonucleotide array-CGH and metaphase-CGH has been performed analysing 15 single fibroblasts from aneuploid cell-lines and 18 single blastomeres from human cleavage-stage embryos. Afterwards, oligonucleotide array-CGH and BAC array-CGH were also compared analysing 16 single blastomeres from human cleavage-stage embryos. All three comprehensive analysis techniques provided broadly similar cytogenetic profiles; however, non-identical profiles appeared when extensive aneuploidies were present in a cell. Both array techniques provided an optimised analysis procedure and a higher resolution than metaphase-CGH. Moreover, oligonucleotide array-CGH was able to define extra segmental imbalances in 14.7% of the blastomeres and it better determined the specific unbalanced chromosome regions due to a higher resolution of the technique (≈ 20 kb). Applicability of oligonucleotide array-CGH for Preimplantation Genetic Diagnosis has been demonstrated in two cases of Robertsonian translocation carriers 45,XY,der(13;14)(q10;q10). Transfer of euploid embryos was performed in both cases and pregnancy was achieved by one of the couples. This is the first time that an oligonucleotide array-CGH approach has been successfully applied to Preimplantation Genetic Diagnosis for balanced chromosome rearrangement carriers.

Oligonucleotide Arrays vs. Metaphase-Comparative Genomic Hybridisation and BAC Arrays for Single-Cell Analysis: First Applications to Preimplantation Genetic Diagnosis for Robertsonian Translocation Carriers

PubMed Central

Ramos, Laia; del Rey, Javier; Daina, Gemma; García-Aragonés, Manel; Armengol, Lluís; Fernandez-Encinas, Alba; Parriego, Mònica; Boada, Montserrat; Martinez-Passarell, Olga; Martorell, Maria Rosa; Casagran, Oriol; Benet, Jordi; Navarro, Joaquima

2014-01-01

Comprehensive chromosome analysis techniques such as metaphase-Comparative Genomic Hybridisation (CGH) and array-CGH are available for single-cell analysis. However, while metaphase-CGH and BAC array-CGH have been widely used for Preimplantation Genetic Diagnosis, oligonucleotide array-CGH has not been used in an extensive way. A comparison between oligonucleotide array-CGH and metaphase-CGH has been performed analysing 15 single fibroblasts from aneuploid cell-lines and 18 single blastomeres from human cleavage-stage embryos. Afterwards, oligonucleotide array-CGH and BAC array-CGH were also compared analysing 16 single blastomeres from human cleavage-stage embryos. All three comprehensive analysis techniques provided broadly similar cytogenetic profiles; however, non-identical profiles appeared when extensive aneuploidies were present in a cell. Both array techniques provided an optimised analysis procedure and a higher resolution than metaphase-CGH. Moreover, oligonucleotide array-CGH was able to define extra segmental imbalances in 14.7% of the blastomeres and it better determined the specific unbalanced chromosome regions due to a higher resolution of the technique (≈20 kb). Applicability of oligonucleotide array-CGH for Preimplantation Genetic Diagnosis has been demonstrated in two cases of Robertsonian translocation carriers 45,XY,der(13;14)(q10;q10). Transfer of euploid embryos was performed in both cases and pregnancy was achieved by one of the couples. This is the first time that an oligonucleotide array-CGH approach has been successfully applied to Preimplantation Genetic Diagnosis for balanced chromosome rearrangement carriers. PMID:25415307

Nanosecond fluorescence microscopy. Emission kinetics of fura-2 in single cells.

PubMed Central

Keating, S M; Wensel, T G

1991-01-01

A microscope based time-correlated single photon counting instrument has been constructed to measure fluorescence intensity and emission anisotropy decays from fluorophores in single cells on a nanosecond time scale. The sample is excited and the emission collected using epi-illumination optics with frequency-doubled pulses from the cavity-dumped output of a synchronously pumped dye laser serving as an excitation source. Collection of decays from a single cell is possible due to the presence of an iris in the emission path that can be reduced to less than the diameter of a single cell. Using the instrument the decay of 60 nM 1,6-diphenyl-1,3,5-hexatriene was measured, demonstrating that adequate data for lifetime analysis can be recorded from fewer 10(3) molecules of the fluorophore in an illuminated volume of 23 fl. In addition, the intensity and anisotropy decays of fura-2 in single adherent cells and in suspensions of fura-2 loaded cells in suspension, although the relative amplitudes and decay constants vary somewhat from cell to cell. The results indicate that a significant but variable fraction of fura-2 is bound to relatively immobile macromolecular components in these cells. PMID:2015383

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.

Droplet electric separator microfluidic device for cell sorting

NASA Astrophysics Data System (ADS)

Guo, Feng; Ji, Xing-Hu; Liu, Kan; He, Rong-Xiang; Zhao, Li-Bo; Guo, Zhi-Xiao; Liu, Wei; Guo, Shi-Shang; Zhao, Xing-Zhong

2010-05-01

A simple and effective droplet electric separator microfluidic device was developed for cell sorting. The aqueous droplet without precharging operation was influenced to move a distance in the channel along the electric field direction by applying dc voltage on the electrodes beside the channel, which made the target droplet flowing to the collector. Single droplet can be isolated in a sorting rate of ˜100 Hz with microelectrodes under a required pulse. Single or multiple mammalian cell (HePG2) encapsulated in the surfactant free alginate droplet could be sorted out respectively. This method may be used for single cell operation or analysis.

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

PubMed Central

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

2013-01-01

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

Analyzing cell fate control by cytokines through continuous single cell biochemistry.

PubMed

Rieger, Michael A; Schroeder, Timm

2009-10-01

Cytokines are important regulators of cell fates with high clinical and commercial relevance. However, despite decades of intense academic and industrial research, it proved surprisingly difficult to describe the biological functions of cytokines in a precise and comprehensive manner. The exact analysis of cytokine biology is complicated by the fact that individual cytokines control many different cell fates and activate a multitude of intracellular signaling pathways. Moreover, although activating different molecular programs, different cytokines can be redundant in their biological effects. In addition, cytokines with different biological effects can activate overlapping signaling pathways. This prospect article will outline the necessity of continuous single cell biochemistry to unravel the biological functions of molecular cytokine signaling. It focuses on potentials and limitations of recent technical developments in fluorescent time-lapse imaging and single cell tracking allowing constant long-term observation of molecules and behavior of single cells. (c) 2009 Wiley-Liss, Inc.

Whole-genome multiple displacement amplification from single cells.

PubMed

Spits, Claudia; Le Caignec, Cédric; De Rycke, Martine; Van Haute, Lindsey; Van Steirteghem, André; Liebaers, Inge; Sermon, Karen

2006-01-01

Multiple displacement amplification (MDA) is a recently described method of whole-genome amplification (WGA) that has proven efficient in the amplification of small amounts of DNA, including DNA from single cells. Compared with PCR-based WGA methods, MDA generates DNA with a higher molecular weight and shows better genome coverage. This protocol was developed for preimplantation genetic diagnosis, and details a method for performing single-cell MDA using the phi29 DNA polymerase. It can also be useful for the amplification of other minute quantities of DNA, such as from forensic material or microdissected tissue. The protocol includes the collection and lysis of single cells, and all materials and steps involved in the MDA reaction. The whole procedure takes 3 h and generates 1-2 microg of DNA from a single cell, which is suitable for multiple downstream applications, such as sequencing, short tandem repeat analysis or array comparative genomic hybridization.

Single Cell Proteomics in Biomedicine: High-dimensional Data Acquisition, Visualization and Analysis

PubMed Central

Su, Yapeng; Shi, Qihui; Wei, Wei

2017-01-01

New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions. PMID:28128880

Mutation dynamics and fitness effects followed in single cells.

PubMed

Robert, Lydia; Ollion, Jean; Robert, Jerome; Song, Xiaohu; Matic, Ivan; Elez, Marina

2018-03-16

Mutations have been investigated for more than a century but remain difficult to observe directly in single cells, which limits the characterization of their dynamics and fitness effects. By combining microfluidics, time-lapse imaging, and a fluorescent tag of the mismatch repair system in Escherichia coli , we visualized the emergence of mutations in single cells, revealing Poissonian dynamics. Concomitantly, we tracked the growth and life span of single cells, accumulating ~20,000 mutations genome-wide over hundreds of generations. This analysis revealed that 1% of mutations were lethal; nonlethal mutations displayed a heavy-tailed distribution of fitness effects and were dominated by quasi-neutral mutations with an average cost of 0.3%. Our approach has enabled the investigation of single-cell individuality in mutation rate, mutation fitness costs, and mutation interactions. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

PubMed Central

Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.

2017-01-01

Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800

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

PubMed

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

2018-04-24

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

Real-time detection and monitoring of the drug resistance of single myeloid leukemia cells by diffused total internal reflection.

PubMed

Liang, L; Jin, Y X; Zhu, X Q; Zhou, F L; Yang, Y

2018-05-15

Real-time detection and monitoring of the drug resistance of single cells have important significance in clinical diagnosis and therapy. Traditional methods operate a number of times for each individual concentration, and innovation is required for the design of more simple and efficient manipulation platforms with necessary higher sensitivity. Here, we have developed a novel diffused total internal reflection (TIR) method to perform drug metabolism and cytotoxicity analysis of trapped myeloid leukemia cells. Molm-13 cells, a type of acute myeloid leukemia cell, were chosen and injected into the device and fittingly captured by cell traps. Differing from previous studies, a series of different concentrations of azelaic acid (AZA) drug could be used from 0 mM to 50 mM through convection and diffusion processes in a single chip, with each concentration region featuring 50 cells, with a total of 549 cell trapping units. Thanks to the high sensitivity of the TIR method, only cells with the same drug concentration could be illuminated in the detection process. By adjusting the incident angle, we could exactly detect and monitor the drug resistance of the cells using different drug concentrations and the experimental resolution of the drug concentration was as small as 5 mM. Images of the membrane integrity and morphology of the cells in the bright field were measured and we also monitored the cell viabilities in the dark field over 2 hours. The effects of AZA on the Molm-13 cells were explored in different concentrations at the single cell level. Compared with the results of the traditional MTT assay method, the experimental results are more simple and accurate. A cell death of 5% at an AZA concentration of 5 mM was observed after 30 minutes, while a concentration of 40 mM corresponded to a 98% cell death. The designed method in this study provides a novel toolkit to control and monitor drug resistance at the single cell level more easily with higher sensitivity and we believe it has significant potential application in single cell quality assessment and medicine analysis in clinical practice.

Developmental switching in Physarum polycephalum: Petri net analysis of single cell trajectories of gene expression indicates responsiveness and genetic plasticity of the Waddington quasipotential landscape

NASA Astrophysics Data System (ADS)

Werthmann, Britta; Marwan, Wolfgang

2017-11-01

The developmental switch to sporulation in Physarum polycephalum is a phytochrome-mediated far-red light-induced cell fate decision that synchronously encompasses the entire multinucleate plasmodial cell and is associated with extensive reprogramming of the transcriptome. By repeatedly taking samples of single cells after delivery of a light stimulus pulse, we analysed differential gene expression in two mutant strains and in a heterokaryon of the two strains all of which display a different propensity for making the cell fate decision. Multidimensional scaling of the gene expression data revealed individually different single cell trajectories eventually leading to sporulation. Characterization of the trajectories as walks through states of gene expression discretized by hierarchical clustering allowed the reconstruction of Petri nets that model and predict the observed behavior. Structural analyses of the Petri nets indicated stimulus- and genotype-dependence of both, single cell trajectories and of the quasipotential landscape through which these trajectories are taken. The Petri net-based approach to the analysis and decomposition of complex cellular responses and of complex mutant phenotypes may provide a scaffold for the data-driven reconstruction of causal molecular mechanisms that shape the topology of the quasipotential landscape.

Non-invasive optoacoustic probing of the density and stiffness of single biological cells

NASA Astrophysics Data System (ADS)

Dehoux, T.; Audoin, B.

2012-12-01

Recently, the coherent generation of GHz acoustic waves using ultrashort laser pulses has demonstrated the ability to probe the sound velocity in vegetal cells and in cell-mimicking soft micro-objects with micrometer resolution, opening tremendous potentialities for single-cell biology. However, manipulating biological media in physiological conditions is often a technical challenge when using a laser-based setup. In this article, we present a new opto-acoustic bio-transducer composed of a thin metal film sputtered on a transparent heat sink that allows reducing importantly the laser-induced cellular stresses, and offers a wide variety of optical configurations. In particular, by exploiting the acoustic reflection coefficient at the sample-transducer interface and the photoacoustic interaction inside the transparent sample, the density and compressibility of the sample can be probed simultaneously. Using an ad hoc signal analysis based on Hilbert and wavelet transforms, these quantities are measured accurately for a reference fluid. Similar analysis performed in a single vegetal cell also suggests high sensitivity to the state of the transducer-cell interface, and notably to the presence of the plasma membrane that encloses the cell vacuole.

An open-pattern droplet-in-oil planar array for single cell analysis based on sequential inkjet printing technology.

PubMed

Wang, Chenyu; Liu, Wenwen; Tan, Manqing; Sun, Hongbo; Yu, Yude

2017-07-01

Cellular heterogeneity represents a fundamental principle of cell biology for which a readily available single-cell research tool is urgently required. Here, we present a novel method combining cell-sized well arrays with sequential inkjet printing. Briefly, K562 cells with phosphate buffer saline buffer were captured at high efficiency (74.5%) in a cell-sized well as a "primary droplet" and sealed using fluorinated oil. Then, piezoelectric inkjet printing technology was adapted to precisely inject the cell lysis buffer and the fluorogenic substrate, fluorescein-di-β-D-galactopyranoside, as a "secondary droplet" to penetrate the sealing oil and fuse with the "primary droplet." We thereby successfully measured the intracellular β-galactosidase activity of K562 cells at the single-cell level. Our method allows, for the first time, the ability to simultaneously accommodate the high occupancy rate of single cells and sequential addition of reagents while retaining an open structure. We believe that the feasibility and flexibility of our method will enhance its use as a universal single-cell research tool as well as accelerate the adoption of inkjet printing in the study of cellular heterogeneity.

Magnetomicrofluidics Circuits for Organizing Bioparticle Arrays

NASA Astrophysics Data System (ADS)

Abedini-Nassab, Roozbeh

Single-cell analysis (SCA) tools have important applications in the analysis of phenotypic heterogeneity, which is difficult or impossible to analyze in bulk cell culture or patient samples. SCA tools thus have a myriad of applications ranging from better credentialing of drug therapies to the analysis of rare latent cells harboring HIV infection or in Cancer. However, existing SCA systems usually lack the required combination of programmability, flexibility, and scalability necessary to enable the study of cell behaviors and cell-cell interactions at the scales sufficient to analyze extremely rare events. To advance the field, I have developed a novel, programmable, and massively-parallel SCA tool which is based on the principles of computer circuits. By integrating these magnetic circuits with microfluidics channels, I developed a platform that can organize a large number of single particles into an array in a controlled manner. My magnetophoretic circuits use passive elements constructed in patterned magnetic thin films to move cells along programmed tracks with an external rotating magnetic field. Cell motion along these tracks is analogous to the motion of charges in an electrical conductor, following a rule similar to Ohm's law. I have also developed asymmetric conductors, similar to electrical diodes, and storage sites for cells that behave similarly to electrical capacitors. I have also developed magnetophoretic circuits which use an overlaid pattern of microwires to switch single cells between different tracks. This switching mechanism, analogous to the operation of electronic transistors, is achieved by establishing a semiconducting gap in the magnetic pattern which can be changed from an insulating state to a conducting state by application of electrical current to an overlaid electrode. I performed an extensive study on the operation of transistors to optimize their geometry and minimize the required gate currents. By combining these elements into integrated circuits, I have built devices which are capable of organizing a precise number of cells into individually addressable array sites, similar to how a random access memory (RAM) stores electronic data. My programmable magnetic circuits allow for the organization of both cells and single-cell pairs into large arrays. Single cells can also potentially be retrieved for downstream high-throughput genomic analysis. In order to enhance the efficiency of the tool and to increase the delivery speed of the particles, I have also developed microfluidics systems that are combined with the magnetophoretic circuits. This hybrid system, called magnetomicrofluidics, is capable of rapidly organizing an array of particles and cells with the high precision and control. I have also shown that cells can be grown inside these chips for multiple days, enabling the long-term phenotypic analysis of rare cellular events. These types of studies can reveal important insights about the intercellular signaling networks and answer crucial questions in biology and immunology.

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.

Live single cell functional phenotyping in droplet nano-liter reactors.

PubMed

Konry, Tania; Golberg, Alexander; Yarmush, Martin

2013-11-11

While single cell heterogeneity is present in all biological systems, most studies cannot address it due to technical limitations. Here we describe a nano-liter droplet microfluidic-based approach for stimulation and monitoring of surface and secreted markers of live single immune dendritic cells (DCs) as well as monitoring the live T cell/DC interaction. This nano-liter in vivo simulating microenvironment allows delivering various stimuli reagents to each cell and appropriate gas exchanges which are necessary to ensure functionality and viability of encapsulated cells. Labeling bioassay and microsphere sensors were integrated into nano-liter reaction volume of the droplet to monitor live single cell surface markers and secretion analysis in the time-dependent fashion. Thus live cell stimulation, secretion and surface monitoring can be obtained simultaneously in distinct microenvironment, which previously was possible using complicated and multi-step in vitro and in vivo live-cell microscopy, together with immunological studies of the outcome secretion of cellular function.

