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.

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.

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

PubMed

Schmidt, Felix; Efferth, Thomas

2016-06-16

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

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 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.

Ultraaccurate genome sequencing and haplotyping of single human cells.

PubMed

Chu, Wai Keung; Edge, Peter; Lee, Ho Suk; Bansal, Vikas; Bafna, Vineet; Huang, Xiaohua; Zhang, Kun

2017-11-21

Accurate detection of variants and long-range haplotypes in genomes of single human cells remains very challenging. Common approaches require extensive in vitro amplification of genomes of individual cells using DNA polymerases and high-throughput short-read DNA sequencing. These approaches have two notable drawbacks. First, polymerase replication errors could generate tens of thousands of false-positive calls per genome. Second, relatively short sequence reads contain little to no haplotype information. Here we report a method, which is dubbed SISSOR (single-stranded sequencing using microfluidic reactors), for accurate single-cell genome sequencing and haplotyping. A microfluidic processor is used to separate the Watson and Crick strands of the double-stranded chromosomal DNA in a single cell and to randomly partition megabase-size DNA strands into multiple nanoliter compartments for amplification and construction of barcoded libraries for sequencing. The separation and partitioning of large single-stranded DNA fragments of the homologous chromosome pairs allows for the independent sequencing of each of the complementary and homologous strands. This enables the assembly of long haplotypes and reduction of sequence errors by using the redundant sequence information and haplotype-based error removal. We demonstrated the ability to sequence single-cell genomes with error rates as low as 10 -8 and average 500-kb-long DNA fragments that can be assembled into haplotype contigs with N50 greater than 7 Mb. The performance could be further improved with more uniform amplification and more accurate sequence alignment. The ability to obtain accurate genome sequences and haplotype information from single cells will enable applications of genome sequencing for diverse clinical needs. Copyright © 2017 the Author(s). Published by PNAS.

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

PubMed

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

2014-09-01

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

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.

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.

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.

Modeling genome coverage in single-cell sequencing

PubMed Central

Daley, Timothy; Smith, Andrew D.

2014-01-01

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

Exploring viral infection using single-cell sequencing.

PubMed

Rato, Sylvie; Golumbeanu, Monica; Telenti, Amalio; Ciuffi, Angela

2017-07-15

Single-cell sequencing (SCS) has emerged as a valuable tool to study cellular heterogeneity in diverse fields, including virology. By studying the viral and cellular genome and/or transcriptome, the dynamics of viral infection can be investigated at single cell level. Most studies have explored the impact of cell-to-cell variation on the viral life cycle from the point of view of the virus, by analyzing viral sequences, and from the point of view of the cell, mainly by analyzing the cellular host transcriptome. In this review, we will focus on recent studies that use single-cell sequencing to explore viral diversity and cell variability in response to viral replication. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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.

OncoNEM: inferring tumor evolution from single-cell sequencing data.

PubMed

Ross, Edith M; Markowetz, Florian

2016-04-15

Single-cell sequencing promises a high-resolution view of genetic heterogeneity and clonal evolution in cancer. However, methods to infer tumor evolution from single-cell sequencing data lag behind methods developed for bulk-sequencing data. Here, we present OncoNEM, a probabilistic method for inferring intra-tumor evolutionary lineage trees from somatic single nucleotide variants of single cells. OncoNEM identifies homogeneous cellular subpopulations and infers their genotypes as well as a tree describing their evolutionary relationships. In simulation studies, we assess OncoNEM's robustness and benchmark its performance against competing methods. Finally, we show its applicability in case studies of muscle-invasive bladder cancer and essential thrombocythemia.

Single-cell full-length total RNA sequencing uncovers dynamics of recursive splicing and enhancer RNAs.

PubMed

Hayashi, Tetsutaro; Ozaki, Haruka; Sasagawa, Yohei; Umeda, Mana; Danno, Hiroki; Nikaido, Itoshi

2018-02-12

Total RNA sequencing has been used to reveal poly(A) and non-poly(A) RNA expression, RNA processing and enhancer activity. To date, no method for full-length total RNA sequencing of single cells has been developed despite the potential of this technology for single-cell biology. Here we describe random displacement amplification sequencing (RamDA-seq), the first full-length total RNA-sequencing method for single cells. Compared with other methods, RamDA-seq shows high sensitivity to non-poly(A) RNA and near-complete full-length transcript coverage. Using RamDA-seq with differentiation time course samples of mouse embryonic stem cells, we reveal hundreds of dynamically regulated non-poly(A) transcripts, including histone transcripts and long noncoding RNA Neat1. Moreover, RamDA-seq profiles recursive splicing in >300-kb introns. RamDA-seq also detects enhancer RNAs and their cell type-specific activity in single cells. Taken together, we demonstrate that RamDA-seq could help investigate the dynamics of gene expression, RNA-processing events and transcriptional regulation in single cells.

Single cell RNA sequencing of stem cell-derived retinal ganglion cells.

PubMed

Daniszewski, Maciej; Senabouth, Anne; Nguyen, Quan H; Crombie, Duncan E; Lukowski, Samuel W; Kulkarni, Tejal; Sluch, Valentin M; Jabbari, Jafar S; Chamling, Xitiz; Zack, Donald J; Pébay, Alice; Powell, Joseph E; Hewitt, Alex W

2018-02-13

We used single cell sequencing technology to characterize the transcriptomes of 1,174 human embryonic stem cell-derived retinal ganglion cells (RGCs) at the single cell level. The human embryonic stem cell line BRN3B-mCherry (A81-H7), was differentiated to RGCs using a guided differentiation approach. Cells were harvested at day 36 and prepared for single cell RNA sequencing. Our data indicates the presence of three distinct subpopulations of cells, with various degrees of maturity. One cluster of 288 cells showed increased expression of genes involved in axon guidance together with semaphorin interactions, cell-extracellular matrix interactions and ECM proteoglycans, suggestive of a more mature RGC phenotype.

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.

Interpretable dimensionality reduction of single cell transcriptome data with deep generative models.

PubMed

Ding, Jiarui; Condon, Anne; Shah, Sohrab P

2018-05-21

Single-cell RNA-sequencing has great potential to discover cell types, identify cell states, trace development lineages, and reconstruct the spatial organization of cells. However, dimension reduction to interpret structure in single-cell sequencing data remains a challenge. Existing algorithms are either not able to uncover the clustering structures in the data or lose global information such as groups of clusters that are close to each other. We present a robust statistical model, scvis, to capture and visualize the low-dimensional structures in single-cell gene expression data. Simulation results demonstrate that low-dimensional representations learned by scvis preserve both the local and global neighbor structures in the data. In addition, scvis is robust to the number of data points and learns a probabilistic parametric mapping function to add new data points to an existing embedding. We then use scvis to analyze four single-cell RNA-sequencing datasets, exemplifying interpretable two-dimensional representations of the high-dimensional single-cell RNA-sequencing data.

Genomic Insights into Geothermal Spring Community Members using a 16S Agnostic Single-Cell Approach

NASA Astrophysics Data System (ADS)

Bowers, R. M.

2016-12-01

INSTUTIONS (ALL): DOE Joint Genome Institute, Walnut Creek, CA USA. Bigelow Laboratory for Ocean Sciences, East Boothbay, ME USA. Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada. ABSTRACT BODY: With recent advances in DNA sequencing, rapid and affordable screening of single-cell genomes has become a reality. Single-cell sequencing is a multi-step process that takes advantage of any number of single-cell sorting techniques, whole genome amplification (WGA), and 16S rRNA gene based PCR screening to identify the microbes of interest prior to shotgun sequencing. However, the 16S PCR based screening step is costly and may lead to unanticipated losses of microbial diversity, as cells that do not produce a clean 16S amplicon are typically omitted from downstream shotgun sequencing. While many of the sorted cells that fail the 16S PCR step likely originate from poor quality amplified DNA, some of the cells with good WGA kinetics may instead represent bacteria or archaea with 16S genes that fail to amplify due to primer mis-matches or the presence of intervening sequences. Using cell material from Dewar Creek, a hot spring in British Columbia, we sequenced all sorted cells with good WGA kinetics irrespective of their 16S amplification success. We show that this high-throughput approach to single-cell sequencing (i) can reduce the overall cost of single-cell genome production, and (ii). may lead to the discovery of previously unknown branches on the microbial tree of life.

Sequencing thousands of single-cell genomes with combinatorial indexing.

PubMed

Vitak, Sarah A; Torkenczy, Kristof A; Rosenkrantz, Jimi L; Fields, Andrew J; Christiansen, Lena; Wong, Melissa H; Carbone, Lucia; Steemers, Frank J; Adey, Andrew

2017-03-01

Single-cell genome sequencing has proven valuable for the detection of somatic variation, particularly in the context of tumor evolution. Current technologies suffer from high library construction costs, which restrict the number of cells that can be assessed and thus impose limitations on the ability to measure heterogeneity within a tissue. Here, we present single-cell combinatorial indexed sequencing (SCI-seq) as a means of simultaneously generating thousands of low-pass single-cell libraries for detection of somatic copy-number variants. We constructed libraries for 16,698 single cells from a combination of cultured cell lines, primate frontal cortex tissue and two human adenocarcinomas, and obtained a detailed assessment of subclonal variation within a pancreatic tumor.

Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH.

PubMed

Torre, Eduardo; Dueck, Hannah; Shaffer, Sydney; Gospocic, Janko; Gupte, Rohit; Bonasio, Roberto; Kim, Junhyong; Murray, John; Raj, Arjun

2018-02-28

Although single-cell RNA sequencing can reliably detect large-scale transcriptional programs, it is unclear whether it accurately captures the behavior of individual genes, especially those that express only in rare cells. Here, we use single-molecule RNA fluorescence in situ hybridization as a gold standard to assess trade-offs in single-cell RNA-sequencing data for detecting rare cell expression variability. We quantified the gene expression distribution for 26 genes that range from ubiquitous to rarely expressed and found that the correspondence between estimates across platforms improved with both transcriptome coverage and increased number of cells analyzed. Further, by characterizing the trade-off between transcriptome coverage and number of cells analyzed, we show that when the number of genes required to answer a given biological question is small, then greater transcriptome coverage is more important than analyzing large numbers of cells. More generally, our report provides guidelines for selecting quality thresholds for single-cell RNA-sequencing experiments aimed at rare cell analyses. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-11-01

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

Microfluidic 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.

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

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

Nanoliter reactors improve multiple displacement amplification of genomes from single cells.

PubMed

Marcy, Yann; Ishoey, Thomas; Lasken, Roger S; Stockwell, Timothy B; Walenz, Brian P; Halpern, Aaron L; Beeson, Karen Y; Goldberg, Susanne M D; Quake, Stephen R

2007-09-01

Since only a small fraction of environmental bacteria are amenable to laboratory culture, there is great interest in genomic sequencing directly from single cells. Sufficient DNA for sequencing can be obtained from one cell by the Multiple Displacement Amplification (MDA) method, thereby eliminating the need to develop culture methods. Here we used a microfluidic device to isolate individual Escherichia coli and amplify genomic DNA by MDA in 60-nl reactions. Our results confirm a report that reduced MDA reaction volume lowers nonspecific synthesis that can result from contaminant DNA templates and unfavourable interaction between primers. The quality of the genome amplification was assessed by qPCR and compared favourably to single-cell amplifications performed in standard 50-microl volumes. Amplification bias was greatly reduced in nanoliter volumes, thereby providing a more even representation of all sequences. Single-cell amplicons from both microliter and nanoliter volumes provided high-quality sequence data by high-throughput pyrosequencing, thereby demonstrating a straightforward route to sequencing genomes from single cells.

Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing.

PubMed

Kim, Charissa; Gao, Ruli; Sei, Emi; Brandt, Rachel; Hartman, Johan; Hatschek, Thomas; Crosetto, Nicola; Foukakis, Theodoros; Navin, Nicholas E

2018-05-03

Triple-negative breast cancer (TNBC) is an aggressive subtype that frequently develops resistance to chemotherapy. An unresolved question is whether resistance is caused by the selection of rare pre-existing clones or alternatively through the acquisition of new genomic aberrations. To investigate this question, we applied single-cell DNA and RNA sequencing in addition to bulk exome sequencing to profile longitudinal samples from 20 TNBC patients during neoadjuvant chemotherapy (NAC). Deep-exome sequencing identified 10 patients in which NAC led to clonal extinction and 10 patients in which clones persisted after treatment. In 8 patients, we performed a more detailed study using single-cell DNA sequencing to analyze 900 cells and single-cell RNA sequencing to analyze 6,862 cells. Our data showed that resistant genotypes were pre-existing and adaptively selected by NAC, while transcriptional profiles were acquired by reprogramming in response to chemotherapy in TNBC patients. Copyright © 2018 Elsevier Inc. All rights reserved.

Multi-region and single-cell sequencing reveal variable genomic heterogeneity in rectal cancer.

PubMed

Liu, Mingshan; Liu, Yang; Di, Jiabo; Su, Zhe; Yang, Hong; Jiang, Beihai; Wang, Zaozao; Zhuang, Meng; Bai, Fan; Su, Xiangqian

2017-11-23

Colorectal cancer is a heterogeneous group of malignancies with complex molecular subtypes. While colon cancer has been widely investigated, studies on rectal cancer are very limited. Here, we performed multi-region whole-exome sequencing and single-cell whole-genome sequencing to examine the genomic intratumor heterogeneity (ITH) of rectal tumors. We sequenced nine tumor regions and 88 single cells from two rectal cancer patients with tumors of the same molecular classification and characterized their mutation profiles and somatic copy number alterations (SCNAs) at the multi-region and the single-cell levels. A variable extent of genomic heterogeneity was observed between the two patients, and the degree of ITH increased when analyzed on the single-cell level. We found that major SCNAs were early events in cancer development and inherited steadily. Single-cell sequencing revealed mutations and SCNAs which were hidden in bulk sequencing. In summary, we studied the ITH of rectal cancer at regional and single-cell resolution and demonstrated that variable heterogeneity existed in two patients. The mutational scenarios and SCNA profiles of two patients with treatment naïve from the same molecular subtype are quite different. Our results suggest each tumor possesses its own architecture, which may result in different diagnosis, prognosis, and drug responses. Remarkable ITH exists in the two patients we have studied, providing a preliminary impression of ITH in rectal cancer.

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.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2015-05-01

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

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.

Application of single-cell sequencing in human cancer.

PubMed

Rantalainen, Mattias

2017-11-02

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

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.

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.

A cost effective 5΄ selective single cell transcriptome profiling approach with improved UMI design

PubMed Central

Arguel, Marie-Jeanne; LeBrigand, Kevin; Paquet, Agnès; Ruiz García, Sandra; Zaragosi, Laure-Emmanuelle; Waldmann, Rainer

2017-01-01

Abstract Single cell RNA sequencing approaches are instrumental in studies of cell-to-cell variability. 5΄ selective transcriptome profiling approaches allow simultaneous definition of the transcription start size and have advantages over 3΄ selective approaches which just provide internal sequences close to the 3΄ end. The only currently existing 5΄ selective approach requires costly and labor intensive fragmentation and cell barcoding after cDNA amplification. We developed an optimized 5΄ selective workflow where all the cell indexing is done prior to fragmentation. With our protocol, cell indexing can be performed in the Fluidigm C1 microfluidic device, resulting in a significant reduction of cost and labor. We also designed optimized unique molecular identifiers that show less sequence bias and vulnerability towards sequencing errors resulting in an improved accuracy of molecule counting. We provide comprehensive experimental workflows for Illumina and Ion Proton sequencers that allow single cell sequencing in a cost range comparable to qPCR assays. PMID:27940562

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

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.

Unravelling biology and shifting paradigms in cancer with single-cell sequencing.

PubMed

Baslan, Timour; Hicks, James

2017-08-24

The fundamental operative unit of a cancer is the genetically and epigenetically innovative single cell. Whether proliferating or quiescent, in the primary tumour mass or disseminated elsewhere, single cells govern the parameters that dictate all facets of the biology of cancer. Thus, single-cell analyses provide the ultimate level of resolution in our quest for a fundamental understanding of this disease. Historically, this quest has been hampered by technological shortcomings. In this Opinion article, we argue that the rapidly evolving field of single-cell sequencing has unshackled the cancer research community of these shortcomings. From furthering an elemental understanding of intra-tumoural genetic heterogeneity and cancer genome evolution to illuminating the governing principles of disease relapse and metastasis, we posit that single-cell sequencing promises to unravel the biology of all facets of this disease.

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 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.

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

PubMed Central

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

2017-01-01

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

Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates.

PubMed

Leung, Kaston; Klaus, Anders; Lin, Bill K; Laks, Emma; Biele, Justina; Lai, Daniel; Bashashati, Ali; Huang, Yi-Fei; Aniba, Radhouane; Moksa, Michelle; Steif, Adi; Mes-Masson, Anne-Marie; Hirst, Martin; Shah, Sohrab P; Aparicio, Samuel; Hansen, Carl L

2016-07-26

The genomes of large numbers of single cells must be sequenced to further understanding of the biological significance of genomic heterogeneity in complex systems. Whole genome amplification (WGA) of single cells is generally the first step in such studies, but is prone to nonuniformity that can compromise genomic measurement accuracy. Despite recent advances, robust performance in high-throughput single-cell WGA remains elusive. Here, we introduce droplet multiple displacement amplification (MDA), a method that uses commercially available liquid dispensing to perform high-throughput single-cell MDA in nanoliter volumes. The performance of droplet MDA is characterized using a large dataset of 129 normal diploid cells, and is shown to exceed previously reported single-cell WGA methods in amplification uniformity, genome coverage, and/or robustness. We achieve up to 80% coverage of a single-cell genome at 5× sequencing depth, and demonstrate excellent single-nucleotide variant (SNV) detection using targeted sequencing of droplet MDA product to achieve a median allelic dropout of 15%, and using whole genome sequencing to achieve false and true positive rates of 9.66 × 10(-6) and 68.8%, respectively, in a G1-phase cell. We further show that droplet MDA allows for the detection of copy number variants (CNVs) as small as 30 kb in single cells of an ovarian cancer cell line and as small as 9 Mb in two high-grade serous ovarian cancer samples using only 0.02× depth. Droplet MDA provides an accessible and scalable method for performing robust and accurate CNV and SNV measurements on large numbers of single cells.

Miniaturization Technologies for Efficient Single-Cell Library Preparation for Next-Generation Sequencing.

PubMed

Mora-Castilla, Sergio; To, Cuong; Vaezeslami, Soheila; Morey, Robert; Srinivasan, Srimeenakshi; Dumdie, Jennifer N; Cook-Andersen, Heidi; Jenkins, Joby; Laurent, Louise C

2016-08-01

As the cost of next-generation sequencing has decreased, library preparation costs have become a more significant proportion of the total cost, especially for high-throughput applications such as single-cell RNA profiling. Here, we have applied novel technologies to scale down reaction volumes for library preparation. Our system consisted of in vitro differentiated human embryonic stem cells representing two stages of pancreatic differentiation, for which we prepared multiple biological and technical replicates. We used the Fluidigm (San Francisco, CA) C1 single-cell Autoprep System for single-cell complementary DNA (cDNA) generation and an enzyme-based tagmentation system (Nextera XT; Illumina, San Diego, CA) with a nanoliter liquid handler (mosquito HTS; TTP Labtech, Royston, UK) for library preparation, reducing the reaction volume down to 2 µL and using as little as 20 pg of input cDNA. The resulting sequencing data were bioinformatically analyzed and correlated among the different library reaction volumes. Our results showed that decreasing the reaction volume did not interfere with the quality or the reproducibility of the sequencing data, and the transcriptional data from the scaled-down libraries allowed us to distinguish between single cells. Thus, we have developed a process to enable efficient and cost-effective high-throughput single-cell transcriptome sequencing. © 2016 Society for Laboratory Automation and Screening.

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

SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing

PubMed Central

Bankevich, Anton; Nurk, Sergey; Antipov, Dmitry; Gurevich, Alexey A.; Dvorkin, Mikhail; Kulikov, Alexander S.; Lesin, Valery M.; Nikolenko, Sergey I.; Pham, Son; Prjibelski, Andrey D.; Pyshkin, Alexey V.; Sirotkin, Alexander V.; Vyahhi, Nikolay; Tesler, Glenn; Pevzner, Pavel A.

2012-01-01

Abstract The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V−SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online (http://bioinf.spbau.ru/spades). It is distributed as open source software. PMID:22506599

Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads.

PubMed

Sasagawa, Yohei; Danno, Hiroki; Takada, Hitomi; Ebisawa, Masashi; Tanaka, Kaori; Hayashi, Tetsutaro; Kurisaki, Akira; Nikaido, Itoshi

2018-03-09

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30-50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

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

One Bacterial Cell, One Complete Genome

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

Woyke, Tanja; Tighe, Damon; Mavrommatis, Konstantinos

2010-04-26

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

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.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding.

PubMed

Shahi, Payam; Kim, Samuel C; Haliburton, John R; Gartner, Zev J; Abate, Adam R

2017-03-14

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

NASA Astrophysics Data System (ADS)

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-03-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

PubMed Central

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-01-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing. PMID:28290550

Single-Cell Genomic Analysis in Plants

PubMed Central

Hu, Haifei; Scheben, Armin; Edwards, David

2018-01-01

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

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.

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.

Highly sensitive detection of mutations in CHO cell recombinant DNA using multi-parallel single molecule real-time DNA sequencing.