Scanning ion conductance microscopy: a convergent high-resolution technology for multi-parametric analysis of living cardiovascular cells

PubMed Central

Miragoli, Michele; Moshkov, Alexey; Novak, Pavel; Shevchuk, Andrew; Nikolaev, Viacheslav O.; El-Hamamsy, Ismail; Potter, Claire M. F.; Wright, Peter; Kadir, S.H. Sheikh Abdul; Lyon, Alexander R.; Mitchell, Jane A.; Chester, Adrian H.; Klenerman, David; Lab, Max J.; Korchev, Yuri E.; Harding, Sian E.; Gorelik, Julia

2011-01-01

Cardiovascular diseases are complex pathologies that include alterations of various cell functions at the levels of intact tissue, single cells and subcellular signalling compartments. Conventional techniques to study these processes are extremely divergent and rely on a combination of individual methods, which usually provide spatially and temporally limited information on single parameters of interest. This review describes scanning ion conductance microscopy (SICM) as a novel versatile technique capable of simultaneously reporting various structural and functional parameters at nanometre resolution in living cardiovascular cells at the level of the whole tissue, single cells and at the subcellular level, to investigate the mechanisms of cardiovascular disease. SICM is a multimodal imaging technology that allows concurrent and dynamic analysis of membrane morphology and various functional parameters (cell volume, membrane potentials, cellular contraction, single ion-channel currents and some parameters of intracellular signalling) in intact living cardiovascular cells and tissues with nanometre resolution at different levels of organization (tissue, cellular and subcellular levels). Using this technique, we showed that at the tissue level, cell orientation in the inner and outer aortic arch distinguishes atheroprone and atheroprotected regions. At the cellular level, heart failure leads to a pronounced loss of T-tubules in cardiac myocytes accompanied by a reduction in Z-groove ratio. We also demonstrated the capability of SICM to measure the entire cell volume as an index of cellular hypertrophy. This method can be further combined with fluorescence to simultaneously measure cardiomyocyte contraction and intracellular calcium transients or to map subcellular localization of membrane receptors coupled to cyclic adenosine monophosphate production. The SICM pipette can be used for patch-clamp recordings of membrane potential and single channel currents. In conclusion, SICM provides a highly informative multimodal imaging platform for functional analysis of the mechanisms of cardiovascular diseases, which should facilitate identification of novel therapeutic strategies. PMID:21325316

Single-Cell Memory Regulates a Neural Circuit for Sensory Behavior.

PubMed

Kobayashi, Kyogo; Nakano, Shunji; Amano, Mutsuki; Tsuboi, Daisuke; Nishioka, Tomoki; Ikeda, Shingo; Yokoyama, Genta; Kaibuchi, Kozo; Mori, Ikue

2016-01-05

Unveiling the molecular and cellular mechanisms underlying memory has been a challenge for the past few decades. Although synaptic plasticity is proven to be essential for memory formation, the significance of "single-cell memory" still remains elusive. Here, we exploited a primary culture system for the analysis of C. elegans neurons and show that a single thermosensory neuron has an ability to form, retain, and reset a temperature memory. Genetic and proteomic analyses found that the expression of the single-cell memory exhibits inter-individual variability, which is controlled by the evolutionarily conserved CaMKI/IV and Raf pathway. The variable responses of a sensory neuron influenced the neural activity of downstream interneurons, suggesting that modulation of the sensory neurons ultimately determines the behavioral output in C. elegans. Our results provide proof of single-cell memory and suggest that the individual differences in neural responses at the single-cell level can confer individuality. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2015-02-01

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

In Situ Hot-Spot Assembly as a General Strategy for Probing Single Biomolecules.

PubMed

Liu, Huiqiao; Li, Qiang; Li, Mingmin; Ma, Sisi; Liu, Dingbin

2017-05-02

Single-molecule detection using surface-enhanced Raman spectroscopy (SERS) has attracted increasing attention in chemical and biomedical analysis. However, it remains a major challenge to probe single biomolecules by means of SERS hot spots owing to the small volume of hot spots and their random distribution on substrates. We here report an in situ hot-spot assembly method as a general strategy for probing single biomolecules. As a proof-of-concept, this proposed strategy was successfully used for the detection of single microRNA-21 (miRNA-21, a potential cancer biomarker) at the single-cell level, showing great capability in differentiating the expression of miRNA-21 in single cancer cells from normal cells. This approach was further extended to single-protein detection. The versatility of the strategy opens an exciting avenue for single-molecule detection of biomarkers of interest and thus holds great promise in a variety of biological and biomedical applications.

Genome-wide maps of nuclear lamina interactions in single human cells.

PubMed

Kind, Jop; Pagie, Ludo; de Vries, Sandra S; Nahidiazar, Leila; Dey, Siddharth S; Bienko, Magda; Zhan, Ye; Lajoie, Bryan; de Graaf, Carolyn A; Amendola, Mario; Fudenberg, Geoffrey; Imakaev, Maxim; Mirny, Leonid A; Jalink, Kees; Dekker, Job; van Oudenaarden, Alexander; van Steensel, Bas

2015-09-24

Mammalian interphase chromosomes interact with the nuclear lamina (NL) through hundreds of large lamina-associated domains (LADs). We report a method to map NL contacts genome-wide in single human cells. Analysis of nearly 400 maps reveals a core architecture consisting of gene-poor LADs that contact the NL with high cell-to-cell consistency, interspersed by LADs with more variable NL interactions. The variable contacts tend to be cell-type specific and are more sensitive to changes in genome ploidy than the consistent contacts. Single-cell maps indicate that NL contacts involve multivalent interactions over hundreds of kilobases. Moreover, we observe extensive intra-chromosomal coordination of NL contacts, even over tens of megabases. Such coordinated loci exhibit preferential interactions as detected by Hi-C. Finally, the consistency of NL contacts is inversely linked to gene activity in single cells and correlates positively with the heterochromatic histone modification H3K9me3. These results highlight fundamental principles of single-cell chromatin organization. VIDEO ABSTRACT. Copyright © 2015 Elsevier Inc. All rights reserved.

Self-digitization chip for single-cell genotyping of cancer-related mutations

PubMed Central

Monroe, Luke D.; Kreutz, Jason E.; Schneider, Thomas; Fujimoto, Bryant S.; Chiu, Daniel T.; Radich, Jerald P.; Paguirigan, Amy L.

2018-01-01

Cancer is a heterogeneous disease, and patient-level genetic assessments can guide therapy choice and impact prognosis. However, little is known about the impact of genetic variability within a tumor, intratumoral heterogeneity (ITH), on disease progression or outcome. Current approaches using bulk tumor specimens can suggest the presence of ITH, but only single-cell genetic methods have the resolution to describe the underlying clonal structures themselves. Current techniques tend to be labor and resource intensive and challenging to characterize with respect to sources of biological and technical variability. We have developed a platform using a microfluidic self-digitization chip to partition cells in stationary volumes for cell imaging and allele-specific PCR. Genotyping data from only confirmed single-cell volumes is obtained and subject to a variety of relevant quality control assessments such as allele dropout, false positive, and false negative rates. We demonstrate single-cell genotyping of the NPM1 type A mutation, an important prognostic indicator in acute myeloid leukemia, on single cells of the cell line OCI-AML3, describing a more complex zygosity distribution than would be predicted via bulk analysis. PMID:29718986

Self-digitization chip for single-cell genotyping of cancer-related mutations.

PubMed

Thompson, Alison M; Smith, Jordan L; Monroe, Luke D; Kreutz, Jason E; Schneider, Thomas; Fujimoto, Bryant S; Chiu, Daniel T; Radich, Jerald P; Paguirigan, Amy L

2018-01-01

Cancer is a heterogeneous disease, and patient-level genetic assessments can guide therapy choice and impact prognosis. However, little is known about the impact of genetic variability within a tumor, intratumoral heterogeneity (ITH), on disease progression or outcome. Current approaches using bulk tumor specimens can suggest the presence of ITH, but only single-cell genetic methods have the resolution to describe the underlying clonal structures themselves. Current techniques tend to be labor and resource intensive and challenging to characterize with respect to sources of biological and technical variability. We have developed a platform using a microfluidic self-digitization chip to partition cells in stationary volumes for cell imaging and allele-specific PCR. Genotyping data from only confirmed single-cell volumes is obtained and subject to a variety of relevant quality control assessments such as allele dropout, false positive, and false negative rates. We demonstrate single-cell genotyping of the NPM1 type A mutation, an important prognostic indicator in acute myeloid leukemia, on single cells of the cell line OCI-AML3, describing a more complex zygosity distribution than would be predicted via bulk analysis.

SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.

PubMed

Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin

2018-05-25

Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.

An analysis of particle track effects on solid mammalian tissues

NASA Technical Reports Server (NTRS)

Todd, P.; Clarkson, T. W. (Principal Investigator)

1992-01-01

Relative biological effectiveness (RBE) and quality factor (Q) at extreme values of linear energy transfer (LET) have been determined on the basis of experiments with single-cell systems and specific tissue responses. In typical single-cell systems, each heavy particle (Ar or Fe) passes through a single cell or no cell. In experiments on animal tissues, however, each heavy particle passes through several cells, and the LET can exceed 200 keV micrometers-1 in every cell. In most laboratory animal tissue systems, however, only a small portion of the hit cells are capable of expressing the end-point being measured, such as cell killing, mutation or carcinogenesis. The following question was therefore addressed: do RBEs and Q factors derived from single-cell experiments properly account for the damage at high LET when multiple cells are hit by HZE tracks? A review is offered in which measured radiation effects and known tissue properties are combined to estimate on the one hand, the number of cells at risk, p3n, per track, where n is the number of cells per track based on tissue and organ geometry, and p3 is the probability that a cell in the track is capable of expressing the experimental end-point. On the other hand, the tissue and single-cell responses are compared by determining the ratio RBE in tissue/RBE in corresponding single cells. Experimental data from the literature indicate that tissue RBEs at very high LET (Fe and Ar ions) are higher than corresponding single-cell RBEs, especially in tissues in which p3n is high.

Flow cytometry in the post fluorescence era.

PubMed

Nolan, Garry P

2011-12-01

While flow cytometry once enabled researchers to examine 10--15 cell surface parameters, new mass flow cytometry technology enables interrogation of up to 45 parameters on a single cell. This new technology has increased understanding of cell expression and how cells differentiate during hematopoiesis. Using this information, knowledge of leukemia cell biology has also increased. Other new technologies, such as SPADE analysis and single cell network profiling (SCNP), are enabling researchers to put different cancers into more biologically similar categories and have the potential to enable more personalized medicine. Copyright © 2011. Published by Elsevier Ltd.

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

On-chip Magnetic Separation and Cell Encapsulation in Droplets

NASA Astrophysics Data System (ADS)

Chen, A.; Byvank, T.; Bharde, A.; Miller, B. L.; Chalmers, J. J.; Sooryakumar, R.; Chang, W.-J.; Bashir, R.

2012-02-01

The demand for high-throughput single cell assays is gaining importance because of the heterogeneity of many cell suspensions, even after significant initial sorting. These suspensions may display cell-to-cell variability at the gene expression level that could impact single cell functional genomics, cancer, stem-cell research and drug screening. The on-chip monitoring of individual cells in an isolated environment could prevent cross-contamination, provide high recovery yield and ability to study biological traits at a single cell level These advantages of on-chip biological experiments contrast to conventional methods, which require bulk samples that provide only averaged information on cell metabolism. We report on a device that integrates microfluidic technology with a magnetic tweezers array to combine the functionality of separation and encapsulation of objects such as immunomagnetically labeled cells or magnetic beads into pico-liter droplets on the same chip. The ability to control the separation throughput that is independent of the hydrodynamic droplet generation rate allows the encapsulation efficiency to be optimized. The device can potentially be integrated with on-chip labeling and/or bio-detection to become a powerful single-cell analysis device.

Implementation of stimulated Raman scattering microscopy for single cell analysis

NASA Astrophysics Data System (ADS)

D'Arco, Annalisa; Ferrara, Maria Antonietta; Indolfi, Maurizio; Tufano, Vitaliano; Sirleto, Luigi

2017-05-01

In this work, we present successfully realization of a nonlinear microscope, not purchasable in commerce, based on stimulated Raman scattering. It is obtained by the integration of a femtosecond SRS spectroscopic setup with an inverted research microscope equipped with a scanning unit. Taking account of strength of vibrational contrast of SRS, it provides label-free imaging of single cell analysis. Validation tests on images of polystyrene beads are reported to demonstrate the feasibility of the approach. In order to test the microscope on biological structures, we report and discuss the label-free images of lipid droplets inside fixed adipocyte cells.

Development of an Integrated Chip for Automatic Tracking and Positioning Manipulation for Single Cell Lysis

PubMed Central

Young, Chao-Wang; Hsieh, Jia-Ling; Ay, Chyung

2012-01-01

This study adopted a microelectromechanical fabrication process to design a chip integrated with electroosmotic flow and dielectrophoresis force for single cell lysis. Human histiocytic lymphoma U937 cells were driven rapidly by electroosmotic flow and precisely moved to a specific area for cell lysis. By varying the frequency of AC power, 15 V AC at 1 MHz of frequency configuration achieved 100% cell lysing at the specific area. The integrated chip could successfully manipulate single cells to a specific position and lysis. The overall successful rate of cell tracking, positioning, and cell lysis is 80%. The average speed of cell driving was 17.74 μm/s. This technique will be developed for DNA extraction in biomolecular detection. It can simplify pre-treatment procedures for biotechnological analysis of samples. PMID:22736957

Development of an integrated chip for automatic tracking and positioning manipulation for single cell lysis.

PubMed

Young, Chao-Wang; Hsieh, Jia-Ling; Ay, Chyung

2012-01-01

This study adopted a microelectromechanical fabrication process to design a chip integrated with electroosmotic flow and dielectrophoresis force for single cell lysis. Human histiocytic lymphoma U937 cells were driven rapidly by electroosmotic flow and precisely moved to a specific area for cell lysis. By varying the frequency of AC power, 15 V AC at 1 MHz of frequency configuration achieved 100% cell lysing at the specific area. The integrated chip could successfully manipulate single cells to a specific position and lysis. The overall successful rate of cell tracking, positioning, and cell lysis is 80%. The average speed of cell driving was 17.74 μm/s. This technique will be developed for DNA extraction in biomolecular detection. It can simplify pre-treatment procedures for biotechnological analysis of samples.

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

PubMed

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

2018-04-24

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

A photoelectrochemical platform for the capture and release of rare single cells.

PubMed

Parker, Stephen G; Yang, Ying; Ciampi, Simone; Gupta, Bakul; Kimpton, Kathleen; Mansfeld, Friederike M; Kavallaris, Maria; Gaus, Katharina; Gooding, J Justin

2018-06-12

For many normal and aberrant cell behaviours, it is important to understand the origin of cellular heterogeneity. Although powerful methods for studying cell heterogeneity have emerged, they are more suitable for common rather than rare cells. Exploring the heterogeneity of rare single cells is challenging because these rare cells must be first pre-concentrated and undergo analysis prior to classification and expansion. Here, a versatile capture & release platform consisting of an antibody-modified and electrochemically cleavable semiconducting silicon surface for release of individual cells of interest is presented. The captured cells can be interrogated microscopically and tested for drug responsiveness prior to release and recovery. The capture & release strategy was applied to identify rare tumour cells from whole blood, monitor the uptake of, and response to, doxorubicin and subsequently select cells for single-cell gene expression based on their response to the doxorubicin.

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.

A Label-Free Microfluidic Biosensor for Activity Detection of Single Microalgae Cells Based on Chlorophyll Fluorescence

PubMed Central

Wang, Junsheng; Sun, Jinyang; Song, Yongxin; Xu, Yongyi; Pan, Xinxiang; Sun, Yeqing; Li, Dongqing

2013-01-01

Detection of living microalgae cells is very important for ballast water treatment and analysis. Chlorophyll fluorescence is an indicator of photosynthetic activity and hence the living status of plant cells. In this paper, we developed a novel microfluidic biosensor system that can quickly and accurately detect the viability of single microalgae cells based on chlorophyll fluorescence. The system is composed of a laser diode as an excitation light source, a photodiode detector, a signal analysis circuit, and a microfluidic chip as a microalgae cell transportation platform. To demonstrate the utility of this system, six different living and dead algae samples (Karenia mikimotoi Hansen, Chlorella vulgaris, Nitzschia closterium, Platymonas subcordiformis, Pyramidomonas delicatula and Dunaliella salina) were tested. The developed biosensor can distinguish clearly between the living microalgae cells and the dead microalgae cells. The smallest microalgae cells that can be detected by using this biosensor are 3 μm ones. Even smaller microalgae cells could be detected by increasing the excitation light power. The developed microfluidic biosensor has great potential for in situ ballast water analysis. PMID:24287532

Single-particle tracking of endocytosis and exocytosis of single-walled carbon nanotubes in NIH-3T3 cells.

PubMed

Jin, Hong; Heller, Daniel A; Strano, Michael S

2008-06-01

Over 10000 individual trajectories of nonphotobleaching single-walled carbon nanotubes (SWNT) were tracked as they are incorporated into and expelled from NIH-3T3 cells in real time on a perfusion microscope stage. An analysis of mean square displacement allows the complete construction of the mechanistic steps involved from single duration experiments. We observe the first conclusive evidence of SWNT exocytosis and show that the rate closely matches the endocytosis rate with negligible temporal offset. We identify and study the endocytosis and exocytosis pathway that leads to the previously observed aggregation and accumulation of SWNT within the cells.