PubMed

Cartwright, Joseph F; Anderson, Karin; Longworth, Joseph; Lobb, Philip; James, David C

2018-06-01

High-fidelity replication of biologic-encoding recombinant DNA sequences by engineered mammalian cell cultures is an essential pre-requisite for the development of stable cell lines for the production of biotherapeutics. However, immortalized mammalian cells characteristically exhibit an increased point mutation frequency compared to mammalian cells in vivo, both across their genomes and at specific loci (hotspots). Thus unforeseen mutations in recombinant DNA sequences can arise and be maintained within producer cell populations. These may affect both the stability of recombinant gene expression and give rise to protein sequence variants with variable bioactivity and immunogenicity. Rigorous quantitative assessment of recombinant DNA integrity should therefore form part of the cell line development process and be an essential quality assurance metric for instances where synthetic/multi-component assemblies are utilized to engineer mammalian cells, such as the assessment of recombinant DNA fidelity or the mutability of single-site integration target loci. Based on Pacific Biosciences (Menlo Park, CA) single molecule real-time (SMRT™) circular consensus sequencing (CCS) technology we developed a rDNA sequence analysis tool to process the multi-parallel sequencing of ∼40,000 single recombinant DNA molecules. After statistical filtering of raw sequencing data, we show that this analytical method is capable of detecting single point mutations in rDNA to a minimum single mutation frequency of 0.0042% (<1/24,000 bases). Using a stable CHO transfectant pool harboring a randomly integrated 5 kB plasmid construct encoding GFP we found that 28% of recombinant plasmid copies contained at least one low frequency (<0.3%) point mutation. These mutations were predominantly found in GC base pairs (85%) and that there was no positional bias in mutation across the plasmid sequence. There was no discernable difference between the mutation frequencies of coding and non-coding DNA. The putative ratio of non-synonymous and synonymous changes within the open reading frames (ORFs) in the plasmid sequence indicates that natural selection does not impact upon the prevalence of these mutations. Here we have demonstrated the abundance of mutations that fall outside of the reported range of detection of next generation sequencing (NGS) and second generation sequencing (SGS) platforms, providing a methodology capable of being utilized in cell line development platforms to identify the fidelity of recombinant genes throughout the production process. © 2018 Wiley Periodicals, Inc.

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells.

PubMed

Rizzetto, Simone; Eltahla, Auda A; Lin, Peijie; Bull, Rowena; Lloyd, Andrew R; Ho, Joshua W K; Venturi, Vanessa; Luciani, Fabio

2017-10-06

Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% - 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

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.

Distilled single-cell genome sequencing and de novo assembly for sparse microbial communities.

PubMed

Taghavi, Zeinab; Movahedi, Narjes S; Draghici, Sorin; Chitsaz, Hamidreza

2013-10-01

Identification of every single genome present in a microbial sample is an important and challenging task with crucial applications. It is challenging because there are typically millions of cells in a microbial sample, the vast majority of which elude cultivation. The most accurate method to date is exhaustive single-cell sequencing using multiple displacement amplification, which is simply intractable for a large number of cells. However, there is hope for breaking this barrier, as the number of different cell types with distinct genome sequences is usually much smaller than the number of cells. Here, we present a novel divide and conquer method to sequence and de novo assemble all distinct genomes present in a microbial sample with a sequencing cost and computational complexity proportional to the number of genome types, rather than the number of cells. The method is implemented in a tool called Squeezambler. We evaluated Squeezambler on simulated data. The proposed divide and conquer method successfully reduces the cost of sequencing in comparison with the naïve exhaustive approach. Squeezambler and datasets are available at http://compbio.cs.wayne.edu/software/squeezambler/.

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.

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.

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

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

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

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.

Single-cell mRNA cytometry via sequence-specific nanoparticle clustering and trapping

NASA Astrophysics Data System (ADS)

Labib, Mahmoud; Mohamadi, Reza M.; Poudineh, Mahla; Ahmed, Sharif U.; Ivanov, Ivaylo; Huang, Ching-Lung; Moosavi, Maral; Sargent, Edward H.; Kelley, Shana O.

2018-05-01

Cell-to-cell variation in gene expression creates a need for techniques that can characterize expression at the level of individual cells. This is particularly true for rare circulating tumour cells, in which subtyping and drug resistance are of intense interest. Here we describe a method for cell analysis—single-cell mRNA cytometry—that enables the isolation of rare cells from whole blood as a function of target mRNA sequences. This approach uses two classes of magnetic particles that are labelled to selectively hybridize with different regions of the target mRNA. Hybridization leads to the formation of large magnetic clusters that remain localized within the cells of interest, thereby enabling the cells to be magnetically separated. Targeting specific intracellular mRNAs enablescirculating tumour cells to be distinguished from normal haematopoietic cells. No polymerase chain reaction amplification is required to determine RNA expression levels and genotype at the single-cell level, and minimal cell manipulation is required. To demonstrate this approach we use single-cell mRNA cytometry to detect clinically important sequences in prostate cancer specimens.

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

PubMed Central

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

2016-01-01

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

Single-cell sequencing and tumorigenesis: improved understanding of tumor evolution and metastasis.

PubMed

Ellsworth, Darrell L; Blackburn, Heather L; Shriver, Craig D; Rabizadeh, Shahrooz; Soon-Shiong, Patrick; Ellsworth, Rachel E

2017-12-01

Extensive genomic and transcriptomic heterogeneity in human cancer often negatively impacts treatment efficacy and survival, thus posing a significant ongoing challenge for modern treatment regimens. State-of-the-art DNA- and RNA-sequencing methods now provide high-resolution genomic and gene expression portraits of individual cells, facilitating the study of complex molecular heterogeneity in cancer. Important developments in single-cell sequencing (SCS) technologies over the past 5 years provide numerous advantages over traditional sequencing methods for understanding the complexity of carcinogenesis, but significant hurdles must be overcome before SCS can be clinically useful. In this review, we: (1) highlight current methodologies and recent technological advances for isolating single cells, single-cell whole-genome and whole-transcriptome amplification using minute amounts of nucleic acids, and SCS, (2) summarize research investigating molecular heterogeneity at the genomic and transcriptomic levels and how this heterogeneity affects clonal evolution and metastasis, and (3) discuss the promise for integrating SCS in the clinical care arena for improved patient care.

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

Single-Cell-Based Platform for Copy Number Variation Profiling through Digital Counting of Amplified Genomic DNA Fragments.

PubMed

Li, Chunmei; Yu, Zhilong; Fu, Yusi; Pang, Yuhong; Huang, Yanyi

2017-04-26

We develop a novel single-cell-based platform through digital counting of amplified genomic DNA fragments, named multifraction amplification (mfA), to detect the copy number variations (CNVs) in a single cell. Amplification is required to acquire genomic information from a single cell, while introducing unavoidable bias. Unlike prevalent methods that directly infer CNV profiles from the pattern of sequencing depth, our mfA platform denatures and separates the DNA molecules from a single cell into multiple fractions of a reaction mix before amplification. By examining the sequencing result of each fraction for a specific fragment and applying a segment-merge maximum likelihood algorithm to the calculation of copy number, we digitize the sequencing-depth-based CNV identification and thus provide a method that is less sensitive to the amplification bias. In this paper, we demonstrate a mfA platform through multiple displacement amplification (MDA) chemistry. When performing the mfA platform, the noise of MDA is reduced; therefore, the resolution of single-cell CNV identification can be improved to 100 kb. We can also determine the genomic region free of allelic drop-out with mfA platform, which is impossible for conventional single-cell amplification methods.

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.

Introduction to Single-Cell RNA Sequencing.

PubMed

Olsen, Thale Kristin; Baryawno, Ninib

2018-04-01

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

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

PubMed

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

2016-09-01

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

Sequencing Single Cell Microbial Genomes with Microfluidic Amplifications Tools (MICW - Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Quake, Steve

2018-02-02

Stanford University's Steve Quake on "Sequencing Single Cell Microbial Genomes with Microfluidic Amplification Tools" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Sequencing Single Cell Microbial Genomes with Microfluidic Amplifications Tools (MICW - Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

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

Quake, Steve

2011-10-12

Stanford University's Steve Quake on "Sequencing Single Cell Microbial Genomes with Microfluidic Amplification Tools" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Pooling across cells to normalize single-cell RNA sequencing data with many zero counts.

PubMed

Lun, Aaron T L; Bach, Karsten; Marioni, John C

2016-04-27

Normalization of single-cell RNA sequencing data is necessary to eliminate cell-specific biases prior to downstream analyses. However, this is not straightforward for noisy single-cell data where many counts are zero. We present a novel approach where expression values are summed across pools of cells, and the summed values are used for normalization. Pool-based size factors are then deconvolved to yield cell-based factors. Our deconvolution approach outperforms existing methods for accurate normalization of cell-specific biases in simulated data. Similar behavior is observed in real data, where deconvolution improves the relevance of results of downstream analyses.

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 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 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.

Single Cell Analysis: From Technology to Biology and Medicine.

PubMed

Pan, Xinghua

2014-01-01

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

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.

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

The heterogeneity of human CD127(+) innate lymphoid cells revealed by single-cell RNA sequencing.

PubMed

Björklund, Åsa K; Forkel, Marianne; Picelli, Simone; Konya, Viktoria; Theorell, Jakob; Friberg, Danielle; Sandberg, Rickard; Mjösberg, Jenny

2016-04-01

Innate lymphoid cells (ILCs) are increasingly appreciated as important participants in homeostasis and inflammation. Substantial plasticity and heterogeneity among ILC populations have been reported. Here we have delineated the heterogeneity of human ILCs through single-cell RNA sequencing of several hundreds of individual tonsil CD127(+) ILCs and natural killer (NK) cells. Unbiased transcriptional clustering revealed four distinct populations, corresponding to ILC1 cells, ILC2 cells, ILC3 cells and NK cells, with their respective transcriptomes recapitulating known as well as unknown transcriptional profiles. The single-cell resolution additionally divulged three transcriptionally and functionally diverse subpopulations of ILC3 cells. Our systematic comparison of single-cell transcriptional variation within and between ILC populations provides new insight into ILC biology during homeostasis, with additional implications for dysregulation of the immune system.

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.

Clonal evolution in breast cancer revealed by single nucleus genome sequencing.

PubMed

Wang, Yong; Waters, Jill; Leung, Marco L; Unruh, Anna; Roh, Whijae; Shi, Xiuqing; Chen, Ken; Scheet, Paul; Vattathil, Selina; Liang, Han; Multani, Asha; Zhang, Hong; Zhao, Rui; Michor, Franziska; Meric-Bernstam, Funda; Navin, Nicholas E

2014-08-14

Sequencing studies of breast tumour cohorts have identified many prevalent mutations, but provide limited insight into the genomic diversity within tumours. Here we developed a whole-genome and exome single cell sequencing approach called nuc-seq that uses G2/M nuclei to achieve 91% mean coverage breadth. We applied this method to sequence single normal and tumour nuclei from an oestrogen-receptor-positive (ER(+)) breast cancer and a triple-negative ductal carcinoma. In parallel, we performed single nuclei copy number profiling. Our data show that aneuploid rearrangements occurred early in tumour evolution and remained highly stable as the tumour masses clonally expanded. In contrast, point mutations evolved gradually, generating extensive clonal diversity. Using targeted single-molecule sequencing, many of the diverse mutations were shown to occur at low frequencies (<10%) in the tumour mass. Using mathematical modelling we found that the triple-negative tumour cells had an increased mutation rate (13.3×), whereas the ER(+) tumour cells did not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer.

The determination of complete human mitochondrial DNA sequences in single cells: implications for the study of somatic mitochondrial DNA point mutations

PubMed Central

Taylor, Robert W.; Taylor, Geoffrey A.; Durham, Steve E.; Turnbull, Douglass M.

2001-01-01

Studies of single cells have previously shown intracellular clonal expansion of mitochondrial DNA (mtDNA) mutations to levels that can cause a focal cytochrome c oxidase (COX) defect. Whilst techniques are available to study mtDNA rearrangements at the level of the single cell, recent interest has focused on the possible role of somatic mtDNA point mutations in ageing, neurodegenerative disease and cancer. We have therefore developed a method that permits the reliable determination of the entire mtDNA sequence from single cells without amplifying contaminating, nuclear-embedded pseudogenes. Sequencing and PCR–RFLP analyses of individual COX-negative muscle fibres from a patient with a previously described heteroplasmic COX II (T7587C) mutation indicate that mutant loads as low as 30% can be reliably detected by sequencing. This technique will be particularly useful in identifying the mtDNA mutational spectra in age-related COX-negative cells and will increase our understanding of the pathogenetic mechanisms by which they occur. PMID:11470889

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

PubMed

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

2017-11-01

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

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

PubMed

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

2017-01-23

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

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

PubMed Central

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

2017-01-01

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

Massively parallel nanowell-based single-cell gene expression profiling.

PubMed

Goldstein, Leonard D; Chen, Ying-Jiun Jasmine; Dunne, Jude; Mir, Alain; Hubschle, Hermann; Guillory, Joseph; Yuan, Wenlin; Zhang, Jingli; Stinson, Jeremy; Jaiswal, Bijay; Pahuja, Kanika Bajaj; Mann, Ishminder; Schaal, Thomas; Chan, Leo; Anandakrishnan, Sangeetha; Lin, Chun-Wah; Espinoza, Patricio; Husain, Syed; Shapiro, Harris; Swaminathan, Karthikeyan; Wei, Sherry; Srinivasan, Maithreyan; Seshagiri, Somasekar; Modrusan, Zora

2017-07-07

Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5,184-nanowell-containing microchip to capture ~1,300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing.

PubMed

Zheng, Chunhong; Zheng, Liangtao; Yoo, Jae-Kwang; Guo, Huahu; Zhang, Yuanyuan; Guo, Xinyi; Kang, Boxi; Hu, Ruozhen; Huang, Julie Y; Zhang, Qiming; Liu, Zhouzerui; Dong, Minghui; Hu, Xueda; Ouyang, Wenjun; Peng, Jirun; Zhang, Zemin

2017-06-15

Systematic interrogation of tumor-infiltrating lymphocytes is key to the development of immunotherapies and the prediction of their clinical responses in cancers. Here, we perform deep single-cell RNA sequencing on 5,063 single T cells isolated from peripheral blood, tumor, and adjacent normal tissues from six hepatocellular carcinoma patients. The transcriptional profiles of these individual cells, coupled with assembled T cell receptor (TCR) sequences, enable us to identify 11 T cell subsets based on their molecular and functional properties and delineate their developmental trajectory. Specific subsets such as exhausted CD8 + T cells and Tregs are preferentially enriched and potentially clonally expanded in hepatocellular carcinoma (HCC), and we identified signature genes for each subset. One of the genes, layilin, is upregulated on activated CD8 + T cells and Tregs and represses the CD8 + T cell functions in vitro. This compendium of transcriptome data provides valuable insights and a rich resource for understanding the immune landscape in cancers. Copyright © 2017 Elsevier Inc. All rights reserved.

Single-cell paired-end genome sequencing reveals structural variation per cell cycle

PubMed Central

Voet, Thierry; Kumar, Parveen; Van Loo, Peter; Cooke, Susanna L.; Marshall, John; Lin, Meng-Lay; Zamani Esteki, Masoud; Van der Aa, Niels; Mateiu, Ligia; McBride, David J.; Bignell, Graham R.; McLaren, Stuart; Teague, Jon; Butler, Adam; Raine, Keiran; Stebbings, Lucy A.; Quail, Michael A.; D’Hooghe, Thomas; Moreau, Yves; Futreal, P. Andrew; Stratton, Michael R.; Vermeesch, Joris R.; Campbell, Peter J.

2013-01-01

The nature and pace of genome mutation is largely unknown. Because standard methods sequence DNA from populations of cells, the genetic composition of individual cells is lost, de novo mutations in cells are concealed within the bulk signal and per cell cycle mutation rates and mechanisms remain elusive. Although single-cell genome analyses could resolve these problems, such analyses are error-prone because of whole-genome amplification (WGA) artefacts and are limited in the types of DNA mutation that can be discerned. We developed methods for paired-end sequence analysis of single-cell WGA products that enable (i) detecting multiple classes of DNA mutation, (ii) distinguishing DNA copy number changes from allelic WGA-amplification artefacts by the discovery of matching aberrantly mapping read pairs among the surfeit of paired-end WGA and mapping artefacts and (iii) delineating the break points and architecture of structural variants. By applying the methods, we capture DNA copy number changes acquired over one cell cycle in breast cancer cells and in blastomeres derived from a human zygote after in vitro fertilization. Furthermore, we were able to discover and fine-map a heritable inter-chromosomal rearrangement t(1;16)(p36;p12) by sequencing a single blastomere. The methods will expedite applications in basic genome research and provide a stepping stone to novel approaches for clinical genetic diagnosis. PMID:23630320

Strategies for the acquisition of transcriptional and epigenetic information in single cells.

PubMed

Li, Guang; Dzilic, Elda; Flores, Nick; Shieh, Alice; Wu, Sean M

2017-03-01

As the basic unit of living organisms, each single cell has unique molecular signatures and functions. Our ability to uncover the transcriptional and epigenetic signature of single cells has been hampered by the lack of tools to explore this area of research. The advent of microfluidic single cell technology along with single cell genome-wide DNA amplification methods had greatly improved our understanding of the expression variation in single cells. Transcriptional expression profile by multiplex qPCR or genome-wide RNA sequencing has enabled us to examine genes expression in single cells in different tissues. With the new tools, the identification of new cellular heterogeneity, novel marker genes, unique subpopulations, and spatial locations of each single cell can be acquired successfully. Epigenetic modifications for each single cell can also be obtained via similar methods. Based on single cell genome sequencing, single cell epigenetic information including histone modifications, DNA methylation, and chromatin accessibility have been explored and provided valuable insights regarding gene regulation and disease prognosis. In this article, we review the development of strategies to obtain single cell transcriptional and epigenetic data. Furthermore, we discuss ways in which single cell studies may help to provide greater understanding of the mechanisms of basic cardiovascular biology that will eventually lead to improvement in our ability to diagnose disease and develop new therapies.

Single-Cell Whole-Genome Amplification and Sequencing: Methodology and Applications.

PubMed

Huang, Lei; Ma, Fei; Chapman, Alec; Lu, Sijia; Xie, Xiaoliang Sunney

2015-01-01

We present a survey of single-cell whole-genome amplification (WGA) methods, including degenerate oligonucleotide-primed polymerase chain reaction (DOP-PCR), multiple displacement amplification (MDA), and multiple annealing and looping-based amplification cycles (MALBAC). The key parameters to characterize the performance of these methods are defined, including genome coverage, uniformity, reproducibility, unmappable rates, chimera rates, allele dropout rates, false positive rates for calling single-nucleotide variations, and ability to call copy-number variations. Using these parameters, we compare five commercial WGA kits by performing deep sequencing of multiple single cells. We also discuss several major applications of single-cell genomics, including studies of whole-genome de novo mutation rates, the early evolution of cancer genomes, circulating tumor cells (CTCs), meiotic recombination of germ cells, preimplantation genetic diagnosis (PGD), and preimplantation genomic screening (PGS) for in vitro-fertilized embryos.

Advances in understanding tumour evolution through single-cell sequencing.

PubMed

Kuipers, Jack; Jahn, Katharina; Beerenwinkel, Niko

2017-04-01

The mutational heterogeneity observed within tumours poses additional challenges to the development of effective cancer treatments. A thorough understanding of a tumour's subclonal composition and its mutational history is essential to open up the design of treatments tailored to individual patients. Comparative studies on a large number of tumours permit the identification of mutational patterns which may refine forecasts of cancer progression, response to treatment and metastatic potential. The composition of tumours is shaped by evolutionary processes. Recent advances in next-generation sequencing offer the possibility to analyse the evolutionary history and accompanying heterogeneity of tumours at an unprecedented resolution, by sequencing single cells. New computational challenges arise when moving from bulk to single-cell sequencing data, leading to the development of novel modelling frameworks. In this review, we present the state of the art methods for understanding the phylogeny encoded in bulk or single-cell sequencing data, and highlight future directions for developing more comprehensive and informative pictures of tumour evolution. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A highly sensitive and accurate gene expression analysis by sequencing ("bead-seq") for a single cell.

PubMed

Matsunaga, Hiroko; Goto, Mari; Arikawa, Koji; Shirai, Masataka; Tsunoda, Hiroyuki; Huang, Huan; Kambara, Hideki

2015-02-15

Analyses of gene expressions in single cells are important for understanding detailed biological phenomena. Here, a highly sensitive and accurate method by sequencing (called "bead-seq") to obtain a whole gene expression profile for a single cell is proposed. A key feature of the method is to use a complementary DNA (cDNA) library on magnetic beads, which enables adding washing steps to remove residual reagents in a sample preparation process. By adding the washing steps, the next steps can be carried out under the optimal conditions without losing cDNAs. Error sources were carefully evaluated to conclude that the first several steps were the key steps. It is demonstrated that bead-seq is superior to the conventional methods for single-cell gene expression analyses in terms of reproducibility, quantitative accuracy, and biases caused during sample preparation and sequencing processes. Copyright © 2014 Elsevier Inc. All rights reserved.

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

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

Single-Cell Semiconductor Sequencing

PubMed Central

Kohn, Andrea B.; Moroz, Tatiana P.; Barnes, Jeffrey P.; Netherton, Mandy; Moroz, Leonid L.

2014-01-01

RNA-seq or transcriptome analysis of individual cells and small-cell populations is essential for virtually any biomedical field. It is especially critical for developmental, aging, and cancer biology as well as neuroscience where the enormous heterogeneity of cells present a significant methodological and conceptual challenge. Here we present two methods that allow for fast and cost-efficient transcriptome sequencing from ultra-small amounts of tissue or even from individual cells using semiconductor sequencing technology (Ion Torrent, Life Technologies). The first method is a reduced representation sequencing which maximizes capture of RNAs and preserves transcripts’ directionality. The second, a template-switch protocol, is designed for small mammalian neurons. Both protocols, from cell/tissue isolation to final sequence data, take up to 4 days. The efficiency of these protocols has been validated with single hippocampal neurons and various invertebrate tissues including individually identified neurons within a simpler memory-forming circuit of Aplysia californica and early (1-, 2-, 4-, 8-cells) embryonic and developmental stages from basal metazoans. PMID:23929110

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

PubMed

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

2018-01-11

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells.

PubMed

Guo, Fan; Li, Lin; Li, Jingyun; Wu, Xinglong; Hu, Boqiang; Zhu, Ping; Wen, Lu; Tang, Fuchou

2017-08-01

Single-cell epigenome sequencing techniques have recently been developed. However, the combination of different layers of epigenome sequencing in an individual cell has not yet been achieved. Here, we developed a single-cell multi-omics sequencing technology (single-cell COOL-seq) that can analyze the chromatin state/nucleosome positioning, DNA methylation, copy number variation and ploidy simultaneously from the same individual mammalian cell. We used this method to analyze the reprogramming of the chromatin state and DNA methylation in mouse preimplantation embryos. We found that within < 12 h of fertilization, each individual cell undergoes global genome demethylation together with the rapid and global reprogramming of both maternal and paternal genomes to a highly opened chromatin state. This was followed by decreased openness after the late zygote stage. Furthermore, from the late zygote to the 4-cell stage, the residual DNA methylation is preferentially preserved on intergenic regions of the paternal alleles and intragenic regions of maternal alleles in each individual blastomere. However, chromatin accessibility is similar between paternal and maternal alleles in each individual cell from the late zygote to the blastocyst stage. The binding motifs of several pluripotency regulators are enriched at distal nucleosome depleted regions from as early as the 2-cell stage. This indicates that the cis-regulatory elements of such target genes have been primed to an open state from the 2-cell stage onward, long before pluripotency is eventually established in the ICM of the blastocyst. Genes may be classified into homogeneously open, homogeneously closed and divergent states based on the chromatin accessibility of their promoter regions among individual cells. This can be traced to step-wise transitions during preimplantation development. Our study offers the first single-cell and parental allele-specific analysis of the genome-scale chromatin state and DNA methylation dynamics at single-base resolution in early mouse embryos and provides new insights into the heterogeneous yet highly ordered features of epigenomic reprogramming during this process.

Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells

PubMed Central

Guo, Fan; Li, Lin; Li, Jingyun; Wu, Xinglong; Hu, Boqiang; Zhu, Ping; Wen, Lu; Tang, Fuchou

2017-01-01

Single-cell epigenome sequencing techniques have recently been developed. However, the combination of different layers of epigenome sequencing in an individual cell has not yet been achieved. Here, we developed a single-cell multi-omics sequencing technology (single-cell COOL-seq) that can analyze the chromatin state/nucleosome positioning, DNA methylation, copy number variation and ploidy simultaneously from the same individual mammalian cell. We used this method to analyze the reprogramming of the chromatin state and DNA methylation in mouse preimplantation embryos. We found that within < 12 h of fertilization, each individual cell undergoes global genome demethylation together with the rapid and global reprogramming of both maternal and paternal genomes to a highly opened chromatin state. This was followed by decreased openness after the late zygote stage. Furthermore, from the late zygote to the 4-cell stage, the residual DNA methylation is preferentially preserved on intergenic regions of the paternal alleles and intragenic regions of maternal alleles in each individual blastomere. However, chromatin accessibility is similar between paternal and maternal alleles in each individual cell from the late zygote to the blastocyst stage. The binding motifs of several pluripotency regulators are enriched at distal nucleosome depleted regions from as early as the 2-cell stage. This indicates that the cis-regulatory elements of such target genes have been primed to an open state from the 2-cell stage onward, long before pluripotency is eventually established in the ICM of the blastocyst. Genes may be classified into homogeneously open, homogeneously closed and divergent states based on the chromatin accessibility of their promoter regions among individual cells. This can be traced to step-wise transitions during preimplantation development. Our study offers the first single-cell and parental allele-specific analysis of the genome-scale chromatin state and DNA methylation dynamics at single-base resolution in early mouse embryos and provides new insights into the heterogeneous yet highly ordered features of epigenomic reprogramming during this process. PMID:28621329

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

PubMed

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

2017-12-15

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

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

PubMed

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

2012-01-01

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

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.

Genome-wide base-resolution mapping of DNA methylation in single cells using single-cell bisulfite sequencing (scBS-seq).

PubMed

Clark, Stephen J; Smallwood, Sébastien A; Lee, Heather J; Krueger, Felix; Reik, Wolf; Kelsey, Gavin

2017-03-01

DNA methylation (DNAme) is an important epigenetic mark in diverse species. Our current understanding of DNAme is based on measurements from bulk cell samples, which obscures intercellular differences and prevents analyses of rare cell types. Thus, the ability to measure DNAme in single cells has the potential to make important contributions to the understanding of several key biological processes, such as embryonic development, disease progression and aging. We have recently reported a method for generating genome-wide DNAme maps from single cells, using single-cell bisulfite sequencing (scBS-seq), allowing the quantitative measurement of DNAme at up to 50% of CpG dinucleotides throughout the mouse genome. Here we present a detailed protocol for scBS-seq that includes our most recent developments to optimize recovery of CpGs, mapping efficiency and success rate; reduce hands-on time; and increase sample throughput with the option of using an automated liquid handler. We provide step-by-step instructions for each stage of the method, comprising cell lysis and bisulfite (BS) conversion, preamplification and adaptor tagging, library amplification, sequencing and, lastly, alignment and methylation calling. An individual with relevant molecular biology expertise can complete library preparation within 3 d. Subsequent computational steps require 1-3 d for someone with bioinformatics expertise.

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.

Beta-Poisson model for single-cell RNA-seq data analyses.

PubMed

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

2016-07-15

Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

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.

Mitochondrial DNA mutations in single human blood cells.

PubMed

Yao, Yong-Gang; Kajigaya, Sachiko; Young, Neal S

2015-09-01

Determination mitochondrial DNA (mtDNA) sequences from extremely small amounts of DNA extracted from tissue of limited amounts and/or degraded samples is frequently employed in medical, forensic, and anthropologic studies. Polymerase chain reaction (PCR) amplification followed by DNA cloning is a routine method, especially to examine heteroplasmy of mtDNA mutations. In this review, we compare the mtDNA mutation patterns detected by three different sequencing strategies. Cloning and sequencing methods that are based on PCR amplification of DNA extracted from either single cells or pooled cells yield a high frequency of mutations, partly due to the artifacts introduced by PCR and/or the DNA cloning process. Direct sequencing of PCR product which has been amplified from DNA in individual cells is able to detect the low levels of mtDNA mutations present within a cell. We further summarize the findings in our recent studies that utilized this single cell method to assay mtDNA mutation patterns in different human blood cells. Our data show that many somatic mutations observed in the end-stage differentiated cells are found in hematopoietic stem cells (HSCs) and progenitors within the CD34(+) cell compartment. Accumulation of mtDNA variations in the individual CD34+ cells is affected by both aging and family genetic background. Granulocytes harbor higher numbers of mutations compared with the other cells, such as CD34(+) cells and lymphocytes. Serial assessment of mtDNA mutations in a population of single CD34(+) cells obtained from the same donor over time suggests stability of some somatic mutations. CD34(+) cell clones from a donor marked by specific mtDNA somatic mutations can be found in the recipient after transplantation. The significance of these findings is discussed in terms of the lineage tracing of HSCs, aging effect on accumulation of mtDNA mutations and the usage of mtDNA sequence in forensic identification. Copyright © 2015 Elsevier B.V. All rights reserved.

Systematic assessment of the performance of whole-genome amplification for SNP/CNV detection and β-thalassemia genotyping.

PubMed

He, Fei; Zhou, Wanjun; Cai, Ren; Yan, Tizhen; Xu, Xiangmin

2018-04-01

In this study, we aimed to assess the performance of two whole-genome amplification methods, multiple displacement amplification (MDA), and multiple annealing and looping-based amplification cycle (MALBAC), for β-thalassemia genotyping and single-nucleotide polymorphism (SNP)/copy-number variant (CNV) detection using two DNA sequencing assays. We collected peripheral blood, cell lines, and discarded embryos, and carried out MALBAC and MDA on single-cell and five-cell samples. We detected and statistically analyzed differences in the amplification efficiency, positive predictive value, sensitivity, allele dropout (ADO) rate, SNPs, and CV values between the two methods. Through Sanger sequencing at the single-cell and five-cell levels, we showed that both the amplification rate and ADO rate of MDA were better than those using MALBAC, and the sensitivity and positive predictive value obtained from MDA were higher than those from MALBAC for β-thalassemia genotyping. Using next-generation sequencing (NGS) at the single-cell level, we confirmed that MDA has better properties than MALBAC for SNP detection. However, MALBAC was more stable and homogeneous than MDA using low-depth NGS at the single-cell level for CNV detection. We conclude that MALBAC is the better option for CNV detection, while MDA is better suited for SNV detection.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2016-06-23

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

Fast measurement of proton exchange membrane fuel cell impedance based on pseudo-random binary sequence perturbation signals and continuous wavelet transform

NASA Astrophysics Data System (ADS)

Debenjak, Andrej; Boškoski, Pavle; Musizza, Bojan; Petrovčič, Janko; Juričić, Đani

2014-05-01

This paper proposes an approach to the estimation of PEM fuel cell impedance by utilizing pseudo-random binary sequence as a perturbation signal and continuous wavelet transform with Morlet mother wavelet. With the approach, the impedance characteristic in the frequency band from 0.1 Hz to 500 Hz is identified in 60 seconds, approximately five times faster compared to the conventional single-sine approach. The proposed approach was experimentally evaluated on a single PEM fuel cell of a larger fuel cell stack. The quality of the results remains at the same level compared to the single-sine approach.

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.

Greater than the sum of its parts: single-nucleus sequencing identifies convergent evolution of independent EGFR mutants in GBM.

PubMed

Gini, Beatrice; Mischel, Paul S

2014-08-01

Single-cell sequencing approaches are needed to characterize the genomic diversity of complex tumors, shedding light on their evolutionary paths and potentially suggesting more effective therapies. In this issue of Cancer Discovery, Francis and colleagues develop a novel integrative approach to identify distinct tumor subpopulations based on joint detection of clonal and subclonal events from bulk tumor and single-nucleus whole-genome sequencing, allowing them to infer a subclonal architecture. Surprisingly, the authors identify convergent evolution of multiple, mutually exclusive, independent EGFR gain-of-function variants in a single tumor. This study demonstrates the value of integrative single-cell genomics and highlights the biologic primacy of EGFR as an actionable target in glioblastoma. ©2014 American Association for Cancer Research.

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

Massively multiplex single-cell Hi-C

PubMed Central

Ramani, Vijay; Deng, Xinxian; Qiu, Ruolan; Gunderson, Kevin L; Steemers, Frank J; Disteche, Christine M; Noble, William S; Duan, Zhijun; Shendure, Jay

2016-01-01

We present single-cell combinatorial indexed Hi-C (sciHi-C), which applies the concept of combinatorial cellular indexing to chromosome conformation capture. In this proof-of-concept, we generate and sequence six sciHi-C libraries comprising a total of 10,696 single cells. We use sciHi-C data to separate cells by karytoypic and cell-cycle state differences and identify cell-to-cell heterogeneity in mammalian chromosomal conformation. Our results demonstrate that combinatorial indexing is a generalizable strategy for single-cell genomics. PMID:28135255

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

Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells.

PubMed

Kim, Kyu-Tae; Lee, Hye Won; Lee, Hae-Ock; Kim, Sang Cheol; Seo, Yun Jee; Chung, Woosung; Eum, Hye Hyeon; Nam, Do-Hyun; Kim, Junhyong; Joo, Kyeung Min; Park, Woong-Yang

2015-06-19

Intra-tumoral genetic and functional heterogeneity correlates with cancer clinical prognoses. However, the mechanisms by which intra-tumoral heterogeneity impacts therapeutic outcome remain poorly understood. RNA sequencing (RNA-seq) of single tumor cells can provide comprehensive information about gene expression and single-nucleotide variations in individual tumor cells, which may allow for the translation of heterogeneous tumor cell functional responses into customized anti-cancer treatments. We isolated 34 patient-derived xenograft (PDX) tumor cells from a lung adenocarcinoma patient tumor xenograft. Individual tumor cells were subjected to single cell RNA-seq for gene expression profiling and expressed mutation profiling. Fifty tumor-specific single-nucleotide variations, including KRAS(G12D), were observed to be heterogeneous in individual PDX cells. Semi-supervised clustering, based on KRAS(G12D) mutant expression and a risk score representing expression of 69 lung adenocarcinoma-prognostic genes, classified PDX cells into four groups. PDX cells that survived in vitro anti-cancer drug treatment displayed transcriptome signatures consistent with the group characterized by KRAS(G12D) and low risk score. Single-cell RNA-seq on viable PDX cells identified a candidate tumor cell subgroup associated with anti-cancer drug resistance. Thus, single-cell RNA-seq is a powerful approach for identifying unique tumor cell-specific gene expression profiles which could facilitate the development of optimized clinical anti-cancer strategies.

Comprehensive Genome Profiling of Single Sperm Cells by Multiple Annealing and Looping-Based Amplification Cycles and Next-Generation Sequencing from Carriers of Robertsonian Translocation.

PubMed

Sha, Yanwei; Sha, Yankun; Ji, Zhiyong; Ding, Lu; Zhang, Qing; Ouyang, Honggen; Lin, Shaobin; Wang, Xu; Shao, Lin; Shi, Chong; Li, Ping; Song, Yueqiang

2017-03-01

Robertsonian translocation (RT) is a common cause for male infertility, recurrent pregnancy loss, and birth defects. Studying meiotic recombination in RT-carrier patients helps decipher the mechanism and improve the clinical management of infertility and birth defects caused by RT. Here we present a new method to study spermatogenesis on a single-gamete basis from two RT carriers. By using a combined single-cell whole-genome amplification and sequencing protocol, we comprehensively profiled the chromosomal copy number of 88 single sperms from two RT-carrier patients. With the profiled information, chromosomal aberrations were identified on a whole-genome, per-sperm basis. We found that the previously reported interchromosomal effect might not exist with RT carriers. It is suggested that single-cell genome sequencing enables comprehensive chromosomal aneuploidy screening and provides a powerful tool for studying gamete generation from patients carrying chromosomal diseases. © 2017 John Wiley & Sons Ltd/University College London.

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.

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

PubMed Central

Barron, Martin; Zhang, Siyuan

2018-01-01

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

Optofluidic Single-Cell Genome Amplification of Sub-micron Bacteria in the Ocean Subsurface

PubMed Central

Landry, Zachary C.; Vergin, Kevin; Mannenbach, Christopher; Block, Stephen; Yang, Qiao; Blainey, Paul; Carlson, Craig; Giovannoni, Stephen

2018-01-01

Optofluidic single-cell genome amplification was used to obtain genome sequences from sub-micron cells collected from the euphotic and mesopelagic zones of the northwestern Sargasso Sea. Plankton cells were visually selected and manually sorted with an optical trap, yielding 20 partial genome sequences representing seven bacterial phyla. Two organisms, E01-9C-26 (Gammaproteobacteria), represented by four single cell genomes, and Opi.OSU.00C, an uncharacterized Verrucomicrobia, were the first of their types retrieved by single cell genome sequencing and were studied in detail. Metagenomic data showed that E01-9C-26 is found throughout the dark ocean, while Opi.OSU.00C was observed to bloom transiently in the nutrient-depleted euphotic zone of the late spring and early summer. The E01-9C-26 genomes had an estimated size of 4.76–5.05 Mbps, and contained “O” and “W”-type monooxygenase genes related to methane and ammonium monooxygenases that were previously reported from ocean metagenomes. Metabolic reconstruction indicated E01-9C-26 are likely versatile methylotrophs capable of scavenging C1 compounds, methylated compounds, reduced sulfur compounds, and a wide range of amines, including D-amino acids. The genome sequences identified E01-9C-26 as a source of “O” and “W”-type monooxygenase genes related to methane and ammonium monooxygenases that were previously reported from ocean metagenomes, but are of unknown function. In contrast, Opi.OSU.00C genomes encode genes for catabolizing carbohydrate compounds normally associated with eukaryotic phytoplankton. This exploration of optofluidics showed that it was effective for retrieving diverse single-cell bacterioplankton genomes and has potential advantages in microbiology applications that require working with small sample volumes or targeting cells by their morphology.

Whole-organism clone tracing using single-cell sequencing.

PubMed

Alemany, Anna; Florescu, Maria; Baron, Chloé S; Peterson-Maduro, Josi; van Oudenaarden, Alexander

2018-04-05

Embryonic development is a crucial period in the life of a multicellular organism, during which limited sets of embryonic progenitors produce all cells in the adult body. Determining which fate these progenitors acquire in adult tissues requires the simultaneous measurement of clonal history and cell identity at single-cell resolution, which has been a major challenge. Clonal history has traditionally been investigated by microscopically tracking cells during development, monitoring the heritable expression of genetically encoded fluorescent proteins and, more recently, using next-generation sequencing technologies that exploit somatic mutations, microsatellite instability, transposon tagging, viral barcoding, CRISPR-Cas9 genome editing and Cre-loxP recombination. Single-cell transcriptomics provides a powerful platform for unbiased cell-type classification. Here we present ScarTrace, a single-cell sequencing strategy that enables the simultaneous quantification of clonal history and cell type for thousands of cells obtained from different organs of the adult zebrafish. Using ScarTrace, we show that a small set of multipotent embryonic progenitors generate all haematopoietic cells in the kidney marrow, and that many progenitors produce specific cell types in the eyes and brain. In addition, we study when embryonic progenitors commit to the left or right eye. ScarTrace reveals that epidermal and mesenchymal cells in the caudal fin arise from the same progenitors, and that osteoblast-restricted precursors can produce mesenchymal cells during regeneration. Furthermore, we identify resident immune cells in the fin with a distinct clonal origin from other blood cell types. We envision that similar approaches will have major applications in other experimental systems, in which the matching of embryonic clonal origin to adult cell type will ultimately allow reconstruction of how the adult body is built from a single cell.

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

PubMed

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

2017-03-01

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

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.

LEAP: constructing gene co-expression networks for single-cell RNA-sequencing data using pseudotime ordering.

PubMed

Specht, Alicia T; Li, Jun

2017-03-01

To construct gene co-expression networks based on single-cell RNA-Sequencing data, we present an algorithm called LEAP, which utilizes the estimated pseudotime of the cells to find gene co-expression that involves time delay. R package LEAP available on CRAN. jun.li@nd.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Improved genome recovery and integrated cell-size analyses of individual uncultured microbial cells and viral particles.

PubMed

Stepanauskas, Ramunas; Fergusson, Elizabeth A; Brown, Joseph; Poulton, Nicole J; Tupper, Ben; Labonté, Jessica M; Becraft, Eric D; Brown, Julia M; Pachiadaki, Maria G; Povilaitis, Tadas; Thompson, Brian P; Mascena, Corianna J; Bellows, Wendy K; Lubys, Arvydas

2017-07-20

Microbial single-cell genomics can be used to provide insights into the metabolic potential, interactions, and evolution of uncultured microorganisms. Here we present WGA-X, a method based on multiple displacement amplification of DNA that utilizes a thermostable mutant of the phi29 polymerase. WGA-X enhances genome recovery from individual microbial cells and viral particles while maintaining ease of use and scalability. The greatest improvements are observed when amplifying high G+C content templates, such as those belonging to the predominant bacteria in agricultural soils. By integrating WGA-X with calibrated index-cell sorting and high-throughput genomic sequencing, we are able to analyze genomic sequences and cell sizes of hundreds of individual, uncultured bacteria, archaea, protists, and viral particles, obtained directly from marine and soil samples, in a single experiment. This approach may find diverse applications in microbiology and in biomedical and forensic studies of humans and other multicellular organisms.Single-cell genomics can be used to study uncultured microorganisms. Here, Stepanauskas et al. present a method combining improved multiple displacement amplification and FACS, to obtain genomic sequences and cell size information from uncultivated microbial cells and viral particles in environmental samples.

Genome of a Low-Salinity Ammonia-Oxidizing Archaeon Determined by Single-Cell and Metagenomic Analysis

PubMed Central

Potanina, Anastasia; Francis, Christopher A.; Quake, Stephen R.

2011-01-01

Ammonia-oxidizing archaea (AOA) are thought to be among the most abundant microorganisms on Earth and may significantly impact the global nitrogen and carbon cycles. We sequenced the genome of AOA in an enrichment culture from low-salinity sediments in San Francisco Bay using single-cell and metagenomic genome sequence data. Five single cells were isolated inside an integrated microfluidic device using laser tweezers, the cells' genomic DNA was amplified by multiple displacement amplification (MDA) in 50 nL volumes and then sequenced by high-throughput DNA pyrosequencing. This microscopy-based approach to single-cell genomics minimizes contamination and allows correlation of high-resolution cell images with genomic sequences. Statistical properties of coverage across the five single cells, in combination with the contrasting properties of the metagenomic dataset allowed the assembly of a high-quality draft genome. The genome of this AOA, which we designate Candidatus Nitrosoarchaeum limnia SFB1, is ∼1.77 Mb with >2100 genes and a G+C content of 32%. Across the entire genome, the average nucleotide identity to Nitrosopumilus maritimus, the only AOA in pure culture, is ∼70%, suggesting this AOA represents a new genus of Crenarchaeota. Phylogenetically, the 16S rRNA and ammonia monooxygenase subunit A (amoA) genes of this AOA are most closely related to sequences reported from a wide variety of freshwater ecosystems. Like N. maritimus, the low-salinity AOA genome appears to have an ammonia oxidation pathway distinct from ammonia oxidizing bacteria (AOB). In contrast to other described AOA, these low-salinity AOA appear to be motile, based on the presence of numerous motility- and chemotaxis-associated genes in the genome. This genome data will be used to inform targeted physiological and metabolic studies of this novel group of AOA, which may ultimately advance our understanding of AOA metabolism and their impacts on the global carbon and nitrogen cycles. PMID:21364937

Genome of a low-salinity ammonia-oxidizing archaeon determined by single-cell and metagenomic analysis.

PubMed

Blainey, Paul C; Mosier, Annika C; Potanina, Anastasia; Francis, Christopher A; Quake, Stephen R

2011-02-22

Ammonia-oxidizing archaea (AOA) are thought to be among the most abundant microorganisms on Earth and may significantly impact the global nitrogen and carbon cycles. We sequenced the genome of AOA in an enrichment culture from low-salinity sediments in San Francisco Bay using single-cell and metagenomic genome sequence data. Five single cells were isolated inside an integrated microfluidic device using laser tweezers, the cells' genomic DNA was amplified by multiple displacement amplification (MDA) in 50 nL volumes and then sequenced by high-throughput DNA pyrosequencing. This microscopy-based approach to single-cell genomics minimizes contamination and allows correlation of high-resolution cell images with genomic sequences. Statistical properties of coverage across the five single cells, in combination with the contrasting properties of the metagenomic dataset allowed the assembly of a high-quality draft genome. The genome of this AOA, which we designate Candidatus Nitrosoarchaeum limnia SFB1, is ∼1.77 Mb with >2100 genes and a G+C content of 32%. Across the entire genome, the average nucleotide identity to Nitrosopumilus maritimus, the only AOA in pure culture, is ∼70%, suggesting this AOA represents a new genus of Crenarchaeota. Phylogenetically, the 16S rRNA and ammonia monooxygenase subunit A (amoA) genes of this AOA are most closely related to sequences reported from a wide variety of freshwater ecosystems. Like N. maritimus, the low-salinity AOA genome appears to have an ammonia oxidation pathway distinct from ammonia oxidizing bacteria (AOB). In contrast to other described AOA, these low-salinity AOA appear to be motile, based on the presence of numerous motility- and chemotaxis-associated genes in the genome. This genome data will be used to inform targeted physiological and metabolic studies of this novel group of AOA, which may ultimately advance our understanding of AOA metabolism and their impacts on the global carbon and nitrogen cycles.