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

Single cell transcriptomics of neighboring hyphae of Aspergillus niger

PubMed Central

2011-01-01

Single cell profiling was performed to assess differences in RNA accumulation in neighboring hyphae of the fungus Aspergillus niger. A protocol was developed to isolate and amplify RNA from single hyphae or parts thereof. Microarray analysis resulted in a present call for 4 to 7% of the A. niger genes, of which 12% showed heterogeneous RNA levels. These genes belonged to a wide range of gene categories. PMID:21816052

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

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

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

2013-06-03

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

Addressable droplet microarrays for single cell protein analysis.

PubMed

Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R

2014-11-07

Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.

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

Single-Cell Measurements of IgE-Mediated FcεRI Signaling Using an Integrated Microfluidic Platform

DOE PAGES

Liu, Yanli; Barua, Dipak; Liu, Peng; ...

2013-03-27

Heterogeneity in responses of cells to a stimulus, such as a pathogen or allergen, can potentially play an important role in deciding the fate of the responding cell population and the overall systemic response. Measuring heterogeneous responses requires tools capable of interrogating individual cells. Cell signaling studies commonly do not have single-cell resolution because of the limitations of techniques used such as Westerns, ELISAs, mass spectrometry, and DNA microarrays. Microfluidics devices are increasingly being used to overcome these limitations. In this paper, we report on a microfluidic platform for cell signaling analysis that combines two orthogonal single-cell measurement technologies: on-chipmore » flow cytometry and optical imaging. The device seamlessly integrates cell culture, stimulation, and preparation with downstream measurements permitting hands-free, automated analysis to minimize experimental variability. The platform was used to interrogate IgE receptor (FcεRI) signaling, which is responsible for triggering allergic reactions, in RBL-2H3 cells. Following on-chip crosslinking of IgE-FcεRI complexes by multivalent antigen, we monitored signaling events including protein phosphorylation, calcium mobilization and the release of inflammatory mediators. The results demonstrate the ability of our platform to produce quantitative measurements on a cell-by-cell basis from just a few hundred cells. Finally, model-based analysis of the Syk phosphorylation data suggests that heterogeneity in Syk phosphorylation can be attributed to protein copy number variations, with the level of Syk phosphorylation being particularly sensitive to the copy number of Lyn.« less

Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells.

PubMed

Semrau, Stefan; Goldmann, Johanna E; Soumillon, Magali; Mikkelsen, Tarjei S; Jaenisch, Rudolf; van Oudenaarden, Alexander

2017-10-23

Gene expression heterogeneity in the pluripotent state of mouse embryonic stem cells (mESCs) has been increasingly well-characterized. In contrast, exit from pluripotency and lineage commitment have not been studied systematically at the single-cell level. Here we measure the gene expression dynamics of retinoic acid driven mESC differentiation from pluripotency to lineage commitment, using an unbiased single-cell transcriptomics approach. We find that the exit from pluripotency marks the start of a lineage transition as well as a transient phase of increased susceptibility to lineage specifying signals. Our study reveals several transcriptional signatures of this phase, including a sharp increase of gene expression variability and sequential expression of two classes of transcriptional regulators. In summary, we provide a comprehensive analysis of the exit from pluripotency and lineage commitment at the single cell level, a potential stepping stone to improved lineage manipulation through timing of differentiation cues.

A programmable droplet-based microfluidic device applied to multiparameter analysis of single microbes and microbial communities

PubMed Central

Leung, Kaston; Zahn, Hans; Leaver, Timothy; Konwar, Kishori M.; Hanson, Niels W.; Pagé, Antoine P.; Lo, Chien-Chi; Chain, Patrick S.; Hallam, Steven J.; Hansen, Carl L.

2012-01-01

We present a programmable droplet-based microfluidic device that combines the reconfigurable flow-routing capabilities of integrated microvalve technology with the sample compartmentalization and dispersion-free transport that is inherent to droplets. The device allows for the execution of user-defined multistep reaction protocols in 95 individually addressable nanoliter-volume storage chambers by consecutively merging programmable sequences of picoliter-volume droplets containing reagents or cells. This functionality is enabled by “flow-controlled wetting,” a droplet docking and merging mechanism that exploits the physics of droplet flow through a channel to control the precise location of droplet wetting. The device also allows for automated cross-contamination-free recovery of reaction products from individual chambers into standard microfuge tubes for downstream analysis. The combined features of programmability, addressability, and selective recovery provide a general hardware platform that can be reprogrammed for multiple applications. We demonstrate this versatility by implementing multiple single-cell experiment types with this device: bacterial cell sorting and cultivation, taxonomic gene identification, and high-throughput single-cell whole genome amplification and sequencing using common laboratory strains. Finally, we apply the device to genome analysis of single cells and microbial consortia from diverse environmental samples including a marine enrichment culture, deep-sea sediments, and the human oral cavity. The resulting datasets capture genotypic properties of individual cells and illuminate known and potentially unique partnerships between microbial community members. PMID:22547789

Single-Molecule Localization Microscopy allows for the analysis of cancer metastasis-specific miRNA distribution on the nanoscale

PubMed Central

Tezcan, Kerem Can; Schaufler, Wladimir; Bestvater, Felix; Patil, Nitin; Birk, Udo; Hafner, Mathias; Altevogt, Peter; Cremer, Christoph; Allgayer, Heike

2015-01-01

We describe a novel approach for the detection of small non-coding RNAs in single cells by Single-Molecule Localization Microscopy (SMLM). We used a modified SMLM–setup and applied this instrument in a first proof-of-principle concept to human cancer cell lines. Our method is able to visualize single microRNA (miR)-molecules in fixed cells with a localization accuracy of 10–15 nm, and is able to quantify and analyse clustering and localization in particular subcellular sites, including exosomes. We compared the metastasis-site derived (SW620) and primary site derived (SW480) human colorectal cancer (CRC) cell lines, and (as a proof of principle) evaluated the metastasis relevant miR-31 as a first example. We observed that the subcellular distribution of miR-31 molecules in both cell lines was very heterogeneous with the largest subpopulation of optically acquired weakly metastatic cells characterized by a low number of miR-31 molecules, as opposed to a significantly higher number in the majority of the highly metastatic cells. Furthermore, the highly metastatic cells had significantly more miR-31-molecules in the extracellular space, which were visualized to co-localize with exosomes in significantly higher numbers. From this study, we conclude that miRs are not only aberrantly expressed and regulated, but also differentially compartmentalized in cells with different metastatic potential. Taken together, this novel approach, by providing single molecule images of miRNAs in cellulo can be used as a powerful supplementary tool in the analysis of miRNA function and behaviour and has far reaching potential in defining metastasis-critical subpopulations within a given heterogeneous cancer cell population. PMID:26561203

Revealing the vectors of cellular identity with single-cell genomics

PubMed Central

Wagner, Allon; Regev, Aviv; Yosef, Nir

2017-01-01

Single-cell genomics has now made it possible to create a comprehensive atlas of human cells. At the same time, it has reopened definitions of a cell’s identity and type and of the ways in which they are regulated by the cell’s molecular circuitry. Emerging computational analysis methods, especially in single-cell RNA sequencing (scRNA-seq), have already begun to reveal, in a data-driven way, the diverse simultaneous facets of a cell’s identity, from a taxonomy of discrete cell types to continuous dynamic transitions and spatial locations. These developments will eventually allow a cell to be represented as a superposition of ‘basis vectors’, each determining a different (but possibly dependent) aspect of cellular organization and function. However, computational methods must also overcome considerable challenges—from handling technical noise and data scale to forming new abstractions of biology. As the scale of single-cell experiments continues to increase, new computational approaches will be essential for constructing and characterizing a reference map of cell identities. PMID:27824854

Cnidarian Cell Type Diversity and Regulation Revealed by Whole-Organism Single-Cell RNA-Seq.

PubMed

Sebé-Pedrós, Arnau; Saudemont, Baptiste; Chomsky, Elad; Plessier, Flora; Mailhé, Marie-Pierre; Renno, Justine; Loe-Mie, Yann; Lifshitz, Aviezer; Mukamel, Zohar; Schmutz, Sandrine; Novault, Sophie; Steinmetz, Patrick R H; Spitz, François; Tanay, Amos; Marlow, Heather

2018-05-31

The emergence and diversification of cell types is a leading factor in animal evolution. So far, systematic characterization of the gene regulatory programs associated with cell type specificity was limited to few cell types and few species. Here, we perform whole-organism single-cell transcriptomics to map adult and larval cell types in the cnidarian Nematostella vectensis, a non-bilaterian animal with complex tissue-level body-plan organization. We uncover eight broad cell classes in Nematostella, including neurons, cnidocytes, and digestive cells. Each class comprises different subtypes defined by the expression of multiple specific markers. In particular, we characterize a surprisingly diverse repertoire of neurons, which comparative analysis suggests are the result of lineage-specific diversification. By integrating transcription factor expression, chromatin profiling, and sequence motif analysis, we identify the regulatory codes that underlie Nematostella cell-specific expression. Our study reveals cnidarian cell type complexity and provides insights into the evolution of animal cell-specific genomic regulation. Copyright © 2018 Elsevier Inc. All rights reserved.

Inferring diffusion in single live cells at the single-molecule level

PubMed Central

Robson, Alex; Burrage, Kevin; Leake, Mark C.

2013-01-01

The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffusing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell membrane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the molecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to discriminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells. PMID:23267182

Single cell multiplexed assay for proteolytic activity using droplet microfluidics.

PubMed

Ng, Ee Xien; Miller, Miles A; Jing, Tengyang; Chen, Chia-Hung

2016-07-15

Cellular enzymes interact in a post-translationally regulated fashion to govern individual cell behaviors, yet current platform technologies are limited in their ability to measure multiple enzyme activities simultaneously in single cells. Here, we developed multi-color Förster resonance energy transfer (FRET)-based enzymatic substrates and use them in a microfluidics platform to simultaneously measure multiple specific protease activities from water-in-oil droplets that contain single cells. By integrating the microfluidic platform with a computational analytical method, Proteolytic Activity Matrix Analysis (PrAMA), we are able to infer six different protease activity signals from individual cells in a high throughput manner (~100 cells/experimental run). We characterized protease activity profiles at single cell resolution for several cancer cell lines including breast cancer cell line MDA-MB-231, lung cancer cell line PC-9, and leukemia cell line K-562 using both live-cell and in-situ cell lysis assay formats, with special focus on metalloproteinases important in metastasis. The ability to measure multiple proteases secreted from or expressed in individual cells allows us to characterize cell heterogeneity and has potential applications including systems biology, pharmacology, cancer diagnosis and stem cell biology. Copyright © 2016 Elsevier B.V. All rights reserved.

Single-cell vs. bulk activity properties of coastal bacterioplankton over an annual cycle in a temperate ecosystem.

PubMed

Morán, Xosé Anxelu G; Calvo-Díaz, Alejandra

2009-01-01

The connections between single-cell activity properties of heterotrophic planktonic bacteria and whole community metabolism are still poorly understood. Here, we show flow cytometry single-cell analysis of membrane-intact (live), high nucleic acid (HNA) content and actively respiring (CTC+) bacteria with samples collected monthly during 2006 in northern Spain coastal waters. Bulk activity was assessed by measuring 3H-Leucine incorporation and specific growth rates. Consistently, different single-cell relative abundances were found, with 60-100% for live, 30-84% for HNA and 0.2-12% for CTC+ cells. Leucine incorporation rates (2-153 pmol L(-1) h(-1)), specific growth rates (0.01-0.29 day(-1)) and the total and relative abundances of the three single-cell groups showed marked seasonal patterns. Distinct depth distributions during summer stratification and different relations with temperature, chlorophyll and bacterial biovolume suggest the existence of different controlling factors on each single-cell property. Pooled leucine incorporation rates were similarly correlated with the abundance of all physiological groups, while specific growth rates were only substantially explained by the percentage of CTC+ cells. However, the ability to reduce CTC proved notably better than the other two single-cell properties at predicting bacterial bulk rates within seasons, suggesting a tight linkage between bacterial individual respiration and biomass production at the community level.

Stand-Sit Microchip for High-Throughput, Multiplexed Analysis of Single Cancer Cells.

PubMed

Ramirez, Lisa; Herschkowitz, Jason I; Wang, Jun

2016-09-01

Cellular heterogeneity in function and response to therapeutics has been a major challenge in cancer treatment. The complex nature of tumor systems calls for the development of advanced multiplexed single-cell tools that can address the heterogeneity issue. However, to date such tools are only available in a laboratory setting and don't have the portability to meet the needs in point-of-care cancer diagnostics. Towards that application, we have developed a portable single-cell system that is comprised of a microchip and an adjustable clamp, so on-chip operation only needs pipetting and adjusting of clamping force. Up to 10 proteins can be quantitated from each cell with hundreds of single-cell assays performed in parallel from one chip operation. We validated the technology and analyzed the oncogenic signatures of cancer stem cells by quantitating both aldehyde dehydrogenase (ALDH) activities and 5 signaling proteins in single MDA-MB-231 breast cancer cells. The technology has also been used to investigate the PI3K pathway activities of brain cancer cells expressing mutant epidermal growth factor receptor (EGFR) after drug intervention targeting EGFR signaling. Our portable single-cell system will potentially have broad application in the preclinical and clinical settings for cancer diagnosis in the future.

Developments in label-free microfluidic methods for single-cell analysis and sorting.

PubMed

Carey, Thomas R; Cotner, Kristen L; Li, Brian; Sohn, Lydia L

2018-04-24

Advancements in microfluidic technologies have led to the development of many new tools for both the characterization and sorting of single cells without the need for exogenous labels. Label-free microfluidics reduce the preparation time, reagents needed, and cost of conventional methods based on fluorescent or magnetic labels. Furthermore, these devices enable analysis of cell properties such as mechanical phenotype and dielectric parameters that cannot be characterized with traditional labels. Some of the most promising technologies for current and future development toward label-free, single-cell analysis and sorting include electronic sensors such as Coulter counters and electrical impedance cytometry; deformation analysis using optical traps and deformation cytometry; hydrodynamic sorting such as deterministic lateral displacement, inertial focusing, and microvortex trapping; and acoustic sorting using traveling or standing surface acoustic waves. These label-free microfluidic methods have been used to screen, sort, and analyze cells for a wide range of biomedical and clinical applications, including cell cycle monitoring, rapid complete blood counts, cancer diagnosis, metastatic progression monitoring, HIV and parasite detection, circulating tumor cell isolation, and point-of-care diagnostics. Because of the versatility of label-free methods for characterization and sorting, the low-cost nature of microfluidics, and the rapid prototyping capabilities of modern microfabrication, we expect this class of technology to continue to be an area of high research interest going forward. New developments in this field will contribute to the ongoing paradigm shift in cell analysis and sorting technologies toward label-free microfluidic devices, enabling new capabilities in biomedical research tools as well as clinical diagnostics. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices. © 2018 Wiley Periodicals, Inc.

Optimization and evaluation of single-cell whole-genome multiple displacement amplification.

PubMed

Spits, C; Le Caignec, C; De Rycke, M; Van Haute, L; Van Steirteghem, A; Liebaers, I; Sermon, K

2006-05-01

The scarcity of genomic DNA can be a limiting factor in some fields of genetic research. One of the methods developed to overcome this difficulty is whole genome amplification (WGA). Recently, multiple displacement amplification (MDA) has proved very efficient in the WGA of small DNA samples and pools of cells, the reaction being catalyzed by the phi29 or the Bst DNA polymerases. The aim of the present study was to develop a reliable, efficient, and fast protocol for MDA at the single-cell level. We first compared the efficiency of phi29 and Bst polymerases on DNA samples and single cells. The phi29 polymerase generated accurately, in a short time and from a single cell, sufficient DNA for a large set of tests, whereas the Bst enzyme showed a low efficiency and a high error rate. A single-cell protocol was optimized using the phi29 polymerase and was evaluated on 60 single cells; the DNA obtained DNA was assessed by 22 locus-specific PCRs. This new protocol can be useful for many applications involving minute quantities of starting material, such as forensic DNA analysis, prenatal and preimplantation genetic diagnosis, or cancer research. (c) 2006 Wiley-Liss, Inc.

Toward a Droplet-Based Single-Cell Radiometric Assay.

PubMed

Gallina, Maria Elena; Kim, Tae Jin; Shelor, Mark; Vasquez, Jaime; Mongersun, Amy; Kim, Minkyu; Tang, Sindy K Y; Abbyad, Paul; Pratx, Guillem

2017-06-20

Radiotracers are widely used to track molecular processes, both in vitro and in vivo, with high sensitivity and specificity. However, most radionuclide detection methods have spatial resolution inadequate for single-cell analysis. A few existing methods can extract single-cell information from radioactive decays, but the stochastic nature of the process precludes high-throughput measurement (and sorting) of single cells. In this work, we introduce a new concept for translating radioactive decays occurring stochastically within radiolabeled single-cells into an integrated, long-lasting fluorescence signal. Single cells are encapsulated in radiofluorogenic droplets containing molecular probes sensitive to byproducts of ionizing radiation (primarily reactive oxygen species, or ROS). Different probes were examined in bulk solutions, and dihydrorhodamine 123 (DHRh 123) was selected as the lead candidate due to its sensitivity and reproducibility. Fluorescence intensity of DHRh 123 in bulk increased at a rate of 54% per Gy of X-ray radiation and 15% per MBq/ml of 2-deoxy-2-[ 18 F]-fluoro-d-glucose ([ 18 F]FDG). Fluorescence imaging of microfluidic droplets showed the same linear response, but droplets were less sensitive overall than the bulk ROS sensor (detection limit of 3 Gy per droplet). Finally, droplets encapsulating radiolabeled cancer cells allowed, for the first time, the detection of [ 18 F]FDG radiotracer uptake in single cells through fluorescence activation. With further improvements, we expect this technology to enable quantitative measurement and selective sorting of single cells based on the uptake of radiolabeled small molecules.