A survey of human brain transcriptome diversity at the single cell level.

PubMed

Darmanis, Spyros; Sloan, Steven A; Zhang, Ye; Enge, Martin; Caneda, Christine; Shuer, Lawrence M; Hayden Gephart, Melanie G; Barres, Ben A; Quake, Stephen R

2015-06-09

The human brain is a tissue of vast complexity in terms of the cell types it comprises. Conventional approaches to classifying cell types in the human brain at single cell resolution have been limited to exploring relatively few markers and therefore have provided a limited molecular characterization of any given cell type. We used single cell RNA sequencing on 466 cells to capture the cellular complexity of the adult and fetal human brain at a whole transcriptome level. Healthy adult temporal lobe tissue was obtained during surgical procedures where otherwise normal tissue was removed to gain access to deeper hippocampal pathology in patients with medical refractory seizures. We were able to classify individual cells into all of the major neuronal, glial, and vascular cell types in the brain. We were able to divide neurons into individual communities and show that these communities preserve the categorization of interneuron subtypes that is typically observed with the use of classic interneuron markers. We then used single cell RNA sequencing on fetal human cortical neurons to identify genes that are differentially expressed between fetal and adult neurons and those genes that display an expression gradient that reflects the transition between replicating and quiescent fetal neuronal populations. Finally, we observed the expression of major histocompatibility complex type I genes in a subset of adult neurons, but not fetal neurons. The work presented here demonstrates the applicability of single cell RNA sequencing on the study of the adult human brain and constitutes a first step toward a comprehensive cellular atlas of the human brain.

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

Single-cell transcriptome conservation in cryopreserved cells and tissues.

PubMed

Guillaumet-Adkins, Amy; Rodríguez-Esteban, Gustavo; Mereu, Elisabetta; Mendez-Lago, Maria; Jaitin, Diego A; Villanueva, Alberto; Vidal, August; Martinez-Marti, Alex; Felip, Enriqueta; Vivancos, Ana; Keren-Shaul, Hadas; Heath, Simon; Gut, Marta; Amit, Ido; Gut, Ivo; Heyn, Holger

2017-03-01

A variety of single-cell RNA preparation procedures have been described. So far, protocols require fresh material, which hinders complex study designs. We describe a sample preservation method that maintains transcripts in viable single cells, allowing one to disconnect time and place of sampling from subsequent processing steps. We sequence single-cell transcriptomes from >1000 fresh and cryopreserved cells using 3'-end and full-length RNA preparation methods. Our results confirm that the conservation process did not alter transcriptional profiles. This substantially broadens the scope of applications in single-cell transcriptomics and could lead to a paradigm shift in future study designs.

Simultaneous measurement of chromatin accessibility, DNA methylation, and nucleosome phasing in single cells

PubMed Central

Pott, Sebastian

2017-01-01

Gaining insights into the regulatory mechanisms that underlie the transcriptional variation observed between individual cells necessitates the development of methods that measure chromatin organization in single cells. Here I adapted Nucleosome Occupancy and Methylome-sequencing (NOMe-seq) to measure chromatin accessibility and endogenous DNA methylation in single cells (scNOMe-seq). scNOMe-seq recovered characteristic accessibility and DNA methylation patterns at DNase hypersensitive sites (DHSs). An advantage of scNOMe-seq is that sequencing reads are sampled independently of the accessibility measurement. scNOMe-seq therefore controlled for fragment loss, which enabled direct estimation of the fraction of accessible DHSs within individual cells. In addition, scNOMe-seq provided high resolution of chromatin accessibility within individual loci which was exploited to detect footprints of CTCF binding events and to estimate the average nucleosome phasing distances in single cells. scNOMe-seq is therefore well-suited to characterize the chromatin organization of single cells in heterogeneous cellular mixtures. DOI: http://dx.doi.org/10.7554/eLife.23203.001 PMID:28653622

FACS single cell index sorting is highly reliable and determines immune phenotypes of clonally expanded T cells.

PubMed

Penter, Livius; Dietze, Kerstin; Bullinger, Lars; Westermann, Jörg; Rahn, Hans-Peter; Hansmann, Leo

2018-03-14

FACS index sorting allows the isolation of single cells with retrospective identification of each single cell's high-dimensional immune phenotype. We experimentally determine the error rate of index sorting and combine the technology with T cell receptor sequencing to identify clonal T cell expansion in aplastic anemia bone marrow as an example. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput.

PubMed

Gierahn, Todd M; Wadsworth, Marc H; Hughes, Travis K; Bryson, Bryan D; Butler, Andrew; Satija, Rahul; Fortune, Sarah; Love, J Christopher; Shalek, Alex K

2017-04-01

Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA-seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis.

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.

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

PubMed

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

2014-11-04

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

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

PubMed Central

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

2014-01-01

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

Reconstructing each cell's genome within complex microbial communities-dream or reality?

PubMed

Clingenpeel, Scott; Clum, Alicia; Schwientek, Patrick; Rinke, Christian; Woyke, Tanja

2014-01-01

As the vast majority of microorganisms have yet to be cultivated in a laboratory setting, access to their genetic makeup has largely been limited to cultivation-independent methods. These methods, namely metagenomics and more recently single-cell genomics, have become cornerstones for microbial ecology and environmental microbiology. One ultimate goal is the recovery of genome sequences from each cell within an environment to move toward a better understanding of community metabolic potential and to provide substrate for experimental work. As single-cell sequencing has the ability to decipher all sequence information contained in an individual cell, this method holds great promise in tackling such challenge. Methodological limitations and inherent biases however do exist, which will be discussed here based on environmental and benchmark data, to assess how far we are from reaching this goal.

Dynamic ASXL1 Exon Skipping and Alternative Circular Splicing in Single Human Cells

PubMed Central

Natarajan, Sivaraman; Carter, Robert; Brown, Patrick O.

2016-01-01

Circular RNAs comprise a poorly understood new class of noncoding RNA. In this study, we used a combination of targeted deletion, high-resolution splicing detection, and single-cell sequencing to deeply probe ASXL1 circular splicing. We found that efficient circular splicing required the canonical transcriptional start site and inverted AluSx elements. Sequencing-based interrogation of isoforms after ASXL1 overexpression identified promiscuous linear splicing between all exons, with the two most abundant non-canonical linear products skipping the exons that produced the circular isoforms. Single-cell sequencing revealed a strong preference for either the linear or circular ASXL1 isoforms in each cell, and found the predominant exon skipping product is frequently co-expressed with its reciprocal circular isoform. Finally, absolute quantification of ASXL1 isoforms confirmed our findings and suggests that standard methods overestimate circRNA abundance. Taken together, these data reveal a dynamic new view of circRNA genesis, providing additional framework for studying their roles in cellular biology. PMID:27736885

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.

Cell type discovery using single-cell transcriptomics: implications for ontological representation.

PubMed

Aevermann, Brian D; Novotny, Mark; Bakken, Trygve; Miller, Jeremy A; Diehl, Alexander D; Osumi-Sutherland, David; Lasken, Roger S; Lein, Ed S; Scheuermann, Richard H

2018-05-01

Cells are fundamental function units of multicellular organisms, with different cell types playing distinct physiological roles in the body. The recent advent of single-cell transcriptional profiling using RNA sequencing is producing 'big data', enabling the identification of novel human cell types at an unprecedented rate. In this review, we summarize recent work characterizing cell types in the human central nervous and immune systems using single-cell and single-nuclei RNA sequencing, and discuss the implications that these discoveries are having on the representation of cell types in the reference Cell Ontology (CL). We propose a method, based on random forest machine learning, for identifying sets of necessary and sufficient marker genes, which can be used to assemble consistent and reproducible cell type definitions for incorporation into the CL. The representation of defined cell type classes and their relationships in the CL using this strategy will make the cell type classes being identified by high-throughput/high-content technologies findable, accessible, interoperable and reusable (FAIR), allowing the CL to serve as a reference knowledgebase of information about the role that distinct cellular phenotypes play in human health and disease.

A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation.

PubMed

Nestorowa, Sonia; Hamey, Fiona K; Pijuan Sala, Blanca; Diamanti, Evangelia; Shepherd, Mairi; Laurenti, Elisa; Wilson, Nicola K; Kent, David G; Göttgens, Berthold

2016-08-25

Maintenance of the blood system requires balanced cell fate decisions by hematopoietic stem and progenitor cells (HSPCs). Because cell fate choices are executed at the individual cell level, new single-cell profiling technologies offer exciting possibilities for mapping the dynamic molecular changes underlying HSPC differentiation. Here, we have used single-cell RNA sequencing to profile more than 1600 single HSPCs, and deep sequencing has enabled detection of an average of 6558 protein-coding genes per cell. Index sorting, in combination with broad sorting gates, allowed us to retrospectively assign cells to 12 commonly sorted HSPC phenotypes while also capturing intermediate cells typically excluded by conventional gating. We further show that independently generated single-cell data sets can be projected onto the single-cell resolution expression map to directly compare data from multiple groups and to build and refine new hypotheses. Reconstruction of differentiation trajectories reveals dynamic expression changes associated with early lymphoid, erythroid, and granulocyte-macrophage differentiation. The latter two trajectories were characterized by common upregulation of cell cycle and oxidative phosphorylation transcriptional programs. By using external spike-in controls, we estimate absolute messenger RNA (mRNA) levels per cell, showing for the first time that despite a general reduction in total mRNA, a subset of genes shows higher expression levels in immature stem cells consistent with active maintenance of the stem-cell state. Finally, we report the development of an intuitive Web interface as a new community resource to permit visualization of gene expression in HSPCs at single-cell resolution for any gene of choice. © 2016 by The American Society of Hematology.

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

PubMed

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

2017-01-07

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

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.

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.

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.

Detection of single-copy functional genes in prokaryotic cells by two-pass TSA-FISH with polynucleotide probes.

PubMed

Kawakami, Shuji; Hasegawa, Takuya; Imachi, Hiroyuki; Yamaguchi, Takashi; Harada, Hideki; Ohashi, Akiyoshi; Kubota, Kengo

2012-02-01

In situ detection of functional genes with single-cell resolution is currently of interest to microbiologists. Here, we developed a two-pass tyramide signal amplification (TSA)-fluorescence in situ hybridization (FISH) protocol with PCR-derived polynucleotide probes for the detection of single-copy genes in prokaryotic cells. The mcrA gene and the apsA gene in methanogens and sulfate-reducing bacteria, respectively, were targeted. The protocol showed bright fluorescence with a good signal-to-noise ratio and achieved a high efficiency of detection (>98%). The discrimination threshold was approximately 82-89% sequence identity. Microorganisms possessing the mcrA or apsA gene in anaerobic sludge samples were successfully detected by two-pass TSA-FISH with polynucleotide probes. The developed protocol is useful for identifying single microbial cells based on functional gene sequences. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Polycistronic lentiviral vector for "hit and run" reprogramming of adult skin fibroblasts to induced pluripotent stem cells.

PubMed

Chang, Chia-Wei; Lai, Yi-Shin; Pawlik, Kevin M; Liu, Kaimao; Sun, Chiao-Wang; Li, Chao; Schoeb, Trenton R; Townes, Tim M

2009-05-01

We report the derivation of induced pluripotent stem (iPS) cells from adult skin fibroblasts using a single, polycistronic lentiviral vector encoding the reprogramming factors Oct4, Sox2, and Klf4. Porcine teschovirus-1 2A sequences that trigger ribosome skipping were inserted between human cDNAs for these factors, and the polycistron was subcloned downstream of the elongation factor 1 alpha promoter in a self-inactivating (SIN) lentiviral vector containing a loxP site in the truncated 3' long terminal repeat (LTR). Adult skin fibroblasts from a humanized mouse model of sickle cell disease were transduced with this single lentiviral vector, and iPS cell colonies were picked within 30 days. These cells expressed endogenous Oct4, Sox2, Nanog, alkaline phosphatase, stage-specific embryonic antigen-1, and other markers of pluripotency. The iPS cells produced teratomas containing tissue derived from all three germ layers after injection into immunocompromised mice and formed high-level chimeras after injection into murine blastocysts. iPS cell lines with as few as three lentiviral insertions were obtained. Expression of Cre recombinase in these iPS cells resulted in deletion of the lentiviral vector, and sequencing of insertion sites demonstrated that remnant 291-bp SIN LTRs containing a single loxP site did not interrupt coding sequences, promoters, or known regulatory elements. These results suggest that a single, polycistronic "hit and run" vector can safely and effectively reprogram adult dermal fibroblasts into iPS cells.

Effects of sample treatments on genome recovery via single-cell genomics

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

Clingenpeel, Scott; Schwientek, Patrick; Hugenholtz, Philip

2014-06-13

It is known that single-cell genomics is a powerful tool for accessing genetic information from uncultivated microorganisms. Methods of handling samples before single-cell genomic amplification may affect the quality of the genomes obtained. Using three bacterial strains we demonstrate that, compared to cryopreservation, lower-quality single-cell genomes are recovered when the sample is preserved in ethanol or if the sample undergoes fluorescence in situ hybridization, while sample preservation in paraformaldehyde renders it completely unsuitable for sequencing.

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.

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.

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.

Multiplexed droplet single-cell RNA-sequencing using natural genetic variation.

PubMed

Kang, Hyun Min; Subramaniam, Meena; Targ, Sasha; Nguyen, Michelle; Maliskova, Lenka; McCarthy, Elizabeth; Wan, Eunice; Wong, Simon; Byrnes, Lauren; Lanata, Cristina M; Gate, Rachel E; Mostafavi, Sara; Marson, Alexander; Zaitlen, Noah; Criswell, Lindsey A; Ye, Chun Jimmie

2018-01-01

Droplet single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes. However, assessing differential expression across multiple individuals has been hampered by inefficient sample processing and technical batch effects. Here we describe a computational tool, demuxlet, that harnesses natural genetic variation to determine the sample identity of each droplet containing a single cell (singlet) and detect droplets containing two cells (doublets). These capabilities enable multiplexed dscRNA-seq experiments in which cells from unrelated individuals are pooled and captured at higher throughput than in standard workflows. Using simulated data, we show that 50 single-nucleotide polymorphisms (SNPs) per cell are sufficient to assign 97% of singlets and identify 92% of doublets in pools of up to 64 individuals. Given genotyping data for each of eight pooled samples, demuxlet correctly recovers the sample identity of >99% of singlets and identifies doublets at rates consistent with previous estimates. We apply demuxlet to assess cell-type-specific changes in gene expression in 8 pooled lupus patient samples treated with interferon (IFN)-β and perform eQTL analysis on 23 pooled samples.

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

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.

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

PubMed

Kanwar, Nisha; Done, Susan J

2017-01-01

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

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.

Single-cell genomics for the masses

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

Tringe, Susannah G.

In this issue of Nature Biotechnology, Lan et al. describe a new tool in the toolkit for studying uncultivated microbial communities, enabling orders of magnitude higher single cell genome throughput than previous methods. This is achieved by a complex droplet microfluidics workflow encompassing steps from physical cell isolation through genome sequencing, producing tens of thousands of lowcoverage genomes from individual cells.

Single-cell genomics for the masses

DOE PAGES

Tringe, Susannah G.

2017-07-12

In this issue of Nature Biotechnology, Lan et al. describe a new tool in the toolkit for studying uncultivated microbial communities, enabling orders of magnitude higher single cell genome throughput than previous methods. This is achieved by a complex droplet microfluidics workflow encompassing steps from physical cell isolation through genome sequencing, producing tens of thousands of lowcoverage genomes from individual cells.

Understanding development and stem cells using single cell-based analyses of gene expression

PubMed Central

Kumar, Pavithra; Tan, Yuqi

2017-01-01

In recent years, genome-wide profiling approaches have begun to uncover the molecular programs that drive developmental processes. In particular, technical advances that enable genome-wide profiling of thousands of individual cells have provided the tantalizing prospect of cataloging cell type diversity and developmental dynamics in a quantitative and comprehensive manner. Here, we review how single-cell RNA sequencing has provided key insights into mammalian developmental and stem cell biology, emphasizing the analytical approaches that are specific to studying gene expression in single cells. PMID:28049689

Fluorescence In situ Hybridization: Cell-Based Genetic Diagnostic and Research Applications.

PubMed

Cui, Chenghua; Shu, Wei; Li, Peining

2016-01-01

Fluorescence in situ hybridization (FISH) is a macromolecule recognition technology based on the complementary nature of DNA or DNA/RNA double strands. Selected DNA strands incorporated with fluorophore-coupled nucleotides can be used as probes to hybridize onto the complementary sequences in tested cells and tissues and then visualized through a fluorescence microscope or an imaging system. This technology was initially developed as a physical mapping tool to delineate genes within chromosomes. Its high analytical resolution to a single gene level and high sensitivity and specificity enabled an immediate application for genetic diagnosis of constitutional common aneuploidies, microdeletion/microduplication syndromes, and subtelomeric rearrangements. FISH tests using panels of gene-specific probes for somatic recurrent losses, gains, and translocations have been routinely applied for hematologic and solid tumors and are one of the fastest-growing areas in cancer diagnosis. FISH has also been used to detect infectious microbias and parasites like malaria in human blood cells. Recent advances in FISH technology involve various methods for improving probe labeling efficiency and the use of super resolution imaging systems for direct visualization of intra-nuclear chromosomal organization and profiling of RNA transcription in single cells. Cas9-mediated FISH (CASFISH) allowed in situ labeling of repetitive sequences and single-copy sequences without the disruption of nuclear genomic organization in fixed or living cells. Using oligopaint-FISH and super-resolution imaging enabled in situ visualization of chromosome haplotypes from differentially specified single-nucleotide polymorphism loci. Single molecule RNA FISH (smRNA-FISH) using combinatorial labeling or sequential barcoding by multiple round of hybridization were applied to measure mRNA expression of multiple genes within single cells. Research applications of these single molecule single cells DNA and RNA FISH techniques have visualized intra-nuclear genomic structure and sub-cellular transcriptional dynamics of many genes and revealed their functions in various biological processes.

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

PubMed Central

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

2014-01-01

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

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

Gene expression distribution deconvolution in single-cell RNA sequencing.

PubMed

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

2018-06-26

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

Single molecule and single cell epigenomics.

PubMed

Hyun, Byung-Ryool; McElwee, John L; Soloway, Paul D

2015-01-15

Dynamically regulated changes in chromatin states are vital for normal development and can produce disease when they go awry. Accordingly, much effort has been devoted to characterizing these states under normal and pathological conditions. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is the most widely used method to characterize where in the genome transcription factors, modified histones, modified nucleotides and chromatin binding proteins are found; bisulfite sequencing (BS-seq) and its variants are commonly used to characterize the locations of DNA modifications. Though very powerful, these methods are not without limitations. Notably, they are best at characterizing one chromatin feature at a time, yet chromatin features arise and function in combination. Investigators commonly superimpose separate ChIP-seq or BS-seq datasets, and then infer where chromatin features are found together. While these inferences might be correct, they can be misleading when the chromatin source has distinct cell types, or when a given cell type exhibits any cell to cell variation in chromatin state. These ambiguities can be eliminated by robust methods that directly characterize the existence and genomic locations of combinations of chromatin features in very small inputs of cells or ideally, single cells. Here we review single molecule epigenomic methods under development to overcome these limitations, the technical challenges associated with single molecule methods and their potential application to single cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Single Molecule and Single Cell Epigenomics

PubMed Central

Hyun, Byung-Ryool; McElwee, John L.; Soloway, Paul D.

2014-01-01

Dynamically regulated changes in chromatin states are vital for normal development and can produce disease when they go awry. Accordingly, much effort has been devoted to characterizing these states under normal and pathological conditions. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is the most widely used method to characterize where in the genome transcription factors, modified histones, modified nucleotides and chromatin binding proteins are found; bisulfite sequencing (BS-seq) and its variants are commonly used to characterize the locations of DNA modifications. Though very powerful, these methods are not without limitations. Notably, they are best at characterizing one chromatin feature at a time, yet chromatin features arise and function in combination. Investigators commonly superimpose separate ChIP-seq or BS-seq datasets, and then infer where chromatin features are found together. While these inferences might be correct, they can be misleading when the chromatin source has distinct cell types, or when a given cell type exhibits any cell to cell variation in chromatin state. These ambiguities can be eliminated by robust methods that directly characterize the existence and genomic locations of combinations of chromatin features in very small inputs of cells or ideally, single cells. Here we review single molecule epigenomic methods under development to overcome these limitations, the technical challenges associated with single molecule methods and their potential application to single cells. PMID:25204781

Diversity amongst trigeminal neurons revealed by high throughput single cell sequencing

PubMed Central

Nguyen, Minh Q.; Wu, Youmei; Bonilla, Lauren S.; von Buchholtz, Lars J.

2017-01-01

The trigeminal ganglion contains somatosensory neurons that detect a range of thermal, mechanical and chemical cues and innervate unique sensory compartments in the head and neck including the eyes, nose, mouth, meninges and vibrissae. We used single-cell sequencing and in situ hybridization to examine the cellular diversity of the trigeminal ganglion in mice, defining thirteen clusters of neurons. We show that clusters are well conserved in dorsal root ganglia suggesting they represent distinct functional classes of somatosensory neurons and not specialization associated with their sensory targets. Notably, functionally important genes (e.g. the mechanosensory channel Piezo2 and the capsaicin gated ion channel Trpv1) segregate into multiple clusters and often are expressed in subsets of cells within a cluster. Therefore, the 13 genetically-defined classes are likely to be physiologically heterogeneous rather than highly parallel (i.e., redundant) lines of sensory input. Our analysis harnesses the power of single-cell sequencing to provide a unique platform for in silico expression profiling that complements other approaches linking gene-expression with function and exposes unexpected diversity in the somatosensory system. PMID:28957441

Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R.

PubMed

McCarthy, Davis J; Campbell, Kieran R; Lun, Aaron T L; Wills, Quin F

2017-04-15

Single-cell RNA sequencing (scRNA-seq) is increasingly used to study gene expression at the level of individual cells. However, preparing raw sequence data for further analysis is not a straightforward process. Biases, artifacts and other sources of unwanted variation are present in the data, requiring substantial time and effort to be spent on pre-processing, quality control (QC) and normalization. We have developed the R/Bioconductor package scater to facilitate rigorous pre-processing, quality control, normalization and visualization of scRNA-seq data. The package provides a convenient, flexible workflow to process raw sequencing reads into a high-quality expression dataset ready for downstream analysis. scater provides a rich suite of plotting tools for single-cell data and a flexible data structure that is compatible with existing tools and can be used as infrastructure for future software development. The open-source code, along with installation instructions, vignettes and case studies, is available through Bioconductor at http://bioconductor.org/packages/scater . davis@ebi.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

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

Isolation of single Chlamydia-infected cells using laser microdissection.

PubMed

Podgorny, Oleg V; Polina, Nadezhda F; Babenko, Vladislav V; Karpova, Irina Y; Kostryukova, Elena S; Govorun, Vadim M; Lazarev, Vassili N

2015-02-01

Chlamydia are obligate intracellular parasites of humans and animals that cause a wide range of acute and chronic infections. To elucidate the genetic basis of chlamydial parasitism, several approaches for making genetic modifications to Chlamydia have recently been reported. However, the lack of the available methods for the fast and effective selection of genetically modified bacteria restricts the application of genetic tools. We suggest the use of laser microdissection to isolate of single live Chlamydia-infected cells for the re-cultivation and whole-genome sequencing of single inclusion-derived Chlamydia. To visualise individual infected cells, we made use of the vital labelling of inclusions with the fluorescent Golgi-specific dye BODIPY® FL C5-ceramide. We demonstrated that single Chlamydia-infected cells isolated by laser microdissection and placed onto a host cell monolayer resulted in new cycles of infection. We also demonstrated the successful use of whole-genome sequencing to study the genomic variability of Chlamydia derived from a single inclusion. Our work provides the first evidence of the successful use of laser microdissection for the isolation of single live Chlamydia-infected cells, thus demonstrating that this method can help overcome the barriers to the fast and effective selection of Chlamydia. Copyright © 2014 Elsevier B.V. All rights reserved.

Metagenome, metatranscriptome and single-cell sequencing reveal microbial response to Deepwater Horizon oil spill.

PubMed

Mason, Olivia U; Hazen, Terry C; Borglin, Sharon; Chain, Patrick S G; Dubinsky, Eric A; Fortney, Julian L; Han, James; Holman, Hoi-Ying N; Hultman, Jenni; Lamendella, Regina; Mackelprang, Rachel; Malfatti, Stephanie; Tom, Lauren M; Tringe, Susannah G; Woyke, Tanja; Zhou, Jizhong; Rubin, Edward M; Jansson, Janet K

2012-09-01

The Deepwater Horizon oil spill in the Gulf of Mexico resulted in a deep-sea hydrocarbon plume that caused a shift in the indigenous microbial community composition with unknown ecological consequences. Early in the spill history, a bloom of uncultured, thus uncharacterized, members of the Oceanospirillales was previously detected, but their role in oil disposition was unknown. Here our aim was to determine the functional role of the Oceanospirillales and other active members of the indigenous microbial community using deep sequencing of community DNA and RNA, as well as single-cell genomics. Shotgun metagenomic and metatranscriptomic sequencing revealed that genes for motility, chemotaxis and aliphatic hydrocarbon degradation were significantly enriched and expressed in the hydrocarbon plume samples compared with uncontaminated seawater collected from plume depth. In contrast, although genes coding for degradation of more recalcitrant compounds, such as benzene, toluene, ethylbenzene, total xylenes and polycyclic aromatic hydrocarbons, were identified in the metagenomes, they were expressed at low levels, or not at all based on analysis of the metatranscriptomes. Isolation and sequencing of two Oceanospirillales single cells revealed that both cells possessed genes coding for n-alkane and cycloalkane degradation. Specifically, the near-complete pathway for cyclohexane oxidation in the Oceanospirillales single cells was elucidated and supported by both metagenome and metatranscriptome data. The draft genome also included genes for chemotaxis, motility and nutrient acquisition strategies that were also identified in the metagenomes and metatranscriptomes. These data point towards a rapid response of members of the Oceanospirillales to aliphatic hydrocarbons in the deep sea.

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

DOE PAGES

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

2015-04-07

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

Monodisperse Picoliter Droplets for Low-Bias and Contamination-Free Reactions in Single-Cell Whole Genome Amplification

PubMed Central

Maruyama, Toru; Yamagishi, Keisuke; Mori, Tetsushi; Takeyama, Haruko

2015-01-01

Whole genome amplification (WGA) is essential for obtaining genome sequences from single bacterial cells because the quantity of template DNA contained in a single cell is very low. Multiple displacement amplification (MDA), using Phi29 DNA polymerase and random primers, is the most widely used method for single-cell WGA. However, single-cell MDA usually results in uneven genome coverage because of amplification bias, background amplification of contaminating DNA, and formation of chimeras by linking of non-contiguous chromosomal regions. Here, we present a novel MDA method, termed droplet MDA, that minimizes amplification bias and amplification of contaminants by using picoliter-sized droplets for compartmentalized WGA reactions. Extracted DNA fragments from a lysed cell in MDA mixture are divided into 105 droplets (67 pL) within minutes via flow through simple microfluidic channels. Compartmentalized genome fragments can be individually amplified in these droplets without the risk of encounter with reagent-borne or environmental contaminants. Following quality assessment of WGA products from single Escherichia coli cells, we showed that droplet MDA minimized unexpected amplification and improved the percentage of genome recovery from 59% to 89%. Our results demonstrate that microfluidic-generated droplets show potential as an efficient tool for effective amplification of low-input DNA for single-cell genomics and greatly reduce the cost and labor investment required for determination of nearly complete genome sequences of uncultured bacteria from environmental samples. PMID:26389587

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.

DrImpute: imputing dropout events in single cell RNA sequencing data.

PubMed

Gong, Wuming; Kwak, Il-Youp; Pota, Pruthvi; Koyano-Nakagawa, Naoko; Garry, Daniel J

2018-06-08

The single cell RNA sequencing (scRNA-seq) technique begin a new era by allowing the observation of gene expression at the single cell level. However, there is also a large amount of technical and biological noise. Because of the low number of RNA transcriptomes and the stochastic nature of the gene expression pattern, there is a high chance of missing nonzero entries as zero, which are called dropout events. We develop DrImpute to impute dropout events in scRNA-seq data. We show that DrImpute has significantly better performance on the separation of the dropout zeros from true zeros than existing imputation algorithms. We also demonstrate that DrImpute can significantly improve the performance of existing tools for clustering, visualization and lineage reconstruction of nine published scRNA-seq datasets. DrImpute can serve as a very useful addition to the currently existing statistical tools for single cell RNA-seq analysis. DrImpute is implemented in R and is available at https://github.com/gongx030/DrImpute .

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

PubMed

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

2015-07-01

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

Single Cell Multi-Omics Technology: Methodology and Application.

PubMed

Hu, Youjin; An, Qin; Sheu, Katherine; Trejo, Brandon; Fan, Shuxin; Guo, Ying

2018-01-01

In the era of precision medicine, multi-omics approaches enable the integration of data from diverse omics platforms, providing multi-faceted insight into the interrelation of these omics layers on disease processes. Single cell sequencing technology can dissect the genotypic and phenotypic heterogeneity of bulk tissue and promises to deepen our understanding of the underlying mechanisms governing both health and disease. Through modification and combination of single cell assays available for transcriptome, genome, epigenome, and proteome profiling, single cell multi-omics approaches have been developed to simultaneously and comprehensively study not only the unique genotypic and phenotypic characteristics of single cells, but also the combined regulatory mechanisms evident only at single cell resolution. In this review, we summarize the state-of-the-art single cell multi-omics methods and discuss their applications, challenges, and future directions.

Single Cell Multi-Omics Technology: Methodology and Application

PubMed Central

Hu, Youjin; An, Qin; Sheu, Katherine; Trejo, Brandon; Fan, Shuxin; Guo, Ying

2018-01-01

In the era of precision medicine, multi-omics approaches enable the integration of data from diverse omics platforms, providing multi-faceted insight into the interrelation of these omics layers on disease processes. Single cell sequencing technology can dissect the genotypic and phenotypic heterogeneity of bulk tissue and promises to deepen our understanding of the underlying mechanisms governing both health and disease. Through modification and combination of single cell assays available for transcriptome, genome, epigenome, and proteome profiling, single cell multi-omics approaches have been developed to simultaneously and comprehensively study not only the unique genotypic and phenotypic characteristics of single cells, but also the combined regulatory mechanisms evident only at single cell resolution. In this review, we summarize the state-of-the-art single cell multi-omics methods and discuss their applications, challenges, and future directions. PMID:29732369

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

PubMed

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

2016-05-06

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

Understanding development and stem cells using single cell-based analyses of gene expression.

PubMed

Kumar, Pavithra; Tan, Yuqi; Cahan, Patrick

2017-01-01

In recent years, genome-wide profiling approaches have begun to uncover the molecular programs that drive developmental processes. In particular, technical advances that enable genome-wide profiling of thousands of individual cells have provided the tantalizing prospect of cataloging cell type diversity and developmental dynamics in a quantitative and comprehensive manner. Here, we review how single-cell RNA sequencing has provided key insights into mammalian developmental and stem cell biology, emphasizing the analytical approaches that are specific to studying gene expression in single cells. © 2017. Published by The Company of Biologists Ltd.

Comparative Analysis of Single-Cell RNA Sequencing Methods.

PubMed

Ziegenhain, Christoph; Vieth, Beate; Parekh, Swati; Reinius, Björn; Guillaumet-Adkins, Amy; Smets, Martha; Leonhardt, Heinrich; Heyn, Holger; Hellmann, Ines; Enard, Wolfgang

2017-02-16

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq, and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq, and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq, and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods, and it provides a framework for benchmarking further improvements of scRNA-seq protocols. Copyright © 2017 Elsevier Inc. All rights reserved.

A simple and novel method for RNA-seq library preparation of single cell cDNA analysis by hyperactive Tn5 transposase.

PubMed

Brouilette, Scott; Kuersten, Scott; Mein, Charles; Bozek, Monika; Terry, Anna; Dias, Kerith-Rae; Bhaw-Rosun, Leena; Shintani, Yasunori; Coppen, Steven; Ikebe, Chiho; Sawhney, Vinit; Campbell, Niall; Kaneko, Masahiro; Tano, Nobuko; Ishida, Hidekazu; Suzuki, Ken; Yashiro, Kenta

2012-10-01

Deep sequencing of single cell-derived cDNAs offers novel insights into oncogenesis and embryogenesis. However, traditional library preparation for RNA-seq analysis requires multiple steps with consequent sample loss and stochastic variation at each step significantly affecting output. Thus, a simpler and better protocol is desirable. The recently developed hyperactive Tn5-mediated library preparation, which brings high quality libraries, is likely one of the solutions. Here, we tested the applicability of hyperactive Tn5-mediated library preparation to deep sequencing of single cell cDNA, optimized the protocol, and compared it with the conventional method based on sonication. This new technique does not require any expensive or special equipment, which secures wider availability. A library was constructed from only 100 ng of cDNA, which enables the saving of precious specimens. Only a few steps of robust enzymatic reaction resulted in saved time, enabling more specimens to be prepared at once, and with a more reproducible size distribution among the different specimens. The obtained RNA-seq results were comparable to the conventional method. Thus, this Tn5-mediated preparation is applicable for anyone who aims to carry out deep sequencing for single cell cDNAs. Copyright © 2012 Wiley Periodicals, Inc.

Sequence of neuron origin and neocortical laminar fate: relation to cell cycle of origin in the developing murine cerebral wall

NASA Technical Reports Server (NTRS)

Takahashi, T.; Goto, T.; Miyama, S.; Nowakowski, R. S.; Caviness, V. S. Jr

1999-01-01

Neurons destined for each region of the neocortex are known to arise approximately in an "inside-to-outside" sequence from a pseudostratified ventricular epithelium (PVE). This sequence is initiated rostrolaterally and propagates caudomedially. Moreover, independently of location in the PVE, the neuronogenetic sequence in mouse is divisible into 11 cell cycles that occur over a 6 d period. Here we use a novel "birth hour" method that identifies small cohorts of neurons born during a single 2 hr period, i.e., 10-20% of a single cell cycle, which corresponds to approximately 1.5% of the 6 d neuronogenetic period. This method shows that neurons arising with the same cycle of the 11 cycle sequence in mouse have common laminar fates even if they arise from widely separated positions on the PVE (neurons of fields 1 and 40) and therefore arise at different embryonic times. Even at this high level of temporal resolution, simultaneously arising cells occupy more than one cortical layer, and there is substantial overlap in the distributions of cells arising with successive cycles. We demonstrate additionally that the laminar representation of cells arising with a given cycle is little if at all modified over the early postnatal interval of histogenetic cell death. We infer from these findings that cell cycle is a neuronogenetic counting mechanism and that this counting mechanism is integral to subsequent processes that determine cortical laminar fate.

Single-Cell RNA Sequencing of Lymph Node Stromal Cells Reveals Niche-Associated Heterogeneity.

PubMed

Rodda, Lauren B; Lu, Erick; Bennett, Mariko L; Sokol, Caroline L; Wang, Xiaoming; Luther, Sanjiv A; Barres, Ben A; Luster, Andrew D; Ye, Chun Jimmie; Cyster, Jason G

2018-05-15

Stromal cells (SCs) establish the compartmentalization of lymphoid tissues critical to the immune response. However, the full diversity of lymph node (LN) SCs remains undefined. Using droplet-based single-cell RNA sequencing, we identified nine peripheral LN non-endothelial SC clusters. Included are the established subsets, Ccl19 hi T-zone reticular cells (TRCs), marginal reticular cells, follicular dendritic cells (FDCs), and perivascular cells. We also identified Ccl19 lo TRCs, likely including cholesterol-25-hydroxylase + cells located at the T-zone perimeter, Cxcl9 + TRCs in the T-zone and interfollicular region, CD34 + SCs in the capsule and medullary vessel adventitia, indolethylamine N-methyltransferase + SCs in the medullary cords, and Nr4a1 + SCs in several niches. These data help define how transcriptionally distinct LN SCs support niche-restricted immune functions and provide evidence that many SCs are in an activated state. Copyright © 2018 Elsevier Inc. All rights reserved.

Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data.

PubMed

Chin, Chen-Shan; Alexander, David H; Marks, Patrick; Klammer, Aaron A; Drake, James; Heiner, Cheryl; Clum, Alicia; Copeland, Alex; Huddleston, John; Eichler, Evan E; Turner, Stephen W; Korlach, Jonas

2013-06-01

We present a hierarchical genome-assembly process (HGAP) for high-quality de novo microbial genome assemblies using only a single, long-insert shotgun DNA library in conjunction with Single Molecule, Real-Time (SMRT) DNA sequencing. Our method uses the longest reads as seeds to recruit all other reads for construction of highly accurate preassembled reads through a directed acyclic graph-based consensus procedure, which we follow with assembly using off-the-shelf long-read assemblers. In contrast to hybrid approaches, HGAP does not require highly accurate raw reads for error correction. We demonstrate efficient genome assembly for several microorganisms using as few as three SMRT Cell zero-mode waveguide arrays of sequencing and for BACs using just one SMRT Cell. Long repeat regions can be successfully resolved with this workflow. We also describe a consensus algorithm that incorporates SMRT sequencing primary quality values to produce de novo genome sequence exceeding 99.999% accuracy.

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

PubMed Central

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

2011-01-01

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

Single-cell genomics of multiple uncultured stramenopiles reveals underestimated functional diversity across oceans.

PubMed

Seeleuthner, Yoann; Mondy, Samuel; Lombard, Vincent; Carradec, Quentin; Pelletier, Eric; Wessner, Marc; Leconte, Jade; Mangot, Jean-François; Poulain, Julie; Labadie, Karine; Logares, Ramiro; Sunagawa, Shinichi; de Berardinis, Véronique; Salanoubat, Marcel; Dimier, Céline; Kandels-Lewis, Stefanie; Picheral, Marc; Searson, Sarah; Pesant, Stephane; Poulton, Nicole; Stepanauskas, Ramunas; Bork, Peer; Bowler, Chris; Hingamp, Pascal; Sullivan, Matthew B; Iudicone, Daniele; Massana, Ramon; Aury, Jean-Marc; Henrissat, Bernard; Karsenti, Eric; Jaillon, Olivier; Sieracki, Mike; de Vargas, Colomban; Wincker, Patrick

2018-01-22

Single-celled eukaryotes (protists) are critical players in global biogeochemical cycling of nutrients and energy in the oceans. While their roles as primary producers and grazers are well appreciated, other aspects of their life histories remain obscure due to challenges in culturing and sequencing their natural diversity. Here, we exploit single-cell genomics and metagenomics data from the circumglobal Tara Oceans expedition to analyze the genome content and apparent oceanic distribution of seven prevalent lineages of uncultured heterotrophic stramenopiles. Based on the available data, each sequenced genome or genotype appears to have a specific oceanic distribution, principally correlated with water temperature and depth. The genome content provides hypotheses for specialization in terms of cell motility, food spectra, and trophic stages, including the potential impact on their lifestyles of horizontal gene transfer from prokaryotes. Our results support the idea that prominent heterotrophic marine protists perform diverse functions in ocean ecology.

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

Single-cell Sequencing Reveals Variants in ARID1A, GPRC5A and MLL2 Driving Self-renewal of Human Bladder Cancer Stem Cells.

PubMed

Yang, Zhao; Li, Chong; Fan, Zusen; Liu, Hongjie; Zhang, Xiaolong; Cai, Zhiming; Xu, Liqin; Luo, Jian; Huang, Yi; He, Luyun; Liu, Chunxiao; Wu, Song

2017-01-01

Cancer stem cells are considered responsible for many important aspects of tumors such as their self-renewal, tumor-initiating, drug-resistance and metastasis. However, the genetic basis and origination of human bladder cancer stem cells (BCSCs) remains unknown. Here, we conducted single-cell sequencing on 59 cells including BCSCs, bladder cancer non-stem cells (BCNSCs), bladder epithelial stem cells (BESCs) and bladder epithelial non-stem cells (BENSCs) from three bladder cancer (BC) specimens. Specifically, BCSCs demonstrate clonal homogeneity and suggest their origin from BESCs or BCNSCs through phylogenetic analysis. Moreover, 21 key altered genes were identified in BCSCs including six genes not previously described in BC (ETS1, GPRC5A, MKL1, PAWR, PITX2 and RGS9BP). Co-mutations of ARID1A, GPRC5A and MLL2 introduced by CRISPR/Cas9 significantly enhance the capabilities of self-renewal and tumor-initiating of BCNSCs. To our knowledge, our study first provides an overview of the genetic basis of human BCSCs with single-cell sequencing and demonstrates the biclonal origin of human BCSCs via evolution analysis. Human bladder cancer stem cells show the high level of consistency and may derived from bladder epithelial stem cells or bladder cancer non-stem cells. Mutations of ARID1A, GPRC5A and MLL2 grant bladder cancer non-stem cells the capability of self-renewal. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

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

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

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.

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

PubMed

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

2014-11-01

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

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

Precision oncology using a limited number of cells: optimization of whole genome amplification products for sequencing applications.

PubMed

Sho, Shonan; Court, Colin M; Winograd, Paul; Lee, Sangjun; Hou, Shuang; Graeber, Thomas G; Tseng, Hsian-Rong; Tomlinson, James S

2017-07-01

Sequencing analysis of circulating tumor cells (CTCs) enables "liquid biopsy" to guide precision oncology strategies. However, this requires low-template whole genome amplification (WGA) that is prone to errors and biases from uneven amplifications. Currently, quality control (QC) methods for WGA products, as well as the number of CTCs needed for reliable downstream sequencing, remain poorly defined. We sought to define strategies for selecting and generating optimal WGA products from low-template input as it relates to their potential applications in precision oncology strategies. Single pancreatic cancer cells (HPAF-II) were isolated using laser microdissection. WGA was performed using multiple displacement amplification (MDA), multiple annealing and looping based amplification (MALBAC) and PicoPLEX. Quality of amplified DNA products were assessed using a multiplex/RT-qPCR based method that evaluates for 8-cancer related genes and QC-scores were assigned. We utilized this scoring system to assess the impact of de novo modifications to the WGA protocol. WGA products were subjected to Sanger sequencing, array comparative genomic hybridization (aCGH) and next generation sequencing (NGS) to evaluate their performances in respective downstream analyses providing validation of the QC-score. Single-cell WGA products exhibited a significant sample-to-sample variability in amplified DNA quality as assessed by our 8-gene QC assay. Single-cell WGA products that passed the pre-analysis QC had lower amplification bias and improved aCGH/NGS performance metrics when compared to single-cell WGA products that failed the QC. Increasing the number of cellular input resulted in improved QC-scores overall, but a resultant WGA product that consistently passed the QC step required a starting cellular input of at least 20-cells. Our modified-WGA protocol effectively reduced this number, achieving reproducible high-quality WGA products from ≥5-cells as a starting template. A starting cellular input of 5 to 10-cells amplified using the modified-WGA achieved aCGH and NGS results that closely matched that of unamplified, batch genomic DNA. The modified-WGA protocol coupled with the 8-gene QC serve as an effective strategy to enhance the quality of low-template WGA reactions. Furthermore, a threshold number of 5-10 cells are likely needed for a reliable WGA reaction and product with high fidelity to the original starting template.

High-throughput single-cell PCR using microfluidic emulsions

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

Molecular cytogenetics using fluorescence in situ hybridization

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

Gray, J.W.; Kuo, Wen-Lin; Lucas, J.