Multiparameter cell affinity chromatography: separation and analysis in a single microfluidic channel.

PubMed

Li, Peng; Gao, Yan; Pappas, Dimitri

2012-10-02

The ability to sort and capture more than one cell type from a complex sample will enable a wide variety of studies of cell proliferation and death and the analysis of disease states. In this work, we integrated a pneumatic actuated control layer to an affinity separation layer to create different antibody-coating regions on the same fluidic channel. The comparison of different antibody capture capabilities to the same cell line was demonstrated by flowing Ramos cells through anti-CD19- and anti-CD71-coated regions in the same channel. It was determined that the cell capture density on the anti-CD19 region was 2.44 ± 0.13 times higher than that on the anti-CD71-coated region. This approach can be used to test different affinity molecules for selectivity and capture efficiency using a single cell line in one separation. Selective capture of Ramos and HuT 78 cells from a mixture was also demonstrated using two antibody regions in the same channel. Greater than 90% purity was obtained on both capture areas in both continuous flow and stop flow separation modes. A four-region antibody-coated device was then fabricated to study the simultaneous, serial capture of three different cell lines. In this case the device showed effective capture of cells in a single separation channel, opening up the possibility of multiple cell sorting. Multiparameter sequential blood sample analysis was also demonstrated with high capture specificity (>97% for both CD19+ and CD4+ leukocytes). The chip can also be used to selectively treat cells after affinity separation.

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

PubMed

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

2017-07-01

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

Single-cell trapping and selective treatment via co-flow within a microfluidic platform.

PubMed

Benavente-Babace, A; Gallego-Pérez, D; Hansford, D J; Arana, S; Pérez-Lorenzo, E; Mujika, M

2014-11-15

Lab on a chip (LOC) systems provide interesting and low-cost solutions for key studies and applications in the biomedical field. Along with microfluidics, these microdevices make single-cell manipulation possible with high spatial and temporal resolution. In this work we have designed, fabricated and characterized a versatile and inexpensive microfluidic platform for on-chip selective single-cell trapping and treatment using laminar co-flow. The combination of co-existing laminar flow manipulation and hydrodynamic single-cell trapping for selective treatment offers a cost-effective solution for studying the effect of novel drugs on single-cells. The operation of the whole system is experimentally simple, highly adaptable and requires no specific equipment. As a proof of concept, a cytotoxicity study of ethanol in isolated hepatocytes is presented. The developed microfluidic platform controlled by means of co-flow is an attractive and multipurpose solution for the study of new substances of high interest in cell biology research. In addition, this platform will pave the way for the study of cell behavior under dynamic and controllable fluidic conditions providing information at the individual cell level. Thus, this analysis device could also hold a great potential to easily use the trapped cells as sensing elements expanding its functionalities as a cell-based biosensor with single-cell resolution. Copyright © 2014 Elsevier B.V. All rights reserved.

Metabolic Imaging in Multiple Time Scales

PubMed Central

Ramanujan, V Krishnan

2013-01-01

We report here a novel combination of time-resolved imaging methods for probing mitochondrial metabolism multiple time scales at the level of single cells. By exploiting a mitochondrial membrane potential reporter fluorescence we demonstrate the single cell metabolic dynamics in time scales ranging from milliseconds to seconds to minutes in response to glucose metabolism and mitochondrial perturbations in real time. Our results show that in comparison with normal human mammary epithelial cells, the breast cancer cells display significant alterations in metabolic responses at all measured time scales by single cell kinetics, fluorescence recovery after photobleaching and by scaling analysis of time-series data obtained from mitochondrial fluorescence fluctuations. Furthermore scaling analysis of time-series data in living cells with distinct mitochondrial dysfunction also revealed significant metabolic differences thereby suggesting the broader applicability (e.g. in mitochondrial myopathies and other metabolic disorders) of the proposed strategies beyond the scope of cancer metabolism. We discuss the scope of these findings in the context of developing portable, real-time metabolic measurement systems that can find applications in preclinical and clinical diagnostics. PMID:24013043

Dissecting biological “dark matter” with single-cell genetic analysis of rare and uncultivated TM7 microbes from the human mouth

PubMed Central

Marcy, Yann; Ouverney, Cleber; Bik, Elisabeth M.; Lösekann, Tina; Ivanova, Natalia; Martin, Hector Garcia; Szeto, Ernest; Platt, Darren; Hugenholtz, Philip; Relman, David A.; Quake, Stephen R.

2007-01-01

We have developed a microfluidic device that allows the isolation and genome amplification of individual microbial cells, thereby enabling organism-level genomic analysis of complex microbial ecosystems without the need for culture. This device was used to perform a directed survey of the human subgingival crevice and to isolate bacteria having rod-like morphology. Several isolated microbes had a 16S rRNA sequence that placed them in candidate phylum TM7, which has no cultivated or sequenced members. Genome amplification from individual TM7 cells allowed us to sequence and assemble >1,000 genes, providing insight into the physiology of members of this phylum. This approach enables single-cell genetic analysis of any uncultivated minority member of a microbial community. PMID:17620602

Single Stem Cell Imaging and Analysis Reveals Telomere Length Differences in Diseased Human and Mouse Skeletal Muscles.

PubMed

Tichy, Elisia D; Sidibe, David K; Tierney, Matthew T; Stec, Michael J; Sharifi-Sanjani, Maryam; Hosalkar, Harish; Mubarak, Scott; Johnson, F Brad; Sacco, Alessandra; Mourkioti, Foteini

2017-10-10

Muscle stem cells (MuSCs) contribute to muscle regeneration following injury. In many muscle disorders, the repeated cycles of damage and repair lead to stem cell dysfunction. While telomere attrition may contribute to aberrant stem cell functions, methods to accurately measure telomere length in stem cells from skeletal muscles have not been demonstrated. Here, we have optimized and validated such a method, named MuQ-FISH, for analyzing telomere length in MuSCs from either mice or humans. Our analysis showed no differences in telomere length between young and aged MuSCs from uninjured wild-type mice, but MuSCs isolated from young dystrophic mice exhibited significantly shortened telomeres. In corroboration, we demonstrated that telomere attrition is present in human dystrophic MuSCs, which underscores its importance in diseased regenerative failure. The robust technique described herein provides analysis at a single-cell resolution and may be utilized for other cell types, especially rare populations of cells. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Separation and parallel sequencing of the genomes and transcriptomes of single cells using G&T-seq.

PubMed

Macaulay, Iain C; Teng, Mabel J; Haerty, Wilfried; Kumar, Parveen; Ponting, Chris P; Voet, Thierry

2016-11-01

Parallel sequencing of a single cell's genome and transcriptome provides a powerful tool for dissecting genetic variation and its relationship with gene expression. Here we present a detailed protocol for G&T-seq, a method for separation and parallel sequencing of genomic DNA and full-length polyA(+) mRNA from single cells. We provide step-by-step instructions for the isolation and lysis of single cells; the physical separation of polyA(+) mRNA from genomic DNA using a modified oligo-dT bead capture and the respective whole-transcriptome and whole-genome amplifications; and library preparation and sequence analyses of these amplification products. The method allows the detection of thousands of transcripts in parallel with the genetic variants captured by the DNA-seq data from the same single cell. G&T-seq differs from other currently available methods for parallel DNA and RNA sequencing from single cells, as it involves physical separation of the DNA and RNA and does not require bespoke microfluidics platforms. The process can be implemented manually or through automation. When performed manually, paired genome and transcriptome sequencing libraries from eight single cells can be produced in ∼3 d by researchers experienced in molecular laboratory work. For users with experience in the programming and operation of liquid-handling robots, paired DNA and RNA libraries from 96 single cells can be produced in the same time frame. Sequence analysis and integration of single-cell G&T-seq DNA and RNA data requires a high level of bioinformatics expertise and familiarity with a wide range of informatics tools.

Single Upconversion Nanoparticle-Bacterium Cotrapping for Single-Bacterium Labeling and Analysis.

PubMed

Xin, Hongbao; Li, Yuchao; Xu, Dekang; Zhang, Yueli; Chen, Chia-Hung; Li, Baojun

2017-04-01

Detecting and analyzing pathogenic bacteria in an effective and reliable manner is crucial for the diagnosis of acute bacterial infection and initial antibiotic therapy. However, the precise labeling and analysis of bacteria at the single-bacterium level are a technical challenge but very important to reveal important details about the heterogeneity of cells and responds to environment. This study demonstrates an optical strategy for single-bacterium labeling and analysis by the cotrapping of single upconversion nanoparticles (UCNPs) and bacteria together. A single UCNP with an average size of ≈120 nm is first optically trapped. Both ends of a single bacterium are then trapped and labeled with single UCNPs emitting green light. The labeled bacterium can be flexibly moved to designated locations for further analysis. Signals from bacteria of different sizes are detected in real time for single-bacterium analysis. This cotrapping method provides a new approach for single-pathogenic-bacterium labeling, detection, and real-time analysis at the single-particle and single-bacterium level. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-Throughput Particle Uptake Analysis by Imaging Flow Cytometry

PubMed Central

Smirnov, Asya; Solga, Michael D.; Lannigan, Joanne; Criss, Alison K.

2017-01-01

Quantifying the efficiency of particle uptake by host cells is important in fields including infectious diseases, autoimmunity, cancer, developmental biology, and drug delivery. Here we present a protocol for high-throughput analysis of particle uptake using imaging flow cytometry, using the bacterium Neisseria gonorrhoeae attached and internalized to neutrophils as an example. Cells are exposed to fluorescently labeled bacteria, fixed, and stained with a bacteria-specific antibody of a different fluorophore. Thus in the absence of a permeabilizing agent, extracellular bacteria are double-labeled with two fluorophores while intracellular bacteria remain single-labeled. A spot count algorithm is used to determine the number of single- and double-labeled bacteria in individual cells, to calculate the percent of cells associated with bacteria, percent of cells with internalized bacteria, and percent of cell-associated bacteria that are internalized. These analyses quantify bacterial association and internalization across thousands of cells and can be applied to diverse experimental systems. PMID:28369762

Multiple displacement amplification on single cell and possible PGD applications.

PubMed

Hellani, Ali; Coskun, Serdar; Benkhalifa, Moncef; Tbakhi, Abelghani; Sakati, Nadia; Al-Odaib, Ali; Ozand, Pinar

2004-11-01

Multiple displacement amplification (MDA) is a technique used in the amplification of very low amounts of DNA and reported to yield large quantities of high-quality DNA. We used MDA to amplify the whole genome directly from a single cell. The most common techniques used in PGD are PCR and fluorescent in-situ hybridization (FISH). There are many limitations to these techniques including, the number of chromosomes diagnosed for FISH or the quality of DNA issued from a single cell PCR. This report shows, for the first time, use of MDA for single cell whole genome amplification. A total of 16 short tandem repeats (STRs) were amplified successfully with a similar pattern to the genomic DNA. Furthermore, allelic drop out (ADO) derived from MDA was assessed in 40 single cells by analysing (i) heterozygosity for a known beta globin mutation (IVSI-5 C-G) and by studying (ii) the heterozygous loci present in the STRs. ADO turned out to be 10.25% for the beta globin gene sequencing and 5% for the fluorescent PCR analysis of STRs. Moreover, the amplification accuracy of MDA permitted the detection of trisomy 21 on a single cell using comparative genome hybridization-array. Altogether, these data suggest that MDA can be used for single cell molecular karyotyping and the diagnosis of any single gene disorder in PGD.

Single-cell template strand sequencing by Strand-seq enables the characterization of individual homologs.

PubMed

Sanders, Ashley D; Falconer, Ester; Hills, Mark; Spierings, Diana C J; Lansdorp, Peter M

2017-06-01

The ability to distinguish between genome sequences of homologous chromosomes in single cells is important for studies of copy-neutral genomic rearrangements (such as inversions and translocations), building chromosome-length haplotypes, refining genome assemblies, mapping sister chromatid exchange events and exploring cellular heterogeneity. Strand-seq is a single-cell sequencing technology that resolves the individual homologs within a cell by restricting sequence analysis to the DNA template strands used during DNA replication. This protocol, which takes up to 4 d to complete, relies on the directionality of DNA, in which each single strand of a DNA molecule is distinguished based on its 5'-3' orientation. Culturing cells in a thymidine analog for one round of cell division labels nascent DNA strands, allowing for their selective removal during genomic library construction. To preserve directionality of template strands, genomic preamplification is bypassed and labeled nascent strands are nicked and not amplified during library preparation. Each single-cell library is multiplexed for pooling and sequencing, and the resulting sequence data are aligned, mapping to either the minus or plus strand of the reference genome, to assign template strand states for each chromosome in the cell. The major adaptations to conventional single-cell sequencing protocols include harvesting of daughter cells after a single round of BrdU incorporation, bypassing of whole-genome amplification, and removal of the BrdU + strand during Strand-seq library preparation. By sequencing just template strands, the structure and identity of each homolog are preserved.

Multidimensional analysis of the frequencies and rates of cytokine secretion from single cells by quantitative microengraving.

PubMed

Han, Qing; Bradshaw, Elizabeth M; Nilsson, Björn; Hafler, David A; Love, J Christopher

2010-06-07

The large diversity of cells that comprise the human immune system requires methods that can resolve the individual contributions of specific subsets to an immunological response. Microengraving is process that uses a dense, elastomeric array of microwells to generate microarrays of proteins secreted from large numbers of individual live cells (approximately 10(4)-10(5) cells/assay). In this paper, we describe an approach based on this technology to quantify the rates of secretion from single immune cells. Numerical simulations of the microengraving process indicated an operating regime between 30 min-4 h that permits quantitative analysis of the rates of secretion. Through experimental validation, we demonstrate that microengraving can provide quantitative measurements of both the frequencies and the distribution in rates of secretion for up to four cytokines simultaneously released from individual viable primary immune cells. The experimental limits of detection ranged from 0.5 to 4 molecules/s for IL-6, IL-17, IFNgamma, IL-2, and TNFalpha. These multidimensional measures resolve the number and intensities of responses by cells exposed to stimuli with greater sensitivity than single-parameter assays for cytokine release. We show that cells from different donors exhibit distinct responses based on both the frequency and magnitude of cytokine secretion when stimulated under different activating conditions. Primary T cells with specific profiles of secretion can also be recovered after microengraving for subsequent expansion in vitro. These examples demonstrate the utility of quantitative, multidimensional profiles of single cells for analyzing the diversity and dynamics of immune responses in vitro and for identifying rare cells from clinical samples.

Single cell model for simultaneous drug delivery and efflux.

PubMed

Yi, C; Saidel, G M; Gratzl, M

1999-01-01

Multidrug resistance (MDR) of some cancer cells is a major challenge for chemotherapy of systemic cancers to overcome. To experimentally uncover the cellular mechanisms leading to MDR, it is necessary to quantitatively assess both drug influx into, and efflux from, the cells exposed to drug treatment. By using a novel molecular microdelivery system to enforce continuous and adjustable drug influx into single cells by controlled diffusion through a gel plug in a micropipet tip, drug resistance studies can now be performed on the single cell level. Our dynamic model of this scheme incorporates drug delivery, diffusive mixing, and accumulation inside the cytoplasm, and efflux by both passive and active membrane transport. Model simulations using available experimental information on these processes can assist in the design of MDR related experiments on single cancer cells which are expected to lead to a quantitative evaluation of mechanisms. Simulations indicate that drug resistance of a cancer cell can be quantified better by its dynamic response than by steady-state analysis.

Single-cell and subcellular pharmacokinetic imaging allows insight into drug action in vivo.

PubMed

Thurber, Greg M; Yang, Katy S; Reiner, Thomas; Kohler, Rainer H; Sorger, Peter; Mitchison, Tim; Weissleder, Ralph

2013-01-01

Pharmacokinetic analysis at the organ level provides insight into how drugs distribute throughout the body, but cannot explain how drugs work at the cellular level. Here we demonstrate in vivo single-cell pharmacokinetic imaging of PARP-1 inhibitors and model drug behaviour under varying conditions. We visualize intracellular kinetics of the PARP-1 inhibitor distribution in real time, showing that PARP-1 inhibitors reach their cellular target compartment, the nucleus, within minutes in vivo both in cancer and normal cells in various cancer models. We also use these data to validate predictive finite element modelling. Our theoretical and experimental data indicate that tumour cells are exposed to sufficiently high PARP-1 inhibitor concentrations in vivo and suggest that drug inefficiency is likely related to proteomic heterogeneity or insensitivity of cancer cells to DNA-repair inhibition. This suggests that single-cell pharmacokinetic imaging and derived modelling improve our understanding of drug action at single-cell resolution in vivo.

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

PubMed

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

2018-01-01

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

Comparison of single cell sequencing data between two whole genome amplification methods on two sequencing platforms.