1990-12-07

Fluorescence in situ hybridization (FISH) with chromosome-specific probes enables several new areas of cytogenetic investigation by allowing visual determination of the presence and normality of specific genetic sequences in single metaphase or interphase cells. in this approach, termed molecular cytogenetics, the genetic loci to be analyzed are made microscopically visible in single cells using in situ hybridization with nucleic acid probes specific to these loci. To accomplish this, the DNA in the target cells is made single stranded by thermal denaturation and incubated with single-stranded, chemically modified probe under conditions where the probe will anneal only with DNA sequences tomore » which it has high DNA sequence homology. The bound probe is then made visible by treatment with a fluorescent reagent such as fluorescein that binds to the chemical modification carried by the probe. The DNA to which the probe does not bind is made visible by staining with a dye such as propidium iodide that fluoresces at a wavelength different from that of the reagent used for probe visualization. We show in this report that probes are now available that make this technique useful for biological dosimetry, prenatal diagnosis and cancer biology. 31 refs., 3 figs.« less

Single Cell Transcriptomics of Hypothalamic Warm Sensitive Neurons that Control Core Body Temperature and Fever Response

PubMed Central

Eberwine, James; Bartfai, Tamas

2011-01-01

We report on an ‘unbiased’ molecular characterization of individual, adult neurons, active in a central, anterior hypothalamic neuronal circuit, by establishing cDNA libraries from each individual, electrophysiologically identified warm sensitive neuron (WSN). The cDNA libraries were analyzed by Affymetrix microarray. The presence and frequency of cDNAs was confirmed and enhanced with Illumina sequencing of each single cell cDNA library. cDNAs encoding the GABA biosynthetic enzyme. GAD1 and of adrenomedullin, galanin, prodynorphin, somatostatin, and tachykinin were found in the WSNs. The functional cellular and in vivo studies on dozens of the more than 500 neurotransmitter -, hormone- receptors and ion channels, whose cDNA was identified and sequence confirmed, suggest little or no discrepancy between the transcriptional and functional data in WSNs; whenever agonists were available for a receptor whose cDNA was identified, a functional response was found.. Sequencing single neuron libraries permitted identification of rarely expressed receptors like the insulin receptor, adiponectin receptor2 and of receptor heterodimers; information that is lost when pooling cells leads to dilution of signals and mixing signals. Despite the common electrophysiological phenotype and uniform GAD1 expression, WSN- transcriptomes show heterogenity, suggesting strong epigenetic influence on the transcriptome. Our study suggests that it is well-worth interrogating the cDNA libraries of single neurons by sequencing and chipping. PMID:20970451

Genome sequence of "Candidatus Mycoplasma haemolamae" strain purdue, a red blood cell pathogen of alpacas (Vicugna pacos) and llamas (Lama glama).

PubMed

Guimaraes, Ana M S; Toth, Balazs; Santos, Andrea P; do Nascimento, Naíla C; Kritchevsky, Janice E; Messick, Joanne B

2012-11-01

We report the complete genome sequence of "Candidatus Mycoplasma haemolamae," an endemic red-cell pathogen of camelids. The single, circular chromosome has 756,845 bp, a 39.3% G+C content, and 925 coding sequences (CDSs). A great proportion (49.1%) of these CDSs are organized into paralogous gene families, which can now be further explored with regard to antigenic variation.

Capturing diversity of marine heterotrophic protists: one cell at a time

PubMed Central

Heywood, Jane L; Sieracki, Michael E; Bellows, Wendy; Poulton, Nicole J; Stepanauskas, Ramunas

2011-01-01

Recent applications of culture-independent, molecular methods have revealed unexpectedly high diversity in a variety of functional and phylogenetic groups of microorganisms in the ocean. However, none of the existing research tools are free from significant limitations, such as PCR and cloning biases, low phylogenetic resolution and others. Here, we employed novel, single-cell sequencing techniques to assess the composition of small (<10 μm diameter), heterotrophic protists from the Gulf of Maine. Single cells were isolated by flow cytometry, their genomes amplified, and 18S rRNA marker genes were amplified and sequenced. We compared the results to traditional environmental PCR cloning of sorted cells. The diversity of heterotrophic protists was significantly higher in the library of single amplified genomes (SAGs) than in environmental PCR clone libraries of the 18S rRNA gene, obtained from the same coastal sample. Libraries of SAGs, but not clones contained several recently discovered, uncultured groups, including picobiliphytes and novel marine stramenopiles. Clone, but not SAG, libraries contained several large clusters of identical and nearly identical sequences of Dinophyceae, Cercozoa and Stramenopiles. Similar results were obtained using two alternative primer sets, suggesting that PCR biases may not be the only explanation for the observed patterns. Instead, differences in the number of 18S rRNA gene copies among the various protist taxa probably had a significant role in determining the PCR clone composition. These results show that single-cell sequencing has the potential to more accurately assess protistan community composition than previously established methods. In addition, the creation of SAG libraries opens opportunities for the analysis of multiple genes or entire genomes of the uncultured protist groups. PMID:20962875

Characterizing polymorphic inversions in human genomes by single-cell sequencing

PubMed Central

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

2016-01-01

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

Current Progresses of Single Cell DNA Sequencing in Breast Cancer Research.

PubMed

Liu, Jianlin; Adhav, Ragini; Xu, Xiaoling

2017-01-01

Breast cancers display striking genetic and phenotypic diversities. To date, several hypotheses are raised to explain and understand the heterogeneity, including theories for cancer stem cell (CSC) and clonal evolution. According to the CSC theory, the most tumorigenic cells, while maintaining themselves through symmetric division, divide asymmetrically to generate non-CSCs with less tumorigenic and metastatic potential, although they can also dedifferentiate back to CSCs. Clonal evolution theory recapitulates that a tumor initially arises from a single cell, which then undergoes clonal expansion to a population of cancer cells. During tumorigenesis and evolution process, cancer cells undergo different degrees of genetic instability and consequently obtain varied genetic aberrations. Yet the heterogeneity in breast cancers is very complex, poorly understood and subjected to further investigation. In recent years, single cell sequencing (SCS) technology developed rapidly, providing a powerful new way to better understand the heterogeneity, which may lay foundations to some new strategies for breast cancer therapies. In this review, we will summarize development of SCS technologies and recent advances of SCS in breast cancer.

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

PubMed Central

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

2017-01-01

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

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

Assembling the Marine Metagenome, One Cell at a Time

PubMed Central

Woyke, Tanja; Xie, Gary; Copeland, Alex; González, José M.; Han, Cliff; Kiss, Hajnalka; Saw, Jimmy H.; Senin, Pavel; Yang, Chi; Chatterji, Sourav; Cheng, Jan-Fang; Eisen, Jonathan A.; Sieracki, Michael E.; Stepanauskas, Ramunas

2009-01-01

The difficulty associated with the cultivation of most microorganisms and the complexity of natural microbial assemblages, such as marine plankton or human microbiome, hinder genome reconstruction of representative taxa using cultivation or metagenomic approaches. Here we used an alternative, single cell sequencing approach to obtain high-quality genome assemblies of two uncultured, numerically significant marine microorganisms. We employed fluorescence-activated cell sorting and multiple displacement amplification to obtain hundreds of micrograms of genomic DNA from individual, uncultured cells of two marine flavobacteria from the Gulf of Maine that were phylogenetically distant from existing cultured strains. Shotgun sequencing and genome finishing yielded 1.9 Mbp in 17 contigs and 1.5 Mbp in 21 contigs for the two flavobacteria, with estimated genome recoveries of about 91% and 78%, respectively. Only 0.24% of the assembling sequences were contaminants and were removed from further analysis using rigorous quality control. In contrast to all cultured strains of marine flavobacteria, the two single cell genomes were excellent Global Ocean Sampling (GOS) metagenome fragment recruiters, demonstrating their numerical significance in the ocean. The geographic distribution of GOS recruits along the Northwest Atlantic coast coincided with ocean surface currents. Metabolic reconstruction indicated diverse potential energy sources, including biopolymer degradation, proteorhodopsin photometabolism, and hydrogen oxidation. Compared to cultured relatives, the two uncultured flavobacteria have small genome sizes, few non-coding nucleotides, and few paralogous genes, suggesting adaptations to narrow ecological niches. These features may have contributed to the abundance of the two taxa in specific regions of the ocean, and may have hindered their cultivation. We demonstrate the power of single cell DNA sequencing to generate reference genomes of uncultured taxa from a complex microbial community of marine bacterioplankton. A combination of single cell genomics and metagenomics enabled us to analyze the genome content, metabolic adaptations, and biogeography of these taxa. PMID:19390573

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

PubMed

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

2016-02-02

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

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

PubMed

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

2018-03-26

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

Dissecting genomic diversity, one cell at a time

PubMed Central

Blainey, Paul C; Quake, Stephen R

2014-01-01

Emerging technologies are bringing single-cell genome sequencing into the mainstream; this field has already yielded insights into the genetic architecture and variability between cells that highlight the dynamic nature of the genome. PMID:24524132

Single Cell Assay for Analyzing Single Cell Exosome and Endocrine Secretion and Cancer Markers

NASA Astrophysics Data System (ADS)

Chiu, Yu-Jui

To understand the inhomogeneity of cells in biological systems, there is a growing demand for the capability to characterize the properties of individual single cells. Since single cell studies require continuous monitoring of the cell behaviors instead of a snapshot test at a single time point, an effective single-cell assay that can support time lapsed studies in a high throughput manner is desired. Most currently available single-cell technologies cannot provide proper environments to sustain cell growth and cannot provide, for appropriate cell types, proliferation of single cells and convenient, non-invasive tests of single cell behaviors from molecular markers. In this dissertation, I present a highly versatile single-cell assay that can accommodate different cellular types, enable easy and efficient single cell loading and culturing, and be suitable for the study of effects of in-vitro environmental factors in combination with drug screening. The salient features of the assay are the non-invasive collection and surveying of single cell secretions at different time points and massively parallel translocation of single cells by user defined criteria, producing very high compatibility to the downstream process such as single cell qPCR and sequencing. Above all, the acquired information is quantitative -- for example, one of the studies is measured by the number of exosomes each single cell secretes for a given time period. Therefore, our single-cell assay provides a convenient, low-cost, and enabling tool for quantitative, time lapsed studies of single cell properties.

Single cell systems biology by super-resolution imaging and combinatorial labeling

PubMed Central

Lubeck, Eric; Cai, Long

2012-01-01

Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral separability of fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using Fluorescence in situ Hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured the mRNA levels of 32 genes simultaneously in single S. cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells provides a natural approach to bring systems biology into single cells. PMID:22660740

JANE: efficient mapping of prokaryotic ESTs and variable length sequence reads on related template genomes

PubMed Central

2009-01-01

Background ESTs or variable sequence reads can be available in prokaryotic studies well before a complete genome is known. Use cases include (i) transcriptome studies or (ii) single cell sequencing of bacteria. Without suitable software their further analysis and mapping would have to await finalization of the corresponding genome. Results The tool JANE rapidly maps ESTs or variable sequence reads in prokaryotic sequencing and transcriptome efforts to related template genomes. It provides an easy-to-use graphics interface for information retrieval and a toolkit for EST or nucleotide sequence function prediction. Furthermore, we developed for rapid mapping an enhanced sequence alignment algorithm which reassembles and evaluates high scoring pairs provided from the BLAST algorithm. Rapid assembly on and replacement of the template genome by sequence reads or mapped ESTs is achieved. This is illustrated (i) by data from Staphylococci as well as from a Blattabacteria sequencing effort, (ii) mapping single cell sequencing reads is shown for poribacteria to sister phylum representative Rhodopirellula Baltica SH1. The algorithm has been implemented in a web-server accessible at http://jane.bioapps.biozentrum.uni-wuerzburg.de. Conclusion Rapid prokaryotic EST mapping or mapping of sequence reads is achieved applying JANE even without knowing the cognate genome sequence. PMID:19943962

Unveiling in situ interactions between marine protists and bacteria through single cell sequencing

PubMed Central

Martinez-Garcia, Manuel; Brazel, David; Poulton, Nicole J; Swan, Brandon K; Gomez, Monica Lluesma; Masland, Dashiell; Sieracki, Michael E; Stepanauskas, Ramunas

2012-01-01

Heterotrophic protists are a highly diverse and biogeochemically significant component of marine ecosystems, yet little is known about their species-specific prey preferences and symbiotic interactions in situ. Here we demonstrate how these previously unresolved questions can be addressed by sequencing the eukaryote and bacterial SSU rRNA genes from individual, uncultured protist cells collected from their natural marine environment and sorted by flow cytometry. We detected Pelagibacter ubique in association with a MAST-4 protist, an actinobacterium in association with a chrysophyte and three bacteroidetes in association with diverse protist groups. The presence of identical phylotypes among the putative prey and the free bacterioplankton in the same sample provides evidence for predator–prey interactions. Our results also suggest a discovery of novel symbionts, distantly related to Rickettsiales and the candidate divisions ZB3 and TG2, associated with Cercozoa and Chrysophyta cells. This study demonstrates the power of single cell sequencing to untangle ecological interactions between uncultured protists and prokaryotes. PMID:21938022

Identification of the gene for disaggregatase from Methanosarcina mazei.

PubMed

Osumi, Naoki; Kakehashi, Yoshihiro; Matsumoto, Shiho; Nagaoka, Kazunari; Sakai, Junichi; Miyashita, Kiyotaka; Kimura, Makoto; Asakawa, Susumu

2008-12-01

The gene sequences encoding disaggregatase (Dag), the enzyme responsible for dispersion of cell aggregates of Methanosarcina mazei to single cells, were determined for three strains of M. mazei (S-6(T), LYC and TMA). The dag genes of the three strains were 3234 bp in length and had almost the same sequences with 97% amino acid sequence identities. Dag was predicted to comprise 1077 amino acid residues and to have a molecular mass of 120 kDa containing three repeats of the DNRLRE domain in the C terminus, which is specific to the genus Methanosarcina and may be responsible for structural organization and cell wall function. Recombinant Dag was overexpressed in Escherichia coli and preparations of the expressed protein exhibited enzymatic activity. The RT-PCR analysis showed that dag was transcribed to mRNA in M. mazei LYC and indicated that the gene was expressed in vivo. This is the first time the gene involved in the morphological change of Methanosarcina spp. from aggregate to single cells has been identified.

Adult Mouse Cortical Cell Taxonomy by Single Cell Transcriptomics

PubMed Central

Tasic, Bosiljka; Menon, Vilas; Nguyen, Thuc Nghi; Kim, Tae Kyung; Jarsky, Tim; Yao, Zizhen; Levi, Boaz; Gray, Lucas T.; Sorensen, Staci A.; Dolbeare, Tim; Bertagnolli, Darren; Goldy, Jeff; Shapovalova, Nadiya; Parry, Sheana; Lee, Changkyu; Smith, Kimberly; Bernard, Amy; Madisen, Linda; Sunkin, Susan M.; Hawrylycz, Michael; Koch, Christof; Zeng, Hongkui

2016-01-01

Nervous systems are composed of various cell types, but the extent of cell type diversity is poorly understood. Here, we construct a cellular taxonomy of one cortical region, primary visual cortex, in adult mice based on single cell RNA-sequencing. We identify 49 transcriptomic cell types including 23 GABAergic, 19 glutamatergic and seven non-neuronal types. We also analyze cell-type specific mRNA processing and characterize genetic access to these transcriptomic types by many transgenic Cre lines. Finally, we show that some of our transcriptomic cell types display specific and differential electrophysiological and axon projection properties, thereby confirming that the single cell transcriptomic signatures can be associated with specific cellular properties. PMID:26727548

Technical Considerations for Reduced Representation Bisulfite Sequencing with Multiplexed Libraries

PubMed Central

Chatterjee, Aniruddha; Rodger, Euan J.; Stockwell, Peter A.; Weeks, Robert J.; Morison, Ian M.

2012-01-01

Reduced representation bisulfite sequencing (RRBS), which couples bisulfite conversion and next generation sequencing, is an innovative method that specifically enriches genomic regions with a high density of potential methylation sites and enables investigation of DNA methylation at single-nucleotide resolution. Recent advances in the Illumina DNA sample preparation protocol and sequencing technology have vastly improved sequencing throughput capacity. Although the new Illumina technology is now widely used, the unique challenges associated with multiplexed RRBS libraries on this platform have not been previously described. We have made modifications to the RRBS library preparation protocol to sequence multiplexed libraries on a single flow cell lane of the Illumina HiSeq 2000. Furthermore, our analysis incorporates a bioinformatics pipeline specifically designed to process bisulfite-converted sequencing reads and evaluate the output and quality of the sequencing data generated from the multiplexed libraries. We obtained an average of 42 million paired-end reads per sample for each flow-cell lane, with a high unique mapping efficiency to the reference human genome. Here we provide a roadmap of modifications, strategies, and trouble shooting approaches we implemented to optimize sequencing of multiplexed libraries on an a RRBS background. PMID:23193365

Genome Sequence of “Candidatus Mycoplasma haemolamae” Strain Purdue, a Red Blood Cell Pathogen of Alpacas (Vicugna pacos) and Llamas (Lama glama)

PubMed Central

Toth, Balazs; Santos, Andrea P.; do Nascimento, Naíla C.; Kritchevsky, Janice E.

2012-01-01

We report the complete genome sequence of “Candidatus Mycoplasma haemolamae,” an endemic red-cell pathogen of camelids. The single, circular chromosome has 756,845 bp, a 39.3% G+C content, and 925 coding sequences (CDSs). A great proportion (49.1%) of these CDSs are organized into paralogous gene families, which can now be further explored with regard to antigenic variation. PMID:23105057

Single cell genomics of uncultured marine alveolates shows paraphyly of basal dinoflagellates.

PubMed

Strassert, Jürgen F H; Karnkowska, Anna; Hehenberger, Elisabeth; Del Campo, Javier; Kolisko, Martin; Okamoto, Noriko; Burki, Fabien; Janouškovec, Jan; Poirier, Camille; Leonard, Guy; Hallam, Steven J; Richards, Thomas A; Worden, Alexandra Z; Santoro, Alyson E; Keeling, Patrick J

2018-01-01

Marine alveolates (MALVs) are diverse and widespread early-branching dinoflagellates, but most knowledge of the group comes from a few cultured species that are generally not abundant in natural samples, or from diversity analyses of PCR-based environmental SSU rRNA gene sequences. To more broadly examine MALV genomes, we generated single cell genome sequences from seven individually isolated cells. Genes expected of heterotrophic eukaryotes were found, with interesting exceptions like presence of proteorhodopsin and vacuolar H + -pyrophosphatase. Phylogenetic analysis of concatenated SSU and LSU rRNA gene sequences provided strong support for the paraphyly of MALV lineages. Dinoflagellate viral nucleoproteins were found only in MALV groups that branched as sister to dinokaryotes. Our findings indicate that multiple independent origins of several characteristics early in dinoflagellate evolution, such as a parasitic life style, underlie the environmental diversity of MALVs, and suggest they have more varied trophic modes than previously thought.

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.

MeCorS: Metagenome-enabled error correction of single cell sequencing reads

DOE PAGES

Bremges, Andreas; Singer, Esther; Woyke, Tanja; ...

2016-03-15

Here we present a new tool, MeCorS, to correct chimeric reads and sequencing errors in Illumina data generated from single amplified genomes (SAGs). It uses sequence information derived from accompanying metagenome sequencing to accurately correct errors in SAG reads, even from ultra-low coverage regions. In evaluations on real data, we show that MeCorS outperforms BayesHammer, the most widely used state-of-the-art approach. MeCorS performs particularly well in correcting chimeric reads, which greatly improves both accuracy and contiguity of de novo SAG assemblies.

Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea

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

Bowers, Robert M.; Kyrpides, Nikos C.; Stepanauskas, Ramunas

The number of genomes from uncultivated microbes will soon surpass the number of isolate genomes in public databases (Hugenholtz, Skarshewski, & Parks, 2016). Technological advancements in high-throughput sequencing and assembly, including single-cell genomics and the computational extraction of genomes from metagenomes (GFMs), are largely responsible. Here we propose community standards for reporting the Minimum Information about a Single-Cell Genome (MIxS-SCG) and Minimum Information about Genomes extracted From Metagenomes (MIxS-GFM) specific for Bacteria and Archaea. The standards have been developed in the context of the International Genomics Standards Consortium (GSC) community (Field et al., 2014) and can be viewed as amore » supplement to other GSC checklists including the Minimum Information about a Genome Sequence (MIGS), Minimum information about a Metagenomic Sequence(s) (MIMS) (Field et al., 2008) and Minimum Information about a Marker Gene Sequence (MIMARKS) (P. Yilmaz et al., 2011). Community-wide acceptance of MIxS-SCG and MIxS-GFM for Bacteria and Archaea will enable broad comparative analyses of genomes from the majority of taxa that remain uncultivated, improving our understanding of microbial function, ecology, and evolution.« less

Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity.

PubMed

Nguyen, Quy H; Pervolarakis, Nicholas; Blake, Kerrigan; Ma, Dennis; Davis, Ryan Tevia; James, Nathan; Phung, Anh T; Willey, Elizabeth; Kumar, Raj; Jabart, Eric; Driver, Ian; Rock, Jason; Goga, Andrei; Khan, Seema A; Lawson, Devon A; Werb, Zena; Kessenbrock, Kai

2018-05-23

Breast cancer arises from breast epithelial cells that acquire genetic alterations leading to subsequent loss of tissue homeostasis. Several distinct epithelial subpopulations have been proposed, but complete understanding of the spectrum of heterogeneity and differentiation hierarchy in the human breast remains elusive. Here, we use single-cell mRNA sequencing (scRNAseq) to profile the transcriptomes of 25,790 primary human breast epithelial cells isolated from reduction mammoplasties of seven individuals. Unbiased clustering analysis reveals the existence of three distinct epithelial cell populations, one basal and two luminal cell types, which we identify as secretory L1- and hormone-responsive L2-type cells. Pseudotemporal reconstruction of differentiation trajectories produces one continuous lineage hierarchy that closely connects the basal lineage to the two differentiated luminal branches. Our comprehensive cell atlas provides insights into the cellular blueprint of the human breast epithelium and will form the foundation to understand how the system goes awry during breast cancer.

acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data

DOE PAGES

Lux, Markus; Kruger, Jan; Rinke, Christian; ...

2016-12-20

A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data. We present acdc, a tool specifically developed to aidmore » the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows. Acdc can reliably detect contamination in single-cell genome data. In addition to database-driven detection, it complements existing tools by its unsupervised techniques, which allow for the detection of de novo contaminants. Our contribution has the potential to drastically reduce the amount of resources put into these processes, particularly in the context of limited availability of reference species. As single-cell genome data continues to grow rapidly, acdc adds to the toolkit of crucial quality assurance tools.« less

acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data

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

Lux, Markus; Kruger, Jan; Rinke, Christian

A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data. We present acdc, a tool specifically developed to aidmore » the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows. Acdc can reliably detect contamination in single-cell genome data. In addition to database-driven detection, it complements existing tools by its unsupervised techniques, which allow for the detection of de novo contaminants. Our contribution has the potential to drastically reduce the amount of resources put into these processes, particularly in the context of limited availability of reference species. As single-cell genome data continues to grow rapidly, acdc adds to the toolkit of crucial quality assurance tools.« less

Morphological changes in cultured bovine lymphoid cell lines associated with bovine viral diarrhea virus (BVDV) single and dual infections with bovine leukemia virus (BLV)

USDA-ARS?s Scientific Manuscript database

Currently, American Type Culture Collection (ATCC) makes available two cell lines derived from the same lymphoblast-like suspension cell that have been confirmed by next-generation sequencing and RT-PCR to have either a single contaminate of BVDV2a (CRL-8037) or dual contaminates of both BVDV and BL...

Dissecting the human microbiome with single-cell genomics.

PubMed

Tolonen, Andrew C; Xavier, Ramnik J

2017-06-14

Recent advances in genome sequencing of single microbial cells enable the assignment of functional roles to members of the human microbiome that cannot currently be cultured. This approach can reveal the genomic basis of phenotypic variation between closely related strains and can be applied to the targeted study of immunogenic bacteria in disease.

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.

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.

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

PubMed

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

2017-10-01

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

Single sea urchin phagocytes express messages of a single sequence from the diverse Sp185/333 gene family in response to bacterial challenge.

PubMed

Majeske, Audrey J; Oren, Matan; Sacchi, Sandro; Smith, L Courtney

2014-12-01

Immune systems in animals rely on fast and efficient responses to a wide variety of pathogens. The Sp185/333 gene family in the purple sea urchin, Strongylocentrotus purpuratus, consists of an estimated 50 (±10) members per genome that share a basic gene structure but show high sequence diversity, primarily due to the mosaic appearance of short blocks of sequence called elements. The genes show significantly elevated expression in three subpopulations of phagocytes responding to marine bacteria. The encoded Sp185/333 proteins are highly diverse and have central effector functions in the immune system. In this study we report the Sp185/333 gene expression in single sea urchin phagocytes. Sea urchins challenged with heat-killed marine bacteria resulted in a typical increase in coelomocyte concentration within 24 h, which included an increased proportion of phagocytes expressing Sp185/333 proteins. Phagocyte fractions enriched from coelomocytes were used in limiting dilutions to obtain samples of single cells that were evaluated for Sp185/333 gene expression by nested RT-PCR. Amplicon sequences showed identical or nearly identical Sp185/333 amplicon sequences in single phagocytes with matches to six known Sp185/333 element patterns, including both common and rare element patterns. This suggested that single phagocytes show restricted expression from the Sp185/333 gene family and infers a diverse, flexible, and efficient response to pathogens. This type of expression pattern from a family of immune response genes in single cells has not been identified previously in other invertebrates. Copyright © 2014 by The American Association of Immunologists, Inc.

Draft genome sequence of Thauera sp. strain SWB20, isolated from a Singapore wastewater treatment facility using gel microdroplets

DOE PAGES

Dichosa, Armand E. K.; Davenport, Karen W.; Li, Po-E; ...

2015-03-19

In this study, we report here the genome sequence of Thauera sp. strain SWB20, isolated from a Singaporean wastewater treatment facility using gel microdroplets (GMDs) and single-cell genomics (SCG). This approach provided a single clonal microcolony that was sufficient to obtain a 4.9-Mbp genome assembly of an ecologically relevant Thauera species.

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

PubMed

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

2018-05-11

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

UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy

PubMed Central

2017-01-01

Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughput sequencing experiments. Through a UMI, identical copies arising from distinct molecules can be distinguished from those arising through PCR amplification of the same molecule. However, bioinformatic methods to leverage the information from UMIs have yet to be formalized. In particular, sequencing errors in the UMI sequence are often ignored or else resolved in an ad hoc manner. We show that errors in the UMI sequence are common and introduce network-based methods to account for these errors when identifying PCR duplicates. Using these methods, we demonstrate improved quantification accuracy both under simulated conditions and real iCLIP and single-cell RNA-seq data sets. Reproducibility between iCLIP replicates and single-cell RNA-seq clustering are both improved using our proposed network-based method, demonstrating the value of properly accounting for errors in UMIs. These methods are implemented in the open source UMI-tools software package. PMID:28100584

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.

Single cell transcriptomics of hypothalamic warm sensitive neurons that control core body temperature and fever response Signaling asymmetry and an extension of chemical neuroanatomy.

PubMed

Eberwine, James; Bartfai, Tamas

2011-03-01

We report on an 'unbiased' molecular characterization of individual, adult neurons, active in a central, anterior hypothalamic neuronal circuit, by establishing cDNA libraries from each individual, electrophysiologically identified warm sensitive neuron (WSN). The cDNA libraries were analyzed by Affymetrix microarray. The presence and frequency of cDNAs were confirmed and enhanced with Illumina sequencing of each single cell cDNA library. cDNAs encoding the GABA biosynthetic enzyme Gad1 and of adrenomedullin, galanin, prodynorphin, somatostatin, and tachykinin were found in the WSNs. The functional cellular and in vivo studies on dozens of the more than 500 neurotransmitters, hormone receptors and ion channels, whose cDNA was identified and sequence confirmed, suggest little or no discrepancy between the transcriptional and functional data in WSNs; whenever agonists were available for a receptor whose cDNA was identified, a functional response was found. Sequencing single neuron libraries permitted identification of rarely expressed receptors like the insulin receptor, adiponectin receptor 2 and of receptor heterodimers; information that is lost when pooling cells leads to dilution of signals and mixing signals. Despite the common electrophysiological phenotype and uniform Gad1 expression, WSN transcriptomes show heterogeneity, suggesting strong epigenetic influence on the transcriptome. Our study suggests that it is well-worth interrogating the cDNA libraries of single neurons by sequencing and chipping. Copyright © 2010 Elsevier Inc. All rights reserved.

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

Isolation of a single rice chromosome by optical micromanipulation

NASA Astrophysics Data System (ADS)

Wang, Haowei; Liu, Xiaohui; Li, Yinmei; Han, Bin; Lou, Liren; Wang, Kangjun

2004-01-01

A new method based on optical tweezers technology is reported for the isolation of a single chromosome. A rice cell suspended in liquid was first fragmented by laser pulses (optical scalpel). Then a single released chromosome from the cell was manipulated and pulled away from other cells and oddments by optical tweezers without any direct mechanical contact. Finally the isolated single chromosome was extracted individually into a glass capillary nearby. After molecular cloning of the isolated chromosome, we obtained some specific DNA segments from the single chromosome. All these segments can be used for rice genomic sequencing. Different methods of extracting a single chromosome are compared. The advantages of optical micromanipulation method are summarized.

Reproducibility of Illumina platform deep sequencing errors allows accurate determination of DNA barcodes in cells.

PubMed

Beltman, Joost B; Urbanus, Jos; Velds, Arno; van Rooij, Nienke; Rohr, Jan C; Naik, Shalin H; Schumacher, Ton N

2016-04-02

Next generation sequencing (NGS) of amplified DNA is a powerful tool to describe genetic heterogeneity within cell populations that can both be used to investigate the clonal structure of cell populations and to perform genetic lineage tracing. For applications in which both abundant and rare sequences are biologically relevant, the relatively high error rate of NGS techniques complicates data analysis, as it is difficult to distinguish rare true sequences from spurious sequences that are generated by PCR or sequencing errors. This issue, for instance, applies to cellular barcoding strategies that aim to follow the amount and type of offspring of single cells, by supplying these with unique heritable DNA tags. Here, we use genetic barcoding data from the Illumina HiSeq platform to show that straightforward read threshold-based filtering of data is typically insufficient to filter out spurious barcodes. Importantly, we demonstrate that specific sequencing errors occur at an approximately constant rate across different samples that are sequenced in parallel. We exploit this observation by developing a novel approach to filter out spurious sequences. Application of our new method demonstrates its value in the identification of true sequences amongst spurious sequences in biological data sets.

Sorting Out the Ocean Crust Deep Biosphere with Single Cell Omics Approaches

NASA Astrophysics Data System (ADS)

Orcutt, B.; D'Angelo, T.; Goordial, J.; Jones, R. M.; Carr, S. A.

2017-12-01

Although oceanic crust comprises a large habitat for subsurface life, the structure, function, and dynamics of microbial communities living on rocks in the subsurface are poorly understood. Single cell level approaches can overcome limitations of low biomass in subsurface systems. Coupled with incubation experiments with amino acid orthologs, single cell level sorting can reveal high resolution information about identity, functional potential, and growth. Leveraging collaboration with the Single Cell Genomics Center and the Facility for Aquatic Cytometry at Bigelow Laboratory, we present recent results from single cell level sorting and -omics sequencing from several crustal environments, including the Atlantis Massif and the Juan de Fuca Ridge flank. We will also highlight new experiments conducted with samples recovered from the flank of the Mid-Atlantic Ridge.

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/ .

Comparative analysis of single-cell RNA sequencing data from mouse spermatogonial and mesenchymal stem cells to identify differentially expressed genes and transcriptional regulators of germline cells.

PubMed

Sisakhtnezhad, Sajjad; Heshmati, Parvin

2018-07-01

Identifying effective internal factors for regulating germline commitment during development and for maintaining spermatogonial stem cells (SSCs) self-renewal is important to understand the molecular basis of spermatogenesis process, and to develop new protocols for the production of the germline cells from other cell sources. Therefore, this study was designed to investigate single-cell RNA-sequencing data for identification of differentially expressed genes (DEGs) in 12 mouse-derived single SSCs (mSSCs) in compare with 16 mouse-derived single mesenchymal stem cells. We also aimed to find transcriptional regulators of DEGs. Collectively, 1,584 up-regulated DEGs were identified that are associated with 32 biological processes. Moreover, investigation of the expression profiles of genes including in spermatogenesis process revealed that Dazl, Ddx4, Sall4, Fkbp6, Tex15, Tex19.1, Rnf17, Piwil2, Taf7l, Zbtb16, and Cadm1 are presented in the first 30 up-regulated DEGs. We also found 12 basal transcription factors (TFs) and three sequence-specific TFs that control the expression of DEGs. Our findings also indicated that MEIS1, SMC3, TAF1, KAT2A, STAT3, GTF3C2, SIN3A, BDP1, PHC1, and EGR1 are the main central regulators of DEGs in mSSCs. In addition, we collectively detected two significant protein complexes in the protein-protein interactions network for DEGs regulators. Finally, this study introduces the major upstream kinases for the main central regulators of DEGs and the components of core protein complexes. In conclusion, this study provides a molecular blueprint to uncover the molecular mechanisms behind the biology of SSCs and offers a list of candidate factors for cell type conversion approaches and production of germ cells. © 2017 Wiley Periodicals, Inc.

Mutational analysis of single circulating tumor cells by next generation sequencing in metastatic breast cancer.

PubMed

De Luca, Francesca; Rotunno, Giada; Salvianti, Francesca; Galardi, Francesca; Pestrin, Marta; Gabellini, Stefano; Simi, Lisa; Mancini, Irene; Vannucchi, Alessandro Maria; Pazzagli, Mario; Di Leo, Angelo; Pinzani, Pamela

2016-05-03

Circulating Tumor Cells (CTCs) represent a "liquid biopsy" of the tumor potentially allowing real-time monitoring of cancer biology and therapies in individual patients.The purpose of the study was to explore the applicability of a protocol for the molecular characterization of single CTCs by Next Generation Sequencing (NGS) in order to investigate cell heterogeneity and provide a tool for a personalized medicine approach.CTCs were enriched and enumerated by CellSearch in blood from four metastatic breast cancer patients and singularly isolated by DEPArray. Upon whole genome amplification 3-5 single CTCs per patient were analyzed by NGS for 50 cancer-related genes.We found 51 sequence variants in 25 genes. We observed inter- and intra-patient heterogeneity in the mutational status of CTCs.The highest number of somatic deleterious mutations was found in the gene TP53, whose mutation is associated with adverse prognosis in breast cancer.The discordance between the mutational status of the primary tumor and CTCs observed in 3 patients suggests that, in advanced stages of cancer, CTC characteristics are more closely linked to the dynamic modifications of the disease status.In one patient the mutational profiles of CTCs before and during treatment shared only few sequence variants.This study supports the applicability of a non-invasive approach based on the liquid biopsy in metastatic breast cancer patients which, in perspective, should allow investigating the clonal evolution of the tumor for the development of new therapeutic strategies in precision medicine.

Sequence Dependent Interactions Between DNA and Single-Walled Carbon Nanotubes

NASA Astrophysics Data System (ADS)

Roxbury, Daniel

It is known that single-stranded DNA adopts a helical wrap around a single-walled carbon nanotube (SWCNT), forming a water-dispersible hybrid molecule. The ability to sort mixtures of SWCNTs based on chirality (electronic species) has recently been demonstrated using special short DNA sequences that recognize certain matching SWCNTs of specific chirality. This thesis investigates the intricacies of DNA-SWCNT sequence-specific interactions through both experimental and molecular simulation studies. The DNA-SWCNT binding strengths were experimentally quantified by studying the kinetics of DNA replacement by a surfactant on the surface of particular SWCNTs. Recognition ability was found to correlate strongly with measured binding strength, e.g. DNA sequence (TAT)4 was found to bind 20 times stronger to the (6,5)-SWCNT than sequence (TAT)4T. Next, using replica exchange molecular dynamics (REMD) simulations, equilibrium structures formed by (a) single-strands and (b) multiple-strands of 12-mer oligonucleotides adsorbed on various SWCNTs were explored. A number of structural motifs were discovered in which the DNA strand wraps around the SWCNT and 'stitches' to itself via hydrogen bonding. Great variability among equilibrium structures was observed and shown to be directly influenced by DNA sequence and SWCNT type. For example, the (6,5)-SWCNT DNA recognition sequence, (TAT)4, was found to wrap in a tight single-stranded right-handed helical conformation. In contrast, DNA sequence T12 forms a beta-barrel left-handed structure on the same SWCNT. These are the first theoretical indications that DNA-based SWCNT selectivity can arise on a molecular level. In a biomedical collaboration with the Mayo Clinic, pathways for DNA-SWCNT internalization into healthy human endothelial cells were explored. Through absorbance spectroscopy, TEM imaging, and confocal fluorescence microscopy, we showed that intracellular concentrations of SWCNTs far exceeded those of the incubation solution, which suggested an energy-dependent pathway. Additionally, by means of pharmacological inhibition and vector-induced gene knockout studies, the DNA-SWCNTs were shown to enter the cells via Rac1-mediated macropinocytosis.

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

PubMed

Camp, J Gray; Treutlein, Barbara

2017-05-01

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

Single-cell epigenomics: techniques and emerging applications.

PubMed

Schwartzman, Omer; Tanay, Amos

2015-12-01

Epigenomics is the study of the physical modifications, associations and conformations of genomic DNA sequences, with the aim of linking these with epigenetic memory, cellular identity and tissue-specific functions. While current techniques in the field are characterizing the average epigenomic features across large cell ensembles, the increasing interest in the epigenetics within complex and heterogeneous tissues is driving the development of single-cell epigenomics. We review emerging single-cell methods for capturing DNA methylation, chromatin accessibility, histone modifications, chromosome conformation and replication dynamics. Together, these techniques are rapidly becoming a powerful tool in studies of cellular plasticity and diversity, as seen in stem cells and cancer.

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.

Measles virus minigenomes encoding two autofluorescent proteins reveal cell-to-cell variation in reporter expression dependent on viral sequences between the transcription units.

PubMed

Rennick, Linda J; Duprex, W Paul; Rima, Bert K

2007-10-01

Transcription from morbillivirus genomes commences at a single promoter in the 3' non-coding terminus, with the six genes being transcribed sequentially. The 3' and 5' untranslated regions (UTRs) of the genes (mRNA sense), together with the intergenic trinucleotide spacer, comprise the non-coding sequences (NCS) of the virus and contain the conserved gene end and gene start signals, respectively. Bicistronic minigenomes containing transcription units (TUs) encoding autofluorescent reporter proteins separated by measles virus (MV) NCS were used to give a direct estimation of gene expression in single, living cells by assessing the relative amounts of each fluorescent protein in each cell. Initially, five minigenomes containing each of the MV NCS were generated. Assays were developed to determine the amount of each fluorescent protein in cells at both cell population and single-cell levels. This revealed significant variations in gene expression between cells expressing the same NCS-containing minigenome. The minigenome containing the M/F NCS produced significantly lower amounts of fluorescent protein from the second TU (TU2), compared with the other minigenomes. A minigenome with a truncated F 5' UTR had increased expression from TU2. This UTR is 524 nt longer than the other MV 5' UTRs. Insertions into the 5' UTR of the enhanced green fluorescent protein gene in the minigenome containing the N/P NCS showed that specific sequences, rather than just the additional length of F 5' UTR, govern this decreased expression from TU2.

Massively parallel digital transcriptional profiling of single cells

PubMed Central

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

2017-01-01

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

PyClone: statistical inference of clonal population structure in cancer.

PubMed

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

2014-04-01

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

Metagenomics, metatranscriptomics and single cell genomics reveal functional response of active Oceanospirillales to Gulf oil spill

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

Mason, Olivia U.; Hazen, Terry C.; Borglin, Sharon

The Deepwater Horizon oil spill in the Gulf of Mexico resulted in a deep-sea hydrocarbon plume that caused a shift in the indigenous microbial community composition with unknown ecological consequences. Early in the spill history, a bloom of uncultured, thus uncharacterized, members of the Oceanospirillales was previously detected, but their role in oil disposition was unknown. Here our aim was to determine the functional role of the Oceanospirillales and other active members of the indigenous microbial community using deep sequencing of community DNA and RNA, as well as single-cell genomics. Shotgun metagenomic and metatranscriptomic sequencing revealed that genes for motility,more » chemotaxis and aliphatic hydrocarbon degradation were significantly enriched and expressed in the hydrocarbon plume samples compared with uncontaminated seawater collected from plume depth. In contrast, although genes coding for degradation of more recalcitrant compounds, such as benzene, toluene, ethylbenzene, total xylenes and polycyclic aromatic hydrocarbons, were identified in the metagenomes, they were expressed at low levels, or not at all based on analysis of the metatranscriptomes. Isolation and sequencing of two Oceanospirillales single cells revealed that both cells possessed genes coding for n-alkane and cycloalkane degradation. Specifically, the near-complete pathway for cyclohexane oxidation in the Oceanospirillales single cells was elucidated and supported by both metagenome and metatranscriptome data. The draft genome also included genes for chemotaxis, motility and nutrient acquisition strategies that were also identified in the metagenomes and metatranscriptomes. These data point towards a rapid response of members of the Oceanospirillales to aliphatic hydrocarbons in the deep sea.« less

A Simple Method for Visualization of Locus-Specific H4K20me1 Modifications in Living Caenorhabditis elegans Single Cells.

PubMed

Shinkai, Yoichi; Kuramochi, Masahiro; Doi, Motomichi

2018-05-03

Recently, advances in next-generation sequencing technologies have enabled genome-wide analyses of epigenetic modifications; however, it remains difficult to analyze the states of histone modifications at a single-cell resolution in living multicellular organisms because of the heterogeneity within cellular populations. Here we describe a simple method to visualize histone modifications on the specific sequence of target locus at a single-cell resolution in living Caenorhabditis elegans , by combining the LacO/LacI system and a genetically-encoded H4K20me1-specific probe, "mintbody". We demonstrate that Venus-labeled mintbody and mTurquoise2-labeled LacI can co-localize on an artificial chromosome carrying both the target locus and LacO sequences, where H4K20me1 marks the target locus. We demonstrate that our visualization method can precisely detect H4K20me1 depositions on the her-1 gene sequences on the artificial chromosome, to which the dosage compensation complex binds to regulate sex determination. The degree of H4K20me1 deposition on the her-1 sequences on the artificial chromosome correlated strongly with sex, suggesting that, using the artificial chromosome, this method can reflect context-dependent changes of H4K20me1 on endogenous genomes. Furthermore, we demonstrate live imaging of H4K20me1 depositions on the artificial chromosome. Combined with ChIP assays, this mintbody-LacO/LacI visualization method will enable analysis of developmental and context-dependent alterations of locus-specific histone modifications in specific cells and elucidation of the underlying molecular mechanisms. Copyright © 2018, G3: Genes, Genomes, Genetics.

Mass Spectrometry of Single GABAergic Somatic Motorneurons Identifies a Novel Inhibitory Peptide, As-NLP-22, in the Nematode Ascaris suum.

PubMed

Konop, Christopher J; Knickelbine, Jennifer J; Sygulla, Molly S; Wruck, Colin D; Vestling, Martha M; Stretton, Antony O W

2015-12-01

Neuromodulators have become an increasingly important component of functional circuits, dramatically changing the properties of both neurons and synapses to affect behavior. To explore the role of neuropeptides in Ascaris suum behavior, we devised an improved method for cleanly dissecting single motorneuronal cell bodies from the many other cell processes and hypodermal tissue in the ventral nerve cord. We determined their peptide content using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). The reduced complexity of the peptide mixture greatly aided the detection of peptides; peptide levels were sufficient to permit sequencing by tandem MS from single cells. Inhibitory motorneurons, known to be GABAergic, contain a novel neuropeptide, As-NLP-22 (SLASGRWGLRPamide). From this sequence and information from the A. suum expressed sequence tag (EST) database, we cloned the transcript (As-nlp-22) and synthesized a riboprobe for in situ hybridization, which labeled the inhibitory motorneurons; this validates the integrity of the dissection method, showing that the peptides detected originate from the cells themselves and not from adhering processes from other cells (e.g., synaptic terminals). Synthetic As-NLP-22 has potent inhibitory activity on acetylcholine-induced muscle contraction as well as on basal muscle tone. Both of these effects are dose-dependent: the inhibitory effect on ACh contraction has an IC50 of 8.3 × 10(-9) M. When injected into whole worms, As-NLP-22 produces a dose-dependent inhibition of locomotory movements and, at higher levels, complete paralysis. These experiments demonstrate the utility of MALDI TOF/TOF MS in identifying novel neuromodulators at the single-cell level. Graphical Abstract ᅟ.

Mass Spectrometry of Single GABAergic Somatic Motorneurons Identifies a Novel Inhibitory Peptide, As-NLP-22, in the Nematode Ascaris suum

NASA Astrophysics Data System (ADS)

Konop, Christopher J.; Knickelbine, Jennifer J.; Sygulla, Molly S.; Wruck, Colin D.; Vestling, Martha M.; Stretton, Antony O. W.