PubMed

Chen, DaYang; Zhen, HeFu; Qiu, Yong; Liu, Ping; Zeng, Peng; Xia, Jun; Shi, QianYu; Xie, Lin; Zhu, Zhu; Gao, Ya; Huang, GuoDong; Wang, Jian; Yang, HuanMing; Chen, Fang

2018-03-21

Research based on a strategy of single-cell low-coverage whole genome sequencing (SLWGS) has enabled better reproducibility and accuracy for detection of copy number variations (CNVs). The whole genome amplification (WGA) method and sequencing platform are critical factors for successful SLWGS (<0.1 × coverage). In this study, we compared single cell and multiple cells sequencing data produced by the HiSeq2000 and Ion Proton platforms using two WGA kits and then comprehensively evaluated the GC-bias, reproducibility, uniformity and CNV detection among different experimental combinations. Our analysis demonstrated that the PicoPLEX WGA Kit resulted in higher reproducibility, lower sequencing error frequency but more GC-bias than the GenomePlex Single Cell WGA Kit (WGA4 kit) independent of the cell number on the HiSeq2000 platform. While on the Ion Proton platform, the WGA4 kit (both single cell and multiple cells) had higher uniformity and less GC-bias but lower reproducibility than those of the PicoPLEX WGA Kit. Moreover, on these two sequencing platforms, depending on cell number, the performance of the two WGA kits was different for both sensitivity and specificity on CNV detection. The results can help researchers who plan to use SLWGS on single or multiple cells to select appropriate experimental conditions for their applications.

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

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.

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.

Dissecting Cell-Type Composition and Activity-Dependent Transcriptional State in Mammalian Brains by Massively Parallel Single-Nucleus RNA-Seq.

PubMed

Hu, Peng; Fabyanic, Emily; Kwon, Deborah Y; Tang, Sheng; Zhou, Zhaolan; Wu, Hao

2017-12-07

Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues such as adult mammalian brains is challenging. Here, we integrate sucrose-gradient-assisted purification of nuclei with droplet microfluidics to develop a highly scalable single-nucleus RNA-seq approach (sNucDrop-seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ∼18,000 nuclei isolated from cortical tissues of adult mice, we demonstrate that sNucDrop-seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity but also enables in-depth analysis of transient transcriptional states driven by neuronal activity, at single-cell resolution, in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Single cell proteomics in biomedicine: High-dimensional data acquisition, visualization, and analysis.

PubMed

Su, Yapeng; Shi, Qihui; Wei, Wei

2017-02-01

New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mutagenic effects of a single and an exact number of alpha particles in mammalian cells

NASA Technical Reports Server (NTRS)

Hei, T. K.; Wu, L. J.; Liu, S. X.; Vannais, D.; Waldren, C. A.; Randers-Pehrson, G.

1997-01-01

One of the main uncertainties in risk estimation for environmental radon exposure using lung cancer data from underground miners is the extrapolation from high- to low-dose exposure where multiple traversal is extremely rare. The biological effects of a single alpha particle are currently unknown. Using the recently available microbeam source at the Radiological Research Accelerator Facility at Columbia University, we examined the frequencies and molecular spectrum of S1- mutants induced in human-hamster hybrid (A(L)) cells by either a single or an exact number of alpha particles. Exponentially growing cells were stained briefly with a nontoxic concentration of Hoechst dye for image analysis, and the location of individual cells was computer-monitored. The nucleus of each cell was irradiated with either 1,2,4, or 8 alpha particles at a linear energy transfer of 90 keV/microm consistent with the energy spectrum of domestic radon exposure. Although single-particle traversal was only slightly cytotoxic to A(L) cells (survival fraction approximately 0.82), it was highly mutagenic, and the induced mutant fraction averaged 110 mutants per 10(5) survivors. In addition, both toxicity and mutant induction were dose-dependent. Multiplex PCR analysis of mutant DNA showed that the proportion of mutants with multilocus deletions increased with the number of particle traversals. These data provide direct evidence that a single a particle traversing a nucleus will have a high probability of resulting in a mutation and highlight the need for radiation protection at low doses.

Mutagenic effects of a single and an exact number of alpha particles in mammalian cells.

PubMed

Hei, T K; Wu, L J; Liu, S X; Vannais, D; Waldren, C A; Randers-Pehrson, G

1997-04-15

One of the main uncertainties in risk estimation for environmental radon exposure using lung cancer data from underground miners is the extrapolation from high- to low-dose exposure where multiple traversal is extremely rare. The biological effects of a single alpha particle are currently unknown. Using the recently available microbeam source at the Radiological Research Accelerator Facility at Columbia University, we examined the frequencies and molecular spectrum of S1- mutants induced in human-hamster hybrid (A(L)) cells by either a single or an exact number of alpha particles. Exponentially growing cells were stained briefly with a nontoxic concentration of Hoechst dye for image analysis, and the location of individual cells was computer-monitored. The nucleus of each cell was irradiated with either 1,2,4, or 8 alpha particles at a linear energy transfer of 90 keV/microm consistent with the energy spectrum of domestic radon exposure. Although single-particle traversal was only slightly cytotoxic to A(L) cells (survival fraction approximately 0.82), it was highly mutagenic, and the induced mutant fraction averaged 110 mutants per 10(5) survivors. In addition, both toxicity and mutant induction were dose-dependent. Multiplex PCR analysis of mutant DNA showed that the proportion of mutants with multilocus deletions increased with the number of particle traversals. These data provide direct evidence that a single a particle traversing a nucleus will have a high probability of resulting in a mutation and highlight the need for radiation protection at low doses.

Single shot white light interference microscopy with colour fringe analysis for quantitative phase imaging of biological cells

NASA Astrophysics Data System (ADS)

Srivastava, Vishal; Mehta, D. S.

2013-02-01

To quantitatively obtain the phase map of Onion and human red blood cell (RBC) from white light interferogram we used Hilbert transform color fringe analysis technique. The three Red, Blue and Green color components are decomposed from single white light interferogram and Refractive index profile for Red, Blue and Green colour were computed in a completely non-invasive manner for Onion and human RBC. The present technique might be useful for non-invasive determination of the refractive index variation within cells and tissues and morphological features of sample with ease of operation and low cost.

Photocleavable DNA barcode-antibody conjugates allow sensitive and multiplexed protein analysis in single cells.

PubMed

Agasti, Sarit S; Liong, Monty; Peterson, Vanessa M; Lee, Hakho; Weissleder, Ralph

2012-11-14

DNA barcoding is an attractive technology, as it allows sensitive and multiplexed target analysis. However, DNA barcoding of cellular proteins remains challenging, primarily because barcode amplification and readout techniques are often incompatible with the cellular microenvironment. Here we describe the development and validation of a photocleavable DNA barcode-antibody conjugate method for rapid, quantitative, and multiplexed detection of proteins in single live cells. Following target binding, this method allows DNA barcodes to be photoreleased in solution, enabling easy isolation, amplification, and readout. As a proof of principle, we demonstrate sensitive and multiplexed detection of protein biomarkers in a variety of cancer cells.

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

PubMed

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

2017-11-01

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

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.

In vivo and in situ monitoring of the nitric oxide stimulus response of single cancer cells by Raman spectroscopy

NASA Astrophysics Data System (ADS)

Su, L.; Chen, Y.; Zhang, G. N.; Wang, L. H.; Shen, A. G.; Zhou, X. D.; Wang, X. H.; Hu, J. M.

2013-04-01

Raman spectroscopy is capable of studying time-resolved information of selected biomolecular distributions inside individual cells without labeling. In this study, Raman spectroscopy was for the first time utilized to in vivo and in situ monitor the cellular response to nitric oxide (NO) in single oral squamous cell carcinoma (OSCC) cells over a period of 24 h. Sodium nitroprusside (SNP) was chosen as a NO donor to be incubated with the OSCC cell line (TCA8113) for certain time intervals. In vivo and in situ Raman analysis revealed that the degradation and conformational changes of nucleic acids, lipids and proteins could be directly observed by changes in the characteristic Raman bands. In comparison with conventional flow cytometric analysis, Raman spectroscopy not only detected more subtle NO-induced chemical changes of cells, where the SNP concentration could be even less than 1 mM, but also provided a full view of the whole chemical components of single cells. Raman spectroscopy therefore is an important candidate for label-free, nondestructive and in situ monitoring of cellular changes in response to chemotherapeutic agents, which could potentially be used in rapid screening of novel drugs.

Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq.

PubMed

Chen, Jun; Suo, Shengbao; Tam, Patrick Pl; Han, Jing-Dong J; Peng, Guangdun; Jing, Naihe

2017-03-01

Conventional gene expression studies analyze multiple cells simultaneously or single cells, for which the exact in vivo or in situ position is unknown. Although cellular heterogeneity can be discerned when analyzing single cells, any spatially defined attributes that underpin the heterogeneous nature of the cells cannot be identified. Here, we describe how to use Geo-seq, a method that combines laser capture microdissection (LCM) and single-cell RNA-seq technology. The combination of these two methods enables the elucidation of cellular heterogeneity and spatial variance simultaneously. The Geo-seq protocol allows the profiling of transcriptome information from only a small number cells and retains their native spatial information. This protocol has wide potential applications to address biological and pathological questions of cellular properties such as prospective cell fates, biological function and the gene regulatory network. Geo-seq has been applied to investigate the spatial transcriptome of mouse early embryo, mouse brain, and pathological liver and sperm tissues. The entire protocol from tissue collection and microdissection to sequencing requires ∼5 d, Data analysis takes another 1 or 2 weeks, depending on the amount of data and the speed of the processor.

Bright monomeric photoactivatable red fluorescent protein for two-color super-resolution sptPALM of live cells.

PubMed

Subach, Fedor V; Patterson, George H; Renz, Malte; Lippincott-Schwartz, Jennifer; Verkhusha, Vladislav V

2010-05-12

Rapidly emerging techniques of super-resolution single-molecule microscopy of living cells rely on the continued development of genetically encoded photoactivatable fluorescent proteins. On the basis of monomeric TagRFP, we have developed a photoactivatable TagRFP protein that is initially dark but becomes red fluorescent after violet light irradiation. Compared to other monomeric dark-to-red photoactivatable proteins including PAmCherry, PATagRFP has substantially higher molecular brightness, better pH stability, substantially less sensitivity to blue light, and better photostability in both ensemble and single-molecule modes. Spectroscopic analysis suggests that PATagRFP photoactivation is a two-step photochemical process involving sequential one-photon absorbance by two distinct chromophore forms. True monomeric behavior, absence of green fluorescence, and single-molecule performance in live cells make PATagRFP an excellent protein tag for two-color imaging techniques, including conventional diffraction-limited photoactivation microscopy, super-resolution photoactivated localization microscopy (PALM), and single particle tracking PALM (sptPALM) of living cells. Two-color sptPALM imaging was demonstrated using several PATagRFP tagged transmembrane proteins together with PAGFP-tagged clathrin light chain. Analysis of the resulting sptPALM images revealed that single-molecule transmembrane proteins, which are internalized into a cell via endocytosis, colocalize in space and time with plasma membrane domains enriched in clathrin light-chain molecules.

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

PubMed Central

Grimm, Jonathan B; Lavis, Luke D

2018-01-01

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

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

PubMed

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

2018-01-04

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

Single-cell proteomics: potential implications for cancer diagnostics.

PubMed

Gavasso, Sonia; Gullaksen, Stein-Erik; Skavland, Jørn; Gjertsen, Bjørn T

2016-01-01

Single-cell proteomics in cancer is evolving and promises to provide more accurate diagnoses based on detailed molecular features of cells within tumors. This review focuses on technologies that allow for collection of complex data from single cells, but also highlights methods that are adaptable to routine cancer diagnostics. Current diagnostics rely on histopathological analysis, complemented by mutational detection and clinical imaging. Though crucial, the information gained is often not directly transferable to defined therapeutic strategies, and predicting therapy response in a patient is difficult. In cancer, cellular states revealed through perturbed intracellular signaling pathways can identify functional mutations recurrent in cancer subsets. Single-cell proteomics remains to be validated in clinical trials where serial samples before and during treatment can reveal excessive clonal evolution and therapy failure; its use in clinical trials is anticipated to ignite a diagnostic revolution that will better align diagnostics with the current biological understanding of cancer.

Single-cell RNA-sequencing: The future of genome biology is now

PubMed Central

Picelli, Simone

2017-01-01

ABSTRACT Genome-wide single-cell analysis represents the ultimate frontier of genomics research. In particular, single-cell RNA-sequencing (scRNA-seq) studies have been boosted in the last few years by an explosion of new technologies enabling the study of the transcriptomic landscape of thousands of single cells in complex multicellular organisms. More sensitive and automated methods are being continuously developed and promise to deliver better data quality and higher throughput with less hands-on time. The outstanding amount of knowledge that is going to be gained from present and future studies will have a profound impact in many aspects of our society, from the introduction of truly tailored cancer treatments, to a better understanding of antibiotic resistance and host-pathogen interactions; from the discovery of the mechanisms regulating stem cell differentiation to the characterization of the early event of human embryogenesis. PMID:27442339

High-Density Dielectrophoretic Microwell Array for Detection, Capture, and Single-Cell Analysis of Rare Tumor Cells in Peripheral Blood.

PubMed

Morimoto, Atsushi; Mogami, Toshifumi; Watanabe, Masaru; Iijima, Kazuki; Akiyama, Yasuyuki; Katayama, Koji; Futami, Toru; Yamamoto, Nobuyuki; Sawada, Takeshi; Koizumi, Fumiaki; Koh, Yasuhiro

2015-01-01

Development of a reliable platform and workflow to detect and capture a small number of mutation-bearing circulating tumor cells (CTCs) from a blood sample is necessary for the development of noninvasive cancer diagnosis. In this preclinical study, we aimed to develop a capture system for molecular characterization of single CTCs based on high-density dielectrophoretic microwell array technology. Spike-in experiments using lung cancer cell lines were conducted. The microwell array was used to capture spiked cancer cells, and captured single cells were subjected to whole genome amplification followed by sequencing. A high detection rate (70.2%-90.0%) and excellent linear performance (R2 = 0.8189-0.9999) were noted between the observed and expected numbers of tumor cells. The detection rate was markedly higher than that obtained using the CellSearch system in a blinded manner, suggesting the superior sensitivity of our system in detecting EpCAM- tumor cells. Isolation of single captured tumor cells, followed by detection of EGFR mutations, was achieved using Sanger sequencing. Using a microwell array, we established an efficient and convenient platform for the capture and characterization of single CTCs. The results of a proof-of-principle preclinical study indicated that this platform has potential for the molecular characterization of captured CTCs from patients.

Dissection of Influenza Infection In Vivo by Single-Cell RNA Sequencing.

PubMed

Steuerman, Yael; Cohen, Merav; Peshes-Yaloz, Naama; Valadarsky, Liran; Cohn, Ofir; David, Eyal; Frishberg, Amit; Mayo, Lior; Bacharach, Eran; Amit, Ido; Gat-Viks, Irit

2018-06-01

The influenza virus is a major cause of morbidity and mortality worldwide. Yet, both the impact of intracellular viral replication and the variation in host response across different cell types remain uncharacterized. Here we used single-cell RNA sequencing to investigate the heterogeneity in the response of lung tissue cells to in vivo influenza infection. Analysis of viral and host transcriptomes in the same single cell enabled us to resolve the cellular heterogeneity of bystander (exposed but uninfected) as compared with infected cells. We reveal that all major immune and non-immune cell types manifest substantial fractions of infected cells, albeit at low viral transcriptome loads relative to epithelial cells. We show that all cell types respond primarily with a robust generic transcriptional response, and we demonstrate novel markers specific for influenza-infected as opposed to bystander cells. These findings open new avenues for targeted therapy aimed exclusively at infected cells. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2012-01-01

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

Microfluidic platform for multiplexed detection in single cells and methods thereof

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

Wu, Meiye; Singh, Anup K.

The present invention relates to a microfluidic device and platform configured to conduct multiplexed analysis within the device. In particular, the device allows multiple targets to be detected on a single-cell level. Also provided are methods of performing multiplexed analyses to detect one or more target nucleic acids, proteins, and post-translational modifications.

Fault tree safety analysis of a large Li/SOCl(sub)2 spacecraft battery

NASA Technical Reports Server (NTRS)

Uy, O. Manuel; Maurer, R. H.

1987-01-01

The results of the safety fault tree analysis on the eight module, 576 F cell Li/SOCl2 battery on the spacecraft and in the integration and test environment prior to launch on the ground are presented. The analysis showed that with the right combination of blocking diodes, electrical fuses, thermal fuses, thermal switches, cell balance, cell vents, and battery module vents the probability of a single cell or a 72 cell module exploding can be reduced to .000001, essentially the probability due to explosion for unexplained reasons.

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

visnormsc: A Graphical User Interface to Normalize Single-cell RNA Sequencing Data.

PubMed

Tang, Lijun; Zhou, Nan

2017-12-26

Single-cell RNA sequencing (RNA-seq) allows the analysis of gene expression with high resolution. The intrinsic defects of this promising technology imports technical noise into the single-cell RNA-seq data, increasing the difficulty of accurate downstream inference. Normalization is a crucial step in single-cell RNA-seq data pre-processing. SCnorm is an accurate and efficient method that can be used for this purpose. An R implementation of this method is currently available. On one hand, the R package possesses many excellent features from R. On the other hand, R programming ability is required, which prevents the biologists who lack the skills from learning to use it quickly. To make this method more user-friendly, we developed a graphical user interface, visnormsc, for normalization of single-cell RNA-seq data. It is implemented in Python and is freely available at https://github.com/solo7773/visnormsc . Although visnormsc is based on the existing method, it contributes to this field by offering a user-friendly alternative. The out-of-the-box and cross-platform features make visnormsc easy to learn and to use. It is expected to serve biologists by simplifying single-cell RNA-seq normalization.

Single-cell RNA-Seq reveals cell heterogeneity and hierarchy within mouse mammary epithelia.

PubMed

Sun, Heng; Miao, Zhengqiang; Zhang, Xin; Chan, Un In; Su, Sek Man; Guo, Sen; Wong, Chris Koon Ho; Xu, Xiaoling; Deng, Chu-Xia

2018-06-01

The mammary gland is very intricately and well organized into distinct tissues, including epithelia, endothelia, adipocytes, and stromal and immune cells. Many mammary gland diseases, such as breast cancer, arise from abnormalities in the mammary epithelium, which is mainly composed of two distinct lineages, the basal and luminal cells. Because of the limitation of traditional transcriptome analysis of bulk mammary cells, the hierarchy and heterogeneity of mammary cells within these two lineages remain unclear. To this end, using single-cell RNA-Seq coupled with FACS analysis and principal component analysis, we determined gene expression profiles of mammary epithelial cells of virgin and pregnant mice. These analyses revealed a much higher heterogeneity among the mammary cells than has been previously reported and enabled cell classification into distinct subgroups according to signature gene markers present in each group. We also identified and verified a rare CDH5 + cell subpopulation within a basal cell lineage as quiescent mammary stem cells (MaSCs). Moreover, using pseudo-temporal analysis, we reconstructed the developmental trajectory of mammary epithelia and uncovered distinct changes in gene expression and in biological functions of mammary cells along the developmental process. In conclusion, our work greatly refines the resolution of the cellular hierarchy in developing mammary tissues. The discovery of CDH5 + cells as MaSCs in these tissues may have implications for our understanding of the initiation, development, and pathogenesis of mammary tumors. © 2018 Sun et al.

Endocrine cells in human Bartholin's glands. An immunohistochemical and ultrastructural analysis.

PubMed

Fetissof, F; Arbeille, B; Bellet, D; Barre, I; Lansac, J

1989-01-01

Endocrine cells were investigated in human Bartholin's glands by use of histochemical, immunohistochemical and ultrastructural methods. Endocrine cells represent normal constituents of these glands, being mainly distributed throughout the transitional epithelium of the major excretory duct; however, single elements are dispersed among the acinar lobules. Serotonin-, calcitonin-, katacalcin-, bombesin- and alpha-hCG-immunoreactive cells were recognized, with serotonin-immunoreactive cells predominating. Co-expression of calcitonin, katacalcin or alpha-hCG with serotonin was observed in single endocrine cells. At the ultrastructural level, these cells are richly granulated and show typical neuroendocrine features. Bartholin's glands display an endocrine profile quite similar to that of other cloacal-derived tissues.

Cross-platform single cell analysis of kidney development shows stromal cells express Gdnf.

PubMed

Magella, Bliss; Adam, Mike; Potter, Andrew S; Venkatasubramanian, Meenakshi; Chetal, Kashish; Hay, Stuart B; Salomonis, Nathan; Potter, S Steven

2018-02-01

The developing kidney provides a useful model for study of the principles of organogenesis. In this report we use three independent platforms, Drop-Seq, Chromium 10x Genomics and Fluidigm C1, to carry out single cell RNA-Seq (scRNA-Seq) analysis of the E14.5 mouse kidney. Using the software AltAnalyze, in conjunction with the unsupervised approach ICGS, we were unable to identify and confirm the presence of 16 distinct cell populations during this stage of active nephrogenesis. Using a novel integrative supervised computational strategy, we were able to successfully harmonize and compare the cell profiles across all three technological platforms. Analysis of possible cross compartment receptor/ligand interactions identified the nephrogenic zone stroma as a source of GDNF. This was unexpected because the cap mesenchyme nephron progenitors had been thought to be the sole source of GDNF, which is a key driver of branching morphogenesis of the collecting duct system. The expression of Gdnf by stromal cells was validated in several ways, including Gdnf in situ hybridization combined with immunohistochemistry for SIX2, and marker of nephron progenitors, and MEIS1, a marker of stromal cells. Finally, the single cell gene expression profiles generated in this study confirmed and extended previous work showing the presence of multilineage priming during kidney development. Nephron progenitors showed stochastic expression of genes associated with multiple potential differentiation lineages. Copyright © 2017 Elsevier Inc. All rights reserved.

Single-Cell Sequencing of the Healthy and Diseased Heart Reveals Ckap4 as a New Modulator of Fibroblasts Activation.

PubMed

Gladka, Monika M; Molenaar, Bas; de Ruiter, Hesther; van der Elst, Stefan; Tsui, Hoyee; Versteeg, Danielle; Lacraz, Grègory P A; Huibers, Manon M H; van Oudenaarden, Alexander; van Rooij, Eva

2018-01-31

Background -Genome-wide transcriptome analysis has greatly advanced our understanding of the regulatory networks underlying basic cardiac biology and mechanisms driving disease. However, so far, the resolution of studying gene expression patterns in the adult heart has been limited to the level of extracts from whole tissues. The use of tissue homogenates inherently causes the loss of any information on cellular origin or cell type-specific changes in gene expression. Recent developments in RNA amplification strategies provide a unique opportunity to use small amounts of input RNA for genome-wide sequencing of single cells. Methods -Here, we present a method to obtain high quality RNA from digested cardiac tissue from adult mice for automated single-cell sequencing of both the healthy and diseased heart. Results -After optimization, we were able to perform single-cell sequencing on adult cardiac tissue under both homeostatic conditions and after ischemic injury. Clustering analysis based on differential gene expression unveiled known and novel markers of all main cardiac cell types. Based on differential gene expression we were also able to identify multiple subpopulations within a certain cell type. Furthermore, applying single-cell sequencing on both the healthy and the injured heart indicated the presence of disease-specific cell subpopulations. As such, we identified cytoskeleton associated protein 4 ( Ckap4 ) as a novel marker for activated fibroblasts that positively correlates with known myofibroblast markers in both mouse and human cardiac tissue. Ckap4 inhibition in activated fibroblasts treated with TGFβ triggered a greater increase in the expression of genes related to activated fibroblasts compared to control, suggesting a role of Ckap4 in modulating fibroblast activation in the injured heart. Conclusions -Single-cell sequencing on both the healthy and diseased adult heart allows us to study transcriptomic differences between cardiac cells, as well as cell type-specific changes in gene expression during cardiac disease. This new approach provides a wealth of novel insights into molecular changes that underlie the cellular processes relevant for cardiac biology and pathophysiology. Applying this technology could lead to the discovery of new therapeutic targets relevant for heart disease.

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.

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

PubMed

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

2015-09-01

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

FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data.

PubMed

DeTomaso, David; Yosef, Nir

2016-08-23

A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualization. However, there are a variety of methods to achieve this result and once projected, it can be difficult to ascribe biological significance to the observed features. Additionally, when analyzing single-cell data, the relationship between cells can be obscured by technical confounders such as variable gene capture rates. To aid in the analysis and interpretation of single-cell RNA-Seq data, we have developed FastProject, a software tool which analyzes a gene expression matrix and produces a dynamic output report in which two-dimensional projections of the data can be explored. Annotated gene sets (referred to as gene 'signatures') are incorporated so that features in the projections can be understood in relation to the biological processes they might represent. FastProject provides a novel method of scoring each cell against a gene signature so as to minimize the effect of missed transcripts as well as a method to rank signature-projection pairings so that meaningful associations can be quickly identified. Additionally, FastProject is written with a modular architecture and designed to serve as a platform for incorporating and comparing new projection methods and gene selection algorithms. Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge.

An automated approach for single-cell tracking in epifluorescence microscopy applied to E. coli growth analysis on microfluidics biochips

NASA Astrophysics Data System (ADS)

Fetita, Catalin; Kirov, Boris; Jaramillo, Alfonso; Lefevre, Christophe

2012-03-01

With the accumulation of knowledge for the intimate molecular mechanisms governing the processes inside the living cells in the later years, the ability to characterize the performance of elementary genetic circuits and parts at the single-cell level is becoming of crucial importance. Biological science is arriving to the point where it can develop hypothesis for the action of each molecule participating in the biochemical reactions and need proper techniques to test those hypothesis. Microfluidics is emerging as the technology that combined with high-magnification microscopy will allow for the long-term single-cell level observation of bacterial physiology. In this study we design, build and characterize the gene dynamics of genetic circuits as one of the basic parts governing programmed cell behavior. We use E. coli as model organism and grow it in microfluidics chips, which we observe with epifluorescence microscopy. One of the most invaluable segments of this technology is the consequent image processing, since it allows for the automated analysis of vast amount of single-cell observation and the fast and easy derivation of conclusions based on that data. Specifically, we are interested in promoter activity as function of time. We expect it to be oscillatory and for that we use GFP (green fluorescent protein) as a reporter in our genetic circuits. In this paper, an automated framework for single-cell tracking in phase-contrast microscopy is developed, combining 2D segmentation of cell time frames and graph-based reconstruction of their spatiotemporal evolution with fast tracking of the associated fluorescence signal. The results obtained on the investigated biological database are presented and discussed.

Parallel single-cell analysis of active caspase-3/7 in apoptotic and non-apoptotic cells.

PubMed

Ledvina, Vojtěch; Janečková, Eva; Matalová, Eva; Klepárník, Karel

2017-01-01

Analysing the chemical content of individual cells has already been proven to reveal unique information on various biological processes. Single-cell analysis provides more accurate and reliable results for biology and medicine than analyses of extracts from cell populations, where a natural heterogeneity is averaged. To meet the requirements in the research of important biologically active molecules, such as caspases, we have developed a miniaturized device for simultaneous analyses of individual cells. A stainless steel body with a carousel holder enables high-sensitivity parallel detections in eight microvials. The holder is mounted in front of a photomultiplier tube with cooled photocathode working in photon counting mode. The detection of active caspase-3/7, central effector caspases in apoptosis, in single cells is based on the bioluminescence chemistry commercially available as Caspase-Glo ® 3/7 reagent developed by Promega. Individual cells were captured from a culture medium under microscope and transferred by micromanipulator into detection microvial filled with the reagent. As a result of testing, the limits of detection and quantification were determined to be 0.27/0.86 of active caspase-3/7 content in an average apoptotic cell and 0.46/2.92 for non-apoptotic cells. Application potential of this technology in laboratory diagnostics and related medical research is discussed. Graphical abstract Miniaturized device for simultaneous analyses of individual cells.

Aberration-free FTIR spectroscopic imaging of live cells in microfluidic devices.

PubMed

Chan, K L Andrew; Kazarian, Sergei G

2013-07-21

The label-free, non-destructive chemical analysis offered by FTIR spectroscopic imaging is a very attractive and potentially powerful tool for studies of live biological cells. FTIR imaging of live cells is a challenging task, due to the fact that cells are cultured in an aqueous environment. While the synchrotron facility has proven to be a valuable tool for FTIR microspectroscopic studies of single live cells, we have demonstrated that high quality infrared spectra of single live cells using an ordinary Globar source can also be obtained by adding a pair of lenses to a common transmission liquid cell. The lenses, when placed on the transmission cell window, form pseudo hemispheres which removes the refraction of light and hence improve the imaging and spectral quality of the obtained data. This study demonstrates that infrared spectra of single live cells can be obtained without the focus shifting effect at different wavenumbers, caused by the chromatic aberration. Spectra of the single cells have confirmed that the measured spectral region remains in focus across the whole range, while spectra of the single cells measured without the lenses have shown some erroneous features as a result of the shift of focus. It has also been demonstrated that the addition of lenses can be applied to the imaging of cells in microfabricated devices. We have shown that it was not possible to obtain a focused image of an isolated cell in a droplet of DPBS in oil unless the lenses are applied. The use of the approach described herein allows for well focused images of single cells in DPBS droplets to be obtained.

Application of advanced cytometric and molecular technologies to minimal residual disease monitoring

NASA Astrophysics Data System (ADS)

Leary, James F.; He, Feng; Reece, Lisa M.

2000-04-01

Minimal residual disease monitoring presents a number of theoretical and practical challenges. Recently it has been possible to meet some of these challenges by combining a number of new advanced biotechnologies. To monitor the number of residual tumor cells requires complex cocktails of molecular probes that collectively provide sensitivities of detection on the order of one residual tumor cell per million total cells. Ultra-high-speed, multi parameter flow cytometry is capable of analyzing cells at rates in excess of 100,000 cells/sec. Residual tumor selection marker cocktails can be optimized by use of receiver operating characteristic analysis. New data minimizing techniques when combined with multi variate statistical or neural network classifications of tumor cells can more accurately predict residual tumor cell frequencies. The combination of these techniques can, under at least some circumstances, detect frequencies of tumor cells as low as one cell in a million with an accuracy of over 98 percent correct classification. Detection of mutations in tumor suppressor genes requires insolation of these rare tumor cells and single-cell DNA sequencing. Rare residual tumor cells can be isolated at single cell level by high-resolution single-cell cell sorting. Molecular characterization of tumor suppressor gene mutations can be accomplished using a combination of single- cell polymerase chain reaction amplification of specific gene sequences followed by TA cloning techniques and DNA sequencing. Mutations as small as a single base pair in a tumor suppressor gene of a single sorted tumor cell have been detected using these methods. Using new amplification procedures and DNA micro arrays it should be possible to extend the capabilities shown in this paper to screening of multiple DNA mutations in tumor suppressor and other genes on small numbers of sorted metastatic tumor cells.

Planar cell polarity signaling coordinates oriented cell division and cell rearrangement in clonally expanding growth plate cartilage.

PubMed

Li, Yuwei; Li, Ang; Junge, Jason; Bronner, Marianne

2017-10-10

Both oriented cell divisions and cell rearrangements are critical for proper embryogenesis and organogenesis. However, little is known about how these two cellular events are integrated. Here we examine the linkage between these processes in chick limb cartilage. By combining retroviral-based multicolor clonal analysis with live imaging, the results show that single chondrocyte precursors can generate both single-column and multi-column clones through oriented division followed by cell rearrangements. Focusing on single column formation, we show that this stereotypical tissue architecture is established by a pivot-like process between sister cells. After mediolateral cell division, N-cadherin is enriched in the post-cleavage furrow; then one cell pivots around the other, resulting in stacking into a column. Perturbation analyses demonstrate that planar cell polarity signaling enables cells to pivot in the direction of limb elongation via this N-cadherin-mediated coupling. Our work provides new insights into the mechanisms generating appropriate tissue architecture of limb skeleton.

Planar cell polarity signaling coordinates oriented cell division and cell rearrangement in clonally expanding growth plate cartilage

PubMed Central

Li, Yuwei; Li, Ang; Junge, Jason

2017-01-01

Both oriented cell divisions and cell rearrangements are critical for proper embryogenesis and organogenesis. However, little is known about how these two cellular events are integrated. Here we examine the linkage between these processes in chick limb cartilage. By combining retroviral-based multicolor clonal analysis with live imaging, the results show that single chondrocyte precursors can generate both single-column and multi-column clones through oriented division followed by cell rearrangements. Focusing on single column formation, we show that this stereotypical tissue architecture is established by a pivot-like process between sister cells. After mediolateral cell division, N-cadherin is enriched in the post-cleavage furrow; then one cell pivots around the other, resulting in stacking into a column. Perturbation analyses demonstrate that planar cell polarity signaling enables cells to pivot in the direction of limb elongation via this N-cadherin-mediated coupling. Our work provides new insights into the mechanisms generating appropriate tissue architecture of limb skeleton. PMID:28994649

A streamlined workflow for single-cells genome-wide copy-number profiling by low-pass sequencing of LM-PCR whole-genome amplification products.

PubMed

Ferrarini, Alberto; Forcato, Claudio; Buson, Genny; Tononi, Paola; Del Monaco, Valentina; Terracciano, Mario; Bolognesi, Chiara; Fontana, Francesca; Medoro, Gianni; Neves, Rui; Möhlendick, Birte; Rihawi, Karim; Ardizzoni, Andrea; Sumanasuriya, Semini; Flohr, Penny; Lambros, Maryou; de Bono, Johann; Stoecklein, Nikolas H; Manaresi, Nicolò

2018-01-01

Chromosomal instability and associated chromosomal aberrations are hallmarks of cancer and play a critical role in disease progression and development of resistance to drugs. Single-cell genome analysis has gained interest in latest years as a source of biomarkers for targeted-therapy selection and drug resistance, and several methods have been developed to amplify the genomic DNA and to produce libraries suitable for Whole Genome Sequencing (WGS). However, most protocols require several enzymatic and cleanup steps, thus increasing the complexity and length of protocols, while robustness and speed are key factors for clinical applications. To tackle this issue, we developed a single-tube, single-step, streamlined protocol, exploiting ligation mediated PCR (LM-PCR) Whole Genome Amplification (WGA) method, for low-pass genome sequencing with the Ion Torrent™ platform and copy number alterations (CNAs) calling from single cells. The method was evaluated on single cells isolated from 6 aberrant cell lines of the NCI-H series. In addition, to demonstrate the feasibility of the workflow on clinical samples, we analyzed single circulating tumor cells (CTCs) and white blood cells (WBCs) isolated from the blood of patients affected by prostate cancer or lung adenocarcinoma. The results obtained show that the developed workflow generates data accurately representing whole genome absolute copy number profiles of single cell and allows alterations calling at resolutions down to 100 Kbp with as few as 200,000 reads. The presented data demonstrate the feasibility of the Ampli1™ WGA-based low-pass workflow for detection of CNAs in single tumor cells which would be of particular interest for genome-driven targeted therapy selection and for monitoring of disease progression.

Next-generation Sequencing (NGS) Analysis on Single Circulating Tumor Cells (CTCs) with No Need of Whole-genome Amplification (WGA).

PubMed

Palmirotta, Raffaele; Lovero, Domenica; Silvestris, Erica; Felici, Claudia; Quaresmini, Davide; Cafforio, Paola; Silvestris, Franco

2017-01-01

Isolation and genotyping of circulating tumor cells (CTCs) is gaining an increasing interest by clinical researchers in oncology not only for investigative purposes, but also for concrete application in clinical practice in terms of diagnosis, prognosis and decision treatment with targeted therapies. For the mutational analysis of single CTCs, the most advanced biotechnology methodology currently available includes the combination of whole genome amplification (WGA) followed by next-generation sequencing (NGS). However, the sequence of these molecular techniques is time-consuming and may also favor operator-dependent errors, related to the procedures themselves that, as in the case of the WGA technique, might affect downstream molecular analyses. A preliminary approach of molecular analysis by NGS on a model of CTCs without previous WGA procedural step was performed. We set-up an artificial sample obtained by spiking the SK-MEL-28 melanoma cell line in normal donor peripheral whole blood. Melanoma cells were first enriched using an AutoMACS® (Miltenyi) cell separator and then isolated as single and pooled CTCs by DEPArray™ System (Silicon Biosystems). NGS analysis, using the Ion AmpliSeq™ Cancer Hotspot Panel v2 (Life Technologies) with the Ion Torrent PGM™ system (Life Technologies), was performed on the SK-MEL-28 cell pellet, a single CTC previously processed with WGA and on 1, 2, 4 and 8 recovered CTCs without WGA pre-amplification. NGS directly carried out on CTCs without WGA showed the same mutations identified in SK-MEL-28 cell line pellet, with a considerable efficiency and avoiding the errors induced by the WGA procedure. We identified a cost-effective, time-saving and reliable methodological approach that could improve the analytical accuracy of the liquid biopsy and appears promising in studying CTCs from cancer patients for both research and clinical purposes. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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

FANTOM5 CAGE profiles of human and mouse samples.

PubMed

Noguchi, Shuhei; Arakawa, Takahiro; Fukuda, Shiro; Furuno, Masaaki; Hasegawa, Akira; Hori, Fumi; Ishikawa-Kato, Sachi; Kaida, Kaoru; Kaiho, Ai; Kanamori-Katayama, Mutsumi; Kawashima, Tsugumi; Kojima, Miki; Kubosaki, Atsutaka; Manabe, Ri-Ichiroh; Murata, Mitsuyoshi; Nagao-Sato, Sayaka; Nakazato, Kenichi; Ninomiya, Noriko; Nishiyori-Sueki, Hiromi; Noma, Shohei; Saijyo, Eri; Saka, Akiko; Sakai, Mizuho; Simon, Christophe; Suzuki, Naoko; Tagami, Michihira; Watanabe, Shoko; Yoshida, Shigehiro; Arner, Peter; Axton, Richard A; Babina, Magda; Baillie, J Kenneth; Barnett, Timothy C; Beckhouse, Anthony G; Blumenthal, Antje; Bodega, Beatrice; Bonetti, Alessandro; Briggs, James; Brombacher, Frank; Carlisle, Ailsa J; Clevers, Hans C; Davis, Carrie A; Detmar, Michael; Dohi, Taeko; Edge, Albert S B; Edinger, Matthias; Ehrlund, Anna; Ekwall, Karl; Endoh, Mitsuhiro; Enomoto, Hideki; Eslami, Afsaneh; Fagiolini, Michela; Fairbairn, Lynsey; Farach-Carson, Mary C; Faulkner, Geoffrey J; Ferrai, Carmelo; Fisher, Malcolm E; Forrester, Lesley M; Fujita, Rie; Furusawa, Jun-Ichi; Geijtenbeek, Teunis B; Gingeras, Thomas; Goldowitz, Daniel; Guhl, Sven; Guler, Reto; Gustincich, Stefano; Ha, Thomas J; Hamaguchi, Masahide; Hara, Mitsuko; Hasegawa, Yuki; Herlyn, Meenhard; Heutink, Peter; Hitchens, Kelly J; Hume, David A; Ikawa, Tomokatsu; Ishizu, Yuri; Kai, Chieko; Kawamoto, Hiroshi; Kawamura, Yuki I; Kempfle, Judith S; Kenna, Tony J; Kere, Juha; Khachigian, Levon M; Kitamura, Toshio; Klein, Sarah; Klinken, S Peter; Knox, Alan J; Kojima, Soichi; Koseki, Haruhiko; Koyasu, Shigeo; Lee, Weonju; Lennartsson, Andreas; Mackay-Sim, Alan; Mejhert, Niklas; Mizuno, Yosuke; Morikawa, Hiromasa; Morimoto, Mitsuru; Moro, Kazuyo; Morris, Kelly J; Motohashi, Hozumi; Mummery, Christine L; Nakachi, Yutaka; Nakahara, Fumio; Nakamura, Toshiyuki; Nakamura, Yukio; Nozaki, Tadasuke; Ogishima, Soichi; Ohkura, Naganari; Ohno, Hiroshi; Ohshima, Mitsuhiro; Okada-Hatakeyama, Mariko; Okazaki, Yasushi; Orlando, Valerio; Ovchinnikov, Dmitry A; Passier, Robert; Patrikakis, Margaret; Pombo, Ana; Pradhan-Bhatt, Swati; Qin, Xian-Yang; Rehli, Michael; Rizzu, Patrizia; Roy, Sugata; Sajantila, Antti; Sakaguchi, Shimon; Sato, Hiroki; Satoh, Hironori; Savvi, Suzana; Saxena, Alka; Schmidl, Christian; Schneider, Claudio; Schulze-Tanzil, Gundula G; Schwegmann, Anita; Sheng, Guojun; Shin, Jay W; Sugiyama, Daisuke; Sugiyama, Takaaki; Summers, Kim M; Takahashi, Naoko; Takai, Jun; Tanaka, Hiroshi; Tatsukawa, Hideki; Tomoiu, Andru; Toyoda, Hiroo; van de Wetering, Marc; van den Berg, Linda M; Verardo, Roberto; Vijayan, Dipti; Wells, Christine A; Winteringham, Louise N; Wolvetang, Ernst; Yamaguchi, Yoko; Yamamoto, Masayuki; Yanagi-Mizuochi, Chiyo; Yoneda, Misako; Yonekura, Yohei; Zhang, Peter G; Zucchelli, Silvia; Abugessaisa, Imad; Arner, Erik; Harshbarger, Jayson; Kondo, Atsushi; Lassmann, Timo; Lizio, Marina; Sahin, Serkan; Sengstag, Thierry; Severin, Jessica; Shimoji, Hisashi; Suzuki, Masanori; Suzuki, Harukazu; Kawai, Jun; Kondo, Naoto; Itoh, Masayoshi; Daub, Carsten O; Kasukawa, Takeya; Kawaji, Hideya; Carninci, Piero; Forrest, Alistair R R; Hayashizaki, Yoshihide

2017-08-29

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.

FANTOM5 CAGE profiles of human and mouse samples

PubMed Central

Noguchi, Shuhei; Arakawa, Takahiro; Fukuda, Shiro; Furuno, Masaaki; Hasegawa, Akira; Hori, Fumi; Ishikawa-Kato, Sachi; Kaida, Kaoru; Kaiho, Ai; Kanamori-Katayama, Mutsumi; Kawashima, Tsugumi; Kojima, Miki; Kubosaki, Atsutaka; Manabe, Ri-ichiroh; Murata, Mitsuyoshi; Nagao-Sato, Sayaka; Nakazato, Kenichi; Ninomiya, Noriko; Nishiyori-Sueki, Hiromi; Noma, Shohei; Saijyo, Eri; Saka, Akiko; Sakai, Mizuho; Simon, Christophe; Suzuki, Naoko; Tagami, Michihira; Watanabe, Shoko; Yoshida, Shigehiro; Arner, Peter; Axton, Richard A.; Babina, Magda; Baillie, J. Kenneth; Barnett, Timothy C.; Beckhouse, Anthony G.; Blumenthal, Antje; Bodega, Beatrice; Bonetti, Alessandro; Briggs, James; Brombacher, Frank; Carlisle, Ailsa J.; Clevers, Hans C.; Davis, Carrie A.; Detmar, Michael; Dohi, Taeko; Edge, Albert S.B.; Edinger, Matthias; Ehrlund, Anna; Ekwall, Karl; Endoh, Mitsuhiro; Enomoto, Hideki; Eslami, Afsaneh; Fagiolini, Michela; Fairbairn, Lynsey; Farach-Carson, Mary C.; Faulkner, Geoffrey J.; Ferrai, Carmelo; Fisher, Malcolm E.; Forrester, Lesley M.; Fujita, Rie; Furusawa, Jun-ichi; Geijtenbeek, Teunis B.; Gingeras, Thomas; Goldowitz, Daniel; Guhl, Sven; Guler, Reto; Gustincich, Stefano; Ha, Thomas J.; Hamaguchi, Masahide; Hara, Mitsuko; Hasegawa, Yuki; Herlyn, Meenhard; Heutink, Peter; Hitchens, Kelly J.; Hume, David A.; Ikawa, Tomokatsu; Ishizu, Yuri; Kai, Chieko; Kawamoto, Hiroshi; Kawamura, Yuki I.; Kempfle, Judith S.; Kenna, Tony J.; Kere, Juha; Khachigian, Levon M.; Kitamura, Toshio; Klein, Sarah; Klinken, S. Peter; Knox, Alan J.; Kojima, Soichi; Koseki, Haruhiko; Koyasu, Shigeo; Lee, Weonju; Lennartsson, Andreas; Mackay-sim, Alan; Mejhert, Niklas; Mizuno, Yosuke; Morikawa, Hiromasa; Morimoto, Mitsuru; Moro, Kazuyo; Morris, Kelly J.; Motohashi, Hozumi; Mummery, Christine L.; Nakachi, Yutaka; Nakahara, Fumio; Nakamura, Toshiyuki; Nakamura, Yukio; Nozaki, Tadasuke; Ogishima, Soichi; Ohkura, Naganari; Ohno, Hiroshi; Ohshima, Mitsuhiro; Okada-Hatakeyama, Mariko; Okazaki, Yasushi; Orlando, Valerio; Ovchinnikov, Dmitry A.; Passier, Robert; Patrikakis, Margaret; Pombo, Ana; Pradhan-Bhatt, Swati; Qin, Xian-Yang; Rehli, Michael; Rizzu, Patrizia; Roy, Sugata; Sajantila, Antti; Sakaguchi, Shimon; Sato, Hiroki; Satoh, Hironori; Savvi, Suzana; Saxena, Alka; Schmidl, Christian; Schneider, Claudio; Schulze-Tanzil, Gundula G.; Schwegmann, Anita; Sheng, Guojun; Shin, Jay W.; Sugiyama, Daisuke; Sugiyama, Takaaki; Summers, Kim M.; Takahashi, Naoko; Takai, Jun; Tanaka, Hiroshi; Tatsukawa, Hideki; Tomoiu, Andru; Toyoda, Hiroo; van de Wetering, Marc; van den Berg, Linda M.; Verardo, Roberto; Vijayan, Dipti; Wells, Christine A.; Winteringham, Louise N.; Wolvetang, Ernst; Yamaguchi, Yoko; Yamamoto, Masayuki; Yanagi-Mizuochi, Chiyo; Yoneda, Misako; Yonekura, Yohei; Zhang, Peter G.; Zucchelli, Silvia; Abugessaisa, Imad; Arner, Erik; Harshbarger, Jayson; Kondo, Atsushi; Lassmann, Timo; Lizio, Marina; Sahin, Serkan; Sengstag, Thierry; Severin, Jessica; Shimoji, Hisashi; Suzuki, Masanori; Suzuki, Harukazu; Kawai, Jun; Kondo, Naoto; Itoh, Masayoshi; Daub, Carsten O.; Kasukawa, Takeya; Kawaji, Hideya; Carninci, Piero; Forrest, Alistair R.R.; Hayashizaki, Yoshihide

2017-01-01

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities. PMID:28850106

Enrichment of Root Endophytic Bacteria from Populus deltoides and Single-Cell-Genomics Analysis

DOE PAGES

Utturkar, Sagar M.; Cude, W. Nathan; Robeson, Jr., Michael S.; ...

2016-07-15

Bacterial endophytes that colonize Populus trees contribute to nutrient acquisition, prime immunity responses, and directly or indirectly increase both above- and below-ground biomasses. Endophytes are embedded within plant material, so physical separation and isolation are difficult tasks. Application of culture-independent methods, such as metagenome or bacterial transcriptome sequencing, has been limited due to the predominance of DNA from the plant biomass. In this paper, we present a modified differential and density gradient centrifugation-based protocol for the separation of endophytic bacteria from Populus roots. This protocol achieved substantial reduction in contaminating plant DNA, allowed enrichment of endophytic bacteria away from themore » plant material, and enabled single-cell genomics analysis. Four single-cell genomes were selected for whole-genome amplification based on their rarity in the microbiome (potentially uncultured taxa) as well as their inferred abilities to form associations with plants. Bioinformatics analyses, including assembly, contamination removal, and completeness estimation, were performed to obtain single-amplified genomes (SAGs) of organisms from the phyla Armatimonadetes, Verrucomicrobia, and Planctomycetes, which were unrepresented in our previous cultivation efforts. Finally, comparative genomic analysis revealed unique characteristics of each SAG that could facilitate future cultivation efforts for these bacteria.« less

Displacement correlations between a single mesenchymal-like cell and its nucleus effectively link subcellular activities and motility in cell migration analysis

NASA Astrophysics Data System (ADS)

Lan, Tian; Cheng, Kai; Ren, Tina; Arce, Stephen Hugo; Tseng, Yiider

2016-09-01

Cell migration is an essential process in organism development and physiological maintenance. Although current methods permit accurate comparisons of the effects of molecular manipulations and drug applications on cell motility, effects of alterations in subcellular activities on motility cannot be fully elucidated from those methods. Here, we develop a strategy termed cell-nuclear (CN) correlation to parameterize represented dynamic subcellular activities and to quantify their contributions in mesenchymal-like migration. Based on the biophysical meaning of the CN correlation, we propose a cell migration potential index (CMPI) to measure cell motility. When the effectiveness of CMPI was evaluated with respect to one of the most popular cell migration analysis methods, Persistent Random Walk, we found that the cell motility estimates among six cell lines used in this study were highly consistent between these two approaches. Further evaluations indicated that CMPI can be determined using a shorter time period and smaller cell sample size, and it possesses excellent reliability and applicability, even in the presence of a wide range of noise, as might be generated from individual imaging acquisition systems. The novel approach outlined here introduces a robust strategy through an analysis of subcellular locomotion activities for single cell migration assessment.

Novel approaches in function-driven single-cell genomics.

PubMed

Doud, Devin F R; Woyke, Tanja

2017-07-01

Deeper sequencing and improved bioinformatics in conjunction with single-cell and metagenomic approaches continue to illuminate undercharacterized environmental microbial communities. This has propelled the 'who is there, and what might they be doing' paradigm to the uncultivated and has already radically changed the topology of the tree of life and provided key insights into the microbial contribution to biogeochemistry. While characterization of 'who' based on marker genes can describe a large fraction of the community, answering 'what are they doing' remains the elusive pinnacle for microbiology. Function-driven single-cell genomics provides a solution by using a function-based screen to subsample complex microbial communities in a targeted manner for the isolation and genome sequencing of single cells. This enables single-cell sequencing to be focused on cells with specific phenotypic or metabolic characteristics of interest. Recovered genomes are conclusively implicated for both encoding and exhibiting the feature of interest, improving downstream annotation and revealing activity levels within that environment. This emerging approach has already improved our understanding of microbial community functioning and facilitated the experimental analysis of uncharacterized gene product space. Here we provide a comprehensive review of strategies that have been applied for function-driven single-cell genomics and the future directions we envision. © FEMS 2017.

Novel approaches in function-driven single-cell genomics

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

Doud, Devin F. R.; Woyke, Tanja

Deeper sequencing and improved bioinformatics in conjunction with single-cell and metagenomic approaches continue to illuminate undercharacterized environmental microbial communities. This has propelled the 'who is there, and what might they be doing' paradigm to the uncultivated and has already radically changed the topology of the tree of life and provided key insights into the microbial contribution to biogeochemistry. While characterization of 'who' based on marker genes can describe a large fraction of the community, answering 'what are they doing' remains the elusive pinnacle for microbiology. Function-driven single-cell genomics provides a solution by using a function-based screen to subsample complex microbialmore » communities in a targeted manner for the isolation and genome sequencing of single cells. This enables single-cell sequencing to be focused on cells with specific phenotypic or metabolic characteristics of interest. Recovered genomes are conclusively implicated for both encoding and exhibiting the feature of interest, improving downstream annotation and revealing activity levels within that environment. This emerging approach has already improved our understanding of microbial community functioning and facilitated the experimental analysis of uncharacterized gene product space. Here we provide a comprehensive review of strategies that have been applied for function-driven single-cell genomics and the future directions we envision.« less

Novel approaches in function-driven single-cell genomics

DOE PAGES

Doud, Devin F. R.; Woyke, Tanja

2017-06-07

Deeper sequencing and improved bioinformatics in conjunction with single-cell and metagenomic approaches continue to illuminate undercharacterized environmental microbial communities. This has propelled the 'who is there, and what might they be doing' paradigm to the uncultivated and has already radically changed the topology of the tree of life and provided key insights into the microbial contribution to biogeochemistry. While characterization of 'who' based on marker genes can describe a large fraction of the community, answering 'what are they doing' remains the elusive pinnacle for microbiology. Function-driven single-cell genomics provides a solution by using a function-based screen to subsample complex microbialmore » communities in a targeted manner for the isolation and genome sequencing of single cells. This enables single-cell sequencing to be focused on cells with specific phenotypic or metabolic characteristics of interest. Recovered genomes are conclusively implicated for both encoding and exhibiting the feature of interest, improving downstream annotation and revealing activity levels within that environment. This emerging approach has already improved our understanding of microbial community functioning and facilitated the experimental analysis of uncharacterized gene product space. Here we provide a comprehensive review of strategies that have been applied for function-driven single-cell genomics and the future directions we envision.« less

Single-Cell in Situ RNA Analysis With Switchable Fluorescent Oligonucleotides.

PubMed

Xiao, Lu; Guo, Jia

2018-01-01

Comprehensive RNA analyses in individual cells in their native spatial contexts promise to transform our understanding of normal physiology and disease pathogenesis. Here we report a single-cell in situ RNA analysis approach using switchable fluorescent oligonucleotides (SFO). In this method, transcripts are first hybridized by pre-decoding oligonucleotides. These oligonucleotides subsequently recruit SFO to stain their corresponding RNA targets. After fluorescence imaging, all the SFO in the whole specimen are simultaneously removed by DNA strand displacement reactions. Through continuous cycles of target staining, fluorescence imaging, and SFO removal, a large number of different transcripts can be identified by unique fluorophore sequences and visualized at the optical resolution. To demonstrate the feasibility of this approach, we show that the hybridized SFO can be efficiently stripped by strand displacement reactions within 30 min. We also demonstrate that this SFO removal process maintains the integrity of the RNA targets and the pre-decoding oligonucleotides, and keeps them hybridized. Applying this approach, we show that transcripts can be restained in at least eight hybridization cycles with high analysis accuracy, which theoretically would enable the whole transcriptome to be quantified at the single molecule sensitivity in individual cells. This in situ RNA analysis technology will have wide applications in systems biology, molecular diagnosis, and targeted therapies.

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications.

PubMed

Haque, Ashraful; Engel, Jessica; Teichmann, Sarah A; Lönnberg, Tapio

2017-08-18

RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation.

Recent developments in microfluidics for cell studies.

PubMed

Xiong, Bin; Ren, Kangning; Shu, Yiwei; Chen, Yin; Shen, Bo; Wu, Hongkai

2014-08-20

As a technique for precisely manipulating fluid at the micrometer scale, the field of microfluidics has experienced an explosive growth over the past two decades, particularly owing to the advances in device design and fabrication. With the inherent advantages associated with its scale of operation, and its flexibility in being incorporated with other microscale techniques for manipulation and detection, microfluidics has become a major enabling technology, which has introduced new paradigms in various fields involving biological cells. A microfluidic device is able to realize functions that are not easily imaginable in conventional biological analysis, such as highly parallel, sophisticated high-throughput analysis, single-cell analysis in a well-defined manner, and tissue engineering with the capability of manipulation at the single-cell level. Major advancements in microfluidic device fabrication and the growing trend of implementing microfluidics in cell studies are presented, with a focus on biological research and clinical diagnostics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Label-free isolation and deposition of single bacterial cells from heterogeneous samples for clonal culturing

NASA Astrophysics Data System (ADS)

Riba, J.; Gleichmann, T.; Zimmermann, S.; Zengerle, R.; Koltay, P.

2016-09-01

The isolation and analysis of single prokaryotic cells down to 1 μm and less in size poses a special challenge and requires micro-engineered devices to handle volumes in the picoliter to nanoliter range. Here, an advanced Single-Cell Printer (SCP) was applied for automated and label-free isolation and deposition of bacterial cells encapsulated in 35 pl droplets by inkjet-like printing. To achieve this, dispenser chips to generate micro droplets have been fabricated with nozzles 20 μm in size. Further, the magnification of the optical system used for cell detection was increased. Redesign of the optical path allows for collision-free addressing of any flat substrate since no compartment protrudes below the nozzle of the dispenser chip anymore. The improved system allows for deterministic isolation of individual bacterial cells. A single-cell printing efficiency of 93% was obtained as shown by printing fluorescent labeled E. coli. A 96-well plate filled with growth medium is inoculated with single bacteria cells on average within about 8 min. Finally, individual bacterial cells from a heterogeneous sample of E. coli and E. faecalis were isolated for clonal culturing directly on agar plates in user-defined array geometry.

Single-cell analysis of pyroptosis dynamics reveals conserved GSDMD-mediated subcellular events that precede plasma membrane rupture.

PubMed

de Vasconcelos, Nathalia M; Van Opdenbosch, Nina; Van Gorp, Hanne; Parthoens, Eef; Lamkanfi, Mohamed

2018-04-17

Pyroptosis is rapidly emerging as a mechanism of anti-microbial host defense, and of extracellular release of the inflammasome-dependent cytokines interleukin (IL)-1β and IL-18, which contributes to autoinflammatory pathology. Caspases 1, 4, 5 and 11 trigger this regulated form of necrosis by cleaving the pyroptosis effector gasdermin D (GSDMD), causing its pore-forming amino-terminal domain to oligomerize and perforate the plasma membrane. However, the subcellular events that precede pyroptotic cell lysis are ill defined. In this study, we triggered primary macrophages to undergo pyroptosis from three inflammasome types and recorded their dynamics and morphology using high-resolution live-cell spinning disk confocal laser microscopy. Based on quantitative analysis of single-cell subcellular events, we propose a model of pyroptotic cell disintegration that is initiated by opening of GSDMD-dependent ion channels or pores that are more restrictive than recently proposed GSDMD pores, followed by osmotic cell swelling, commitment of mitochondria and other membrane-bound organelles prior to sudden rupture of the plasma membrane and full permeability to intracellular proteins. This study provides a dynamic framework for understanding cellular changes that occur during pyroptosis, and charts a chronological sequence of GSDMD-mediated subcellular events that define pyroptotic cell death at the single-cell level.

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.

Ultrasonic Scattering Measurements of a Live Single Cell at 86 MHz

PubMed Central

Lee, Changyang; Jung, Hayong; Lam, Kwok Ho; Yoon, Changhan; Shung, K. Kirk

2016-01-01

Cell separation and sorting techniques have been employed biomedical applications such as cancer diagnosis and cell gene expression analysis. The capability to accurately measure ultrasonic scattering properties from cells is crucial in making an ultrasonic cell sorter a reality if ultrasound scattering is to be used as the sensing mechanism as well. To assess the performance of sensing and identifying live single cells with high-frequency ultrasound, an 86-MHz lithium niobate press-focused single-element acoustic transducer was used in a high-frequency ultrasound scattering measurement system that was custom designed and developed for minimizing noise and allowing better mobility. Peak-to-peak echo amplitude, integrated backscatter (IB) coefficient, spectral parameters including spectral slope and intercept, and midband fit from spectral analysis of the backscattered echoes were measured and calculated from a live single cell of two different types on an agar surface: leukemia cells (K562 cells) and red blood cells (RBCs). The amplitudes of echo signals from K562 cells and RBCs were 48.25 ± 11.98 mVpp and 56.97 ± 7.53 mVpp, respectively. The IB coefficient was −89.39 ± 2.44 dB for K562 cells and −89.00 ± 1.19 dB for RBCs. The spectral slope and intercept were 0.30 ± 0.19 dB/MHz and −56.07 ± 17.17 dB, respectively, for K562 cells and 0.78 ± 0.092 dB/MHz and −98.18 ± 8.80 dB, respectively, for RBCs. Midband fits of K562 cells and RBCs were −31.02 ± 3.04 dB and −33.51 ± 1.55 dB, respectively. Acoustic cellular discrimination via these parameters was tested by Student’s t-test. Their values, except for the IB value, showed statistically significant difference (p < 0.001). This paper reports for the first time that ultrasonic scattering measurements can be made on a live single cell with a highly focused high-frequency ultrasound microbeam at 86 MHz. These results also suggest the feasibility of ultrasonic scattering as a sensing mechanism in the development of ultrasonic cell sorters. PMID:26559626

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.

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

PubMed

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

2015-06-01

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

Dynamic Analysis of Human Natural Killer Cell Response at Single-Cell Resolution in B-Cell Non-Hodgkin Lymphoma.

PubMed

Sarkar, Saheli; Sabhachandani, Pooja; Ravi, Dashnamoorthy; Potdar, Sayalee; Purvey, Sneha; Beheshti, Afshin; Evens, Andrew M; Konry, Tania

2017-01-01

Natural killer (NK) cells are phenotypically and functionally diverse lymphocytes that recognize and kill cancer cells. The susceptibility of target cancer cells to NK cell-mediated cytotoxicity depends on the strength and balance of regulatory (activating/inhibitory) ligands expressed on target cell surface. We performed gene expression arrays to determine patterns of NK cell ligands associated with B-cell non-Hodgkin lymphoma (b-NHL). Microarray analyses revealed significant upregulation of a multitude of NK-activating and costimulatory ligands across varied b-NHL cell lines and primary lymphoma cells, including ULBP1, CD72, CD48, and SLAMF6. To correlate genetic signatures with functional anti-lymphoma activity, we developed a dynamic and quantitative cytotoxicity assay in an integrated microfluidic droplet generation and docking array. Individual NK cells and target lymphoma cells were co-encapsulated in picoliter-volume droplets to facilitate monitoring of transient cellular interactions and NK cell effector outcomes at single-cell level. We identified significant variability in NK-lymphoma cell contact duration, frequency, and subsequent cytolysis. Death of lymphoma cells undergoing single contact with NK cells occurred faster than cells that made multiple short contacts. NK cells also killed target cells in droplets via contact-independent mechanisms that partially relied on calcium-dependent processes and perforin secretion, but not on cytokines (interferon-γ or tumor necrosis factor-α). We extended this technique to characterize functional heterogeneity in cytolysis of primary cells from b-NHL patients. Tumor cells from two diffuse large B-cell lymphoma patients showed similar contact durations with NK cells; primary Burkitt lymphoma cells made longer contacts and were lysed at later times. We also tested the cytotoxic efficacy of NK-92, a continuously growing NK cell line being investigated as an antitumor therapy, using our droplet-based bioassay. NK-92 cells were found to be more efficient in killing b-NHL cells compared with primary NK cells, requiring shorter contacts for faster killing activity. Taken together, our combined genetic and microfluidic analysis demonstrate b-NHL cell sensitivity to NK cell-based cytotoxicity, which was associated with significant heterogeneity in the dynamic interaction at single-cell level.

Space-based solar power conversion and delivery systems study. Volume 4: Energy conversion systems studies

NASA Technical Reports Server (NTRS)

1977-01-01

Solar cells and optical configurations for the SSPS were examined. In this task, three specific solar cell materials were examined: single crystal silicon, single crystal gallium arsenide, and polycrystalline cadmium sulfide. The comparison of the three different cells on the basis of a subsystem parametric cost per kW of SSPS-generated power at the terrestrial utility interface showed that gallium arsenide was the most promising solar cell material at high concentration ratios. The most promising solar cell material with no concentration, was dependent upon the particular combination of parameters representing cost, mass and performance that were chosen to represent each cell in this deterministic comparative analysis. The potential for mass production, based on the projections of the present state-of-the-art would tend to favor cadmium sulfide in lieu of single crystal silicon or gallium arsenide solar cells.

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

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

DOE PAGES

Nourbakhsh-Rey, Mehrnoush; Libault, Marc

2016-01-01

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

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

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

Nourbakhsh-Rey, Mehrnoush; Libault, Marc

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

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

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.

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.

Optofluidics for handling and analysis of single living cells

NASA Astrophysics Data System (ADS)

Perozziello, Gerardo; Candeloro, Patrizio; Coluccio, Maria Laura; Di Fabrizio, Enzo

2017-11-01

Optofluidics is a field with important applications in areas such as biotechnology, chemical synthesis and analytical chemistry. Optofluidic devices combine optical elements into microfluidic devices in ways that increase portability and sensitivity of analysis for diagnostic or screening purposes .In fact in these devices fluids give fine adaptability, mobility and accessibility to nanoscale photonic devices which otherwise could not be realized using conventional devices. This review describes several cases inwhich optical or microfluidic approaches are used to trap single cells in proximity of integrated optical sensor for being analysed.

Solid oxide fuel cell anode degradation by the effect of hydrogen chloride in stack and single cell environments

NASA Astrophysics Data System (ADS)

Madi, Hossein; Lanzini, Andrea; Papurello, Davide; Diethelm, Stefan; Ludwig, Christian; Santarelli, Massimo; Van herle, Jan

2016-09-01

The poisoning effect by hydrogen chloride (HCl) on state-of-the-art Ni anode-supported solid oxide fuel cells (SOFCs) at 750 °C is evaluated in either hydrogen or syngas fuel. Experiments are performed on single cells and short stacks and HCl concentration in the fuel gas is increased from 1 ppm(v) up to 1000 ppm(v) at different current densities. Characterization methods such as cell voltage monitoring vs. time and electrochemical impedance response analysis (distribution of relaxation times (DRT), equivalent electrical circuit) are used to identify the prevailing degradation mechanism. Single cell experiments revealed that the poisoning is more severe when feeding with hydrogen than with syngas. Performance loss is attributed to the effects of HCl adsorption onto nickel surfaces, which lowered the catalyst activity. Interestingly, in syngas HCl does not affect stack performance even at concentrations up to 500 ppm(v), even when causing severe corrosion of the anode exhaust pipe. Furthermore, post-test analysis suggests that chlorine is present on the nickel particles in the form of adsorbed chlorine, rather than forming a secondary phase of nickel chlorine.

Trick or TREAT: A Scary-Good New Approach for Single-Molecule mRNA Decay Analysis.

PubMed

Russo, Joseph; Wilusz, Jeffrey

2017-11-02

In this issue of Molecular Cell, Horvathova et al. (2017) have developed a powerful approach to single-molecule assessment of RNA decay in living cells by exploiting the ability of flavivirus RNA structural elements to trap XRN1 decay intermediates in dual-labeled reporter constructs. Copyright © 2017 Elsevier Inc. All rights reserved.

Automated analysis of siRNA screens of cells infected by hepatitis C and dengue viruses based on immunofluorescence microscopy images

NASA Astrophysics Data System (ADS)

Matula, Petr; Kumar, Anil; Wörz, Ilka; Harder, Nathalie; Erfle, Holger; Bartenschlager, Ralf; Eils, Roland; Rohr, Karl

2008-03-01

We present an image analysis approach as part of a high-throughput microscopy siRNA-based screening system using cell arrays for the identification of cellular genes involved in hepatitis C and dengue virus replication. Our approach comprises: cell nucleus segmentation, quantification of virus replication level in the neighborhood of segmented cell nuclei, localization of regions with transfected cells, cell classification by infection status, and quality assessment of an experiment and single images. In particular, we propose a novel approach for the localization of regions of transfected cells within cell array images, which combines model-based circle fitting and grid fitting. By this scheme we integrate information from single cell array images and knowledge from the complete cell arrays. The approach is fully automatic and has been successfully applied to a large number of cell array images from screening experiments. The experimental results show a good agreement with the expected behaviour of positive as well as negative controls and encourage the application to screens from further high-throughput experiments.

Highly sensitive SERS analysis of the cyclic Arg-Gly-Asp peptide ligands of cells using nanogap antennas.

PubMed

Portela, Alejandro; Yano, Taka-Aki; Santschi, Christian; Martin, Olivier J F; Tabata, Hitoshi; Hara, Masahiko

2017-02-01

The cyclic RGD (cRGD) peptide ligands of cells have become widely used for treating several cancers. We report a highly sensitive analysis of c(RGDfC) using surface enhanced Raman spectroscopy (SERS) using single dimer nanogap antennas in aqueous environment. Good agreement between characteristic peaks of the SERS and the Raman spectra of bulk c(RGDfC) with its peptide's constituents were observed. The exhibited blinking of the SERS spectra and synchronization of intensity fluctuations, suggest that the SERS spectra acquired from single dimer nanogap antennas was dominated by the spectrum of single to a few molecules. SERS spectra of c(RGDfC) could be used to detect at the nanoscale, the cells' transmembrane proteins binding to its ligand. SERS of cyclic RGD on nanogap antenna. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification and Single-Cell Functional Characterization of an Endodermally Biased Pluripotent Substate in Human Embryonic Stem Cells.

PubMed

Allison, Thomas F; Smith, Andrew J H; Anastassiadis, Konstantinos; Sloane-Stanley, Jackie; Biga, Veronica; Stavish, Dylan; Hackland, James; Sabri, Shan; Langerman, Justin; Jones, Mark; Plath, Kathrin; Coca, Daniel; Barbaric, Ivana; Gokhale, Paul; Andrews, Peter W

2018-05-09

Human embryonic stem cells (hESCs) display substantial heterogeneity in gene expression, implying the existence of discrete substates within the stem cell compartment. To determine whether these substates impact fate decisions of hESCs we used a GFP reporter line to investigate the properties of fractions of putative undifferentiated cells defined by their differential expression of the endoderm transcription factor, GATA6, together with the hESC surface marker, SSEA3. By single-cell cloning, we confirmed that substates characterized by expression of GATA6 and SSEA3 include pluripotent stem cells capable of long-term self-renewal. When clonal stem cell colonies were formed from GATA6-positive and GATA6-negative cells, more of those derived from GATA6-positive cells contained spontaneously differentiated endoderm cells than similar colonies derived from the GATA6-negative cells. We characterized these discrete cellular states using single-cell transcriptomic analysis, identifying a potential role for SOX17 in the establishment of the endoderm-biased stem cell state. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.