2015-12-01

Neuromodulators have become an increasingly important component of functional circuits, dramatically changing the properties of both neurons and synapses to affect behavior. To explore the role of neuropeptides in Ascaris suum behavior, we devised an improved method for cleanly dissecting single motorneuronal cell bodies from the many other cell processes and hypodermal tissue in the ventral nerve cord. We determined their peptide content using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). The reduced complexity of the peptide mixture greatly aided the detection of peptides; peptide levels were sufficient to permit sequencing by tandem MS from single cells. Inhibitory motorneurons, known to be GABAergic, contain a novel neuropeptide, As-NLP-22 (SLASGRWGLRPamide). From this sequence and information from the A. suum expressed sequence tag (EST) database, we cloned the transcript ( As-nlp-22) and synthesized a riboprobe for in situ hybridization, which labeled the inhibitory motorneurons; this validates the integrity of the dissection method, showing that the peptides detected originate from the cells themselves and not from adhering processes from other cells (e.g., synaptic terminals). Synthetic As-NLP-22 has potent inhibitory activity on acetylcholine-induced muscle contraction as well as on basal muscle tone. Both of these effects are dose-dependent: the inhibitory effect on ACh contraction has an IC50 of 8.3 × 10-9 M. When injected into whole worms, As-NLP-22 produces a dose-dependent inhibition of locomotory movements and, at higher levels, complete paralysis. These experiments demonstrate the utility of MALDI TOF/TOF MS in identifying novel neuromodulators at the single-cell level.

Multiple regulatory mechanisms of hepatocyte growth factor expression in malignant cells with a short poly(dA) sequence in the HGF gene promoter.

PubMed

Sakai, Kazuko; Takeda, Masayuki; Okamoto, Isamu; Nakagawa, Kazuhiko; Nishio, Kazuto

2015-01-01

Hepatocyte growth factor (HGF) expression is a poor prognostic factor in various types of cancer. Expression levels of HGF have been reported to be regulated by shorter poly(dA) sequences in the promoter region. In the present study, the poly(dA) mononucleotide tract in various types of human cancer cell lines was examined and compared with the HGF expression levels in those cells. Short deoxyadenosine repeat sequences were detected in five of the 55 cell lines used in the present study. The H69, IM95, CCK-81, Sui73 and H28 cells exhibited a truncated poly(dA) sequence in which the number of poly(dA) repeats was reduced by ≥5 bp. Two of the cell lines exhibited high HGF expression, determined by reverse transcription quantitative polymerase chain reaction and enzyme-linked immunosorbent assay. The CCK-81, Sui73 and H28 cells with shorter poly(dA) sequences exhibited low HGF expression. The cause of the suppression of HGF expression in the CCK-81, Sui73 and H28 cells was clarified by two approaches, suppression by methylation and single nucleotide polymorphisms in the HGF gene. Exposure to 5-Aza-dC, an inhibitor of DNA methyltransferase 1, induced an increased expression of HGF in the CCK-81 cells, but not in the other cells. Single-nucleotide polymorphism (SNP) rs72525097 in intron 1 was detected in the Sui73 and H28 cells. Taken together, it was found that the defect of poly(dA) in the HGF promoter was present in various types of cancer, including lung, stomach, colorectal, pancreas and mesothelioma. The present study proposes the negative regulation mechanisms by methylation and SNP in intron 1 of HGF for HGF expression in cancer cells with short poly(dA).

Single-cell RNA sequencing highlights transcription activity of autophagy-related genes during hematopoietic stem cell formation in mouse embryos.

PubMed

Hu, Yongfei; Huang, Yan; Yi, Ying; Wang, Hongwei; Liu, Bing; Yu, Jia; Wang, Dong

2017-04-03

Accumulating evidence has demonstrated that macroautophagy/autophagy plays an essential role in self-renewal and differentiation in embryonic hematopoiesis. Here, according to the RNA sequencing data sets of 5 population cells related to hematopoietic stem cell (HSC) formation during mouse embryogenesis (endothelial cells, PTPRC/CD45 - and PTPRC/CD45 + pre-HSCs in the E11 aorta-gonad-mesonephros (AGM) region, mature HSCs in E12 and E14 fetal liver), we explored the dynamic expression of mouse autophagy-related genes in this course at the single-cell level. Our results revealed that the transcription activity of autophagy-related genes had a substantial increase when endothelial cells (ECs) specified into pre-HSCs, and the upregulation of autophagy-essential genes correlated with reduced NOTCH signaling in pre-HSCs, suggesting the autophagy activity may be greatly enhanced during pre-HSC specification from endothelial precursors. In summary, our results presented strong evidence that autophagy plays a critical role in HSC emergence during mouse midgestation.

Single-Cell RNA Sequencing Reveals T Helper Cells Synthesizing Steroids De Novo to Contribute to Immune Homeostasis

PubMed Central

Mahata, Bidesh; Zhang, Xiuwei; Kolodziejczyk, Aleksandra A.; Proserpio, Valentina; Haim-Vilmovsky, Liora; Taylor, Angela E.; Hebenstreit, Daniel; Dingler, Felix A.; Moignard, Victoria; Göttgens, Berthold; Arlt, Wiebke; McKenzie, Andrew N.J.; Teichmann, Sarah A.

2014-01-01

Summary T helper 2 (Th2) cells regulate helminth infections, allergic disorders, tumor immunity, and pregnancy by secreting various cytokines. It is likely that there are undiscovered Th2 signaling molecules. Although steroids are known to be immunoregulators, de novo steroid production from immune cells has not been previously characterized. Here, we demonstrate production of the steroid pregnenolone by Th2 cells in vitro and in vivo in a helminth infection model. Single-cell RNA sequencing and quantitative PCR analysis suggest that pregnenolone synthesis in Th2 cells is related to immunosuppression. In support of this, we show that pregnenolone inhibits Th cell proliferation and B cell immunoglobulin class switching. We also show that steroidogenic Th2 cells inhibit Th cell proliferation in a Cyp11a1 enzyme-dependent manner. We propose pregnenolone as a “lymphosteroid,” a steroid produced by lymphocytes. We speculate that this de novo steroid production may be an intrinsic phenomenon of Th2-mediated immune responses to actively restore immune homeostasis. PMID:24813893

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

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.

P53 Gene Mutagenesis in Breast Cancer

DTIC Science & Technology

2005-03-01

the wild type T peak. 12 Table 1. Sonic ntations dected by SINtA Individual Cell Sequence Amino Acid Species Conservation 3 ID’ ID Change2 Change... differences in the content of toxic substances in the diet (Biggs et al., 1993; Blaszyk et al., 1996). The development of this p53 mutation load...Changes in the P53 Gene in Single Cells Individual Sequence Amino acid Species conservation ’ ID’ Cell ID change’ change Monkey Mouse Rat Chicken

Tn5Prime, a Tn5 based 5' capture method for single cell RNA-seq.

PubMed

Cole, Charles; Byrne, Ashley; Beaudin, Anna E; Forsberg, E Camilla; Vollmers, Christopher

2018-06-01

RNA-sequencing (RNA-seq) is a powerful technique to investigate and quantify entire transcriptomes. Recent advances in the field have made it possible to explore the transcriptomes of single cells. However, most widely used RNA-seq protocols fail to provide crucial information regarding transcription start sites. Here we present a protocol, Tn5Prime, that takes advantage of the Tn5 transposase-based Smart-seq2 protocol to create RNA-seq libraries that capture the 5' end of transcripts. The Tn5Prime method dramatically streamlines the 5' capture process and is both cost effective and reliable. By applying Tn5Prime to bulk RNA and single cell samples, we were able to define transcription start sites as well as quantify transcriptomes at high accuracy and reproducibility. Additionally, similar to 3' end-based high-throughput methods like Drop-seq and 10× Genomics Chromium, the 5' capture Tn5Prime method allows the introduction of cellular identifiers during reverse transcription, simplifying the analysis of large numbers of single cells. In contrast to 3' end-based methods, Tn5Prime also enables the assembly of the variable 5' ends of the antibody sequences present in single B-cell data. Therefore, Tn5Prime presents a robust tool for both basic and applied research into the adaptive immune system and beyond.

Single-cell barcoding and sequencing using droplet microfluidics.

PubMed

Zilionis, Rapolas; Nainys, Juozas; Veres, Adrian; Savova, Virginia; Zemmour, David; Klein, Allon M; Mazutis, Linas

2017-01-01

Single-cell RNA sequencing has recently emerged as a powerful tool for mapping cellular heterogeneity in diseased and healthy tissues, yet high-throughput methods are needed for capturing the unbiased diversity of cells. Droplet microfluidics is among the most promising candidates for capturing and processing thousands of individual cells for whole-transcriptome or genomic analysis in a massively parallel manner with minimal reagent use. We recently established a method called inDrops, which has the capability to index >15,000 cells in an hour. A suspension of cells is first encapsulated into nanoliter droplets with hydrogel beads (HBs) bearing barcoding DNA primers. Cells are then lysed and mRNA is barcoded (indexed) by a reverse transcription (RT) reaction. Here we provide details for (i) establishing an inDrops platform (1 d); (ii) performing hydrogel bead synthesis (4 d); (iii) encapsulating and barcoding cells (1 d); and (iv) RNA-seq library preparation (2 d). inDrops is a robust and scalable platform, and it is unique in its ability to capture and profile >75% of cells in even very small samples, on a scale of thousands or tens of thousands of cells.

Visualization and Enumeration of Bacteria Carrying a Specific Gene Sequence by In Situ Rolling Circle Amplification

PubMed Central

Maruyama, Fumito; Kenzaka, Takehiko; Yamaguchi, Nobuyasu; Tani, Katsuji; Nasu, Masao

2005-01-01

Rolling circle amplification (RCA) generates large single-stranded and tandem repeats of target DNA as amplicons. This technique was applied to in situ nucleic acid amplification (in situ RCA) to visualize and count single Escherichia coli cells carrying a specific gene sequence. The method features (i) one short target sequence (35 to 39 bp) that allows specific detection; (ii) maintaining constant fluorescent intensity of positive cells permeabilized extensively after amplicon detection by fluorescence in situ hybridization, which facilitates the detection of target bacteria in various physiological states; and (iii) reliable enumeration of target bacteria by concentration on a gelatin-coated membrane filter. To test our approach, the presence of the following genes were visualized by in situ RCA: green fluorescent protein gene, the ampicillin resistance gene and the replication origin region on multicopy pUC19 plasmid, as well as the single-copy Shiga-like toxin gene on chromosomes inside E. coli cells. Fluorescent antibody staining after in situ RCA also simultaneously identified cells harboring target genes and determined the specificity of in situ RCA. E. coli cells in a nonculturable state from a prolonged incubation were periodically sampled and used for plasmid uptake study. The numbers of cells taking up plasmids determined by in situ RCA was up to 106-fold higher than that measured by selective plating. In addition, in situ RCA allowed the detection of cells taking up plasmids even when colony-forming cells were not detected during the incubation period. By optimizing the cell permeabilization condition for in situ RCA, this method can become a valuable tool for studying free DNA uptake, especially in nonculturable bacteria. PMID:16332770

Missing data and technical variability in single-cell RNA-sequencing experiments.

PubMed

Hicks, Stephanie C; Townes, F William; Teng, Mingxiang; Irizarry, Rafael A

2017-11-06

Until recently, high-throughput gene expression technology, such as RNA-Sequencing (RNA-seq) required hundreds of thousands of cells to produce reliable measurements. Recent technical advances permit genome-wide gene expression measurement at the single-cell level. Single-cell RNA-Seq (scRNA-seq) is the most widely used and numerous publications are based on data produced with this technology. However, RNA-seq and scRNA-seq data are markedly different. In particular, unlike RNA-seq, the majority of reported expression levels in scRNA-seq are zeros, which could be either biologically-driven, genes not expressing RNA at the time of measurement, or technically-driven, genes expressing RNA, but not at a sufficient level to be detected by sequencing technology. Another difference is that the proportion of genes reporting the expression level to be zero varies substantially across single cells compared to RNA-seq samples. However, it remains unclear to what extent this cell-to-cell variation is being driven by technical rather than biological variation. Furthermore, while systematic errors, including batch effects, have been widely reported as a major challenge in high-throughput technologies, these issues have received minimal attention in published studies based on scRNA-seq technology. Here, we use an assessment experiment to examine data from published studies and demonstrate that systematic errors can explain a substantial percentage of observed cell-to-cell expression variability. Specifically, we present evidence that some of these reported zeros are driven by technical variation by demonstrating that scRNA-seq produces more zeros than expected and that this bias is greater for lower expressed genes. In addition, this missing data problem is exacerbated by the fact that this technical variation varies cell-to-cell. Then, we show how this technical cell-to-cell variability can be confused with novel biological results. Finally, we demonstrate and discuss how batch-effects and confounded experiments can intensify the problem. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Tools for Genomic and Transcriptomic Analysis of Microbes at Single-Cell Level

PubMed Central

Chen, Zixi; Chen, Lei; Zhang, Weiwen

2017-01-01

Microbiologists traditionally study population rather than individual cells, as it is generally assumed that the status of individual cells will be similar to that observed in the population. However, the recent studies have shown that the individual behavior of each single cell could be quite different from that of the whole population, suggesting the importance of extending traditional microbiology studies to single-cell level. With recent technological advances, such as flow cytometry, next-generation sequencing (NGS), and microspectroscopy, single-cell microbiology has greatly enhanced the understanding of individuality and heterogeneity of microbes in many biological systems. Notably, the application of multiple ‘omics’ in single-cell analysis has shed light on how individual cells perceive, respond, and adapt to the environment, how heterogeneity arises under external stress and finally determines the fate of the whole population, and how microbes survive under natural conditions. As single-cell analysis involves no axenic cultivation of target microorganism, it has also been demonstrated as a valuable tool for dissecting the microbial ‘dark matter.’ In this review, current state-of-the-art tools and methods for genomic and transcriptomic analysis of microbes at single-cell level were critically summarized, including single-cell isolation methods and experimental strategies of single-cell analysis with NGS. In addition, perspectives on the future trends of technology development in the field of single-cell analysis was also presented. PMID:28979258

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.

Natural killer cell receptor genes in the family Equidae: not only Ly49.

PubMed

Futas, Jan; Horin, Petr

2013-01-01

Natural killer (NK) cells have important functions in immunity. NK recognition in mammals can be mediated through killer cell immunoglobulin-like receptors (KIR) and/or killer cell lectin-like Ly49 receptors. Genes encoding highly variable NK cell receptors (NKR) represent rapidly evolving genomic regions. No single conservative model of NKR genes was observed in mammals. Single-copy low polymorphic NKR genes present in one mammalian species may expand into highly polymorphic multigene families in other species. In contrast to other non-rodent mammals, multiple Ly49-like genes appear to exist in the horse, while no functional KIR genes were observed in this species. In this study, Ly49 and KIR were sought and their evolution was characterized in the entire family Equidae. Genomic sequences retrieved showed the presence of at least five highly conserved polymorphic Ly49 genes in horses, asses and zebras. These findings confirmed that the expansion of Ly49 occurred in the entire family. Several KIR-like sequences were also identified in the genome of Equids. Besides a previously identified non-functional KIR-Immunoglobulin-like transcript fusion gene (KIR-ILTA) and two putative pseudogenes, a KIR3DL-like sequence was analyzed. In contrast to previous observations made in the horse, the KIR3DL sequence, genomic organization and mRNA expression suggest that all Equids might produce a functional KIR receptor protein molecule with a single non-mutated immune tyrosine-based inhibition motif (ITIM) domain. No evidence for positive selection in the KIR3DL gene was found. Phylogenetic analysis including rhinoceros and tapir genomic DNA and deduced amino acid KIR-related sequences showed differences between families and even between species within the order Perissodactyla. The results suggest that the order Perissodactyla and its family Equidae with expanded Ly49 genes and with a potentially functional KIR gene may represent an interesting model for evolutionary biology of NKR genes.

Natural Killer Cell Receptor Genes in the Family Equidae: Not only Ly49

PubMed Central

Futas, Jan; Horin, Petr

2013-01-01

Natural killer (NK) cells have important functions in immunity. NK recognition in mammals can be mediated through killer cell immunoglobulin-like receptors (KIR) and/or killer cell lectin-like Ly49 receptors. Genes encoding highly variable NK cell receptors (NKR) represent rapidly evolving genomic regions. No single conservative model of NKR genes was observed in mammals. Single-copy low polymorphic NKR genes present in one mammalian species may expand into highly polymorphic multigene families in other species. In contrast to other non-rodent mammals, multiple Ly49-like genes appear to exist in the horse, while no functional KIR genes were observed in this species. In this study, Ly49 and KIR were sought and their evolution was characterized in the entire family Equidae. Genomic sequences retrieved showed the presence of at least five highly conserved polymorphic Ly49 genes in horses, asses and zebras. These findings confirmed that the expansion of Ly49 occurred in the entire family. Several KIR-like sequences were also identified in the genome of Equids. Besides a previously identified non-functional KIR-Immunoglobulin-like transcript fusion gene (KIR-ILTA) and two putative pseudogenes, a KIR3DL-like sequence was analyzed. In contrast to previous observations made in the horse, the KIR3DL sequence, genomic organization and mRNA expression suggest that all Equids might produce a functional KIR receptor protein molecule with a single non-mutated immune tyrosine-based inhibition motif (ITIM) domain. No evidence for positive selection in the KIR3DL gene was found. Phylogenetic analysis including rhinoceros and tapir genomic DNA and deduced amino acid KIR-related sequences showed differences between families and even between species within the order Perissodactyla. The results suggest that the order Perissodactyla and its family Equidae with expanded Ly49 genes and with a potentially functional KIR gene may represent an interesting model for evolutionary biology of NKR genes. PMID:23724088

Parabiosis and single-cell RNA sequencing reveal a limited contribution of monocytes to myofibroblasts in kidney fibrosis.

PubMed

Kramann, Rafael; Machado, Flavia; Wu, Haojia; Kusaba, Tetsuro; Hoeft, Konrad; Schneider, Rebekka K; Humphreys, Benjamin D

2018-05-03

Fibrosis is the common final pathway of virtually all chronic injury to the kidney. While it is well accepted that myofibroblasts are the scar-producing cells in the kidney, their cellular origin is still hotly debated. The relative contribution of proximal tubular epithelium and circulating cells, including mesenchymal stem cells, macrophages, and fibrocytes, to the myofibroblast pool remains highly controversial. Using inducible genetic fate tracing of proximal tubular epithelium, we confirm that the proximal tubule does not contribute to the myofibroblast pool. However, in parabiosis models in which one parabiont is genetically labeled and the other is unlabeled and undergoes kidney fibrosis, we demonstrate that a small fraction of genetically labeled renal myofibroblasts derive from the circulation. Single-cell RNA sequencing confirms this finding but indicates that these cells are circulating monocytes, express few extracellular matrix or other myofibroblast genes, and express many proinflammatory cytokines. We conclude that this small circulating myofibroblast progenitor population contributes to renal fibrosis by paracrine rather than direct mechanisms.

Single-cell RNA sequencing reveals metallothionein heterogeneity during hESC differentiation to definitive endoderm.

PubMed

Lu, Junjie; Baccei, Anna; Lummertz da Rocha, Edroaldo; Guillermier, Christelle; McManus, Sean; Finney, Lydia A; Zhang, Cheng; Steinhauser, Matthew L; Li, Hu; Lerou, Paul H

2018-04-01

Differentiation of human pluripotent stem cells towards definitive endoderm (DE) is the critical first step for generating cells comprising organs such as the gut, liver, pancreas and lung. This in-vitro differentiation process generates a heterogeneous population with a proportion of cells failing to differentiate properly and maintaining expression of pluripotency factors such as Oct4. RNA sequencing of single cells collected at four time points during a 4-day DE differentiation identified high expression of metallothionein genes in the residual Oct4-positive cells that failed to differentiate to DE. Using X-ray fluorescence microscopy and multi-isotope mass spectrometry, we discovered that high intracellular zinc level corresponds with persistent Oct4 expression and failure to differentiate. This study improves our understanding of the cellular heterogeneity during in-vitro directed differentiation and provides a valuable resource to improve DE differentiation efficiency. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor.

PubMed

Crow, Megan; Paul, Anirban; Ballouz, Sara; Huang, Z Josh; Gillis, Jesse

2018-02-28

Single-cell RNA-sequencing (scRNA-seq) technology provides a new avenue to discover and characterize cell types; however, the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine its replicability. Meta-analysis is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that quantifies the degree to which cell types replicate across datasets, and enables rapid identification of clusters with high similarity. We first measure the replicability of neuronal identity, comparing results across eight technically and biologically diverse datasets to define best practices for more complex assessments. We then apply this to novel interneuron subtypes, finding that 24/45 subtypes have evidence of replication, which enables the identification of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types with high accuracy, suggesting a general route forward for large-scale evaluation of scRNA-seq data.

Verification of 2A peptide cleavage.

PubMed

Szymczak-Workman, Andrea L; Vignali, Kate M; Vignali, Dario A A

2012-02-01

The need for reliable, multicistronic vectors for multigene delivery is at the forefront of biomedical technology. It is now possible to express multiple proteins from a single open reading frame (ORF) using 2A peptide-linked multicistronic vectors. These small sequences, when cloned between genes, allow for efficient, stoichiometric production of discrete protein products within a single vector through a novel "cleavage" event within the 2A peptide sequence. The easiest and most effective way to assess 2A cleavage is to perform transient transfection of 293T cells (human embryonic kidney cells) followed by western blot analysis, as described in this protocol. 293T cells are easy to grow and can be efficiently transfected with a variety of vectors. Cleavage can be assessed by detection with antibodies against the target proteins or anti-2A serum.

Direct Measurement of T Cell Receptor Affinity and Sequence from Naïve Anti-Viral T Cells

PubMed Central

Zhang, Shuqi; Parker, Patricia; Ma, Keyue; He, Chenfeng; Shi, Qian; Cui, Zhonghao; Williams, Chad; Wendel, Ben S.; Meriwether, Amanda; Salazar, Mary A.; Jiang, Ning

2016-01-01

T cells recognize and kill a myriad of pathogen-infected or cancer cells using a diverse set of T cell receptors (TCR). The affinity of TCR to cognate antigen is of high interest in adoptive T cell transfer immunotherapy and antigen-specific T cell repertoire immune profiling because it is widely known to correlate with downstream T cell responses. Here, we introduce the in situ TCR affinity and sequence test (iTAST) for simultaneous measurement of TCR affinity and sequence from single primary CD8+ T cells in human blood. We demonstrate that the repertoire of primary antigen-specific T cells from pathogen inexperienced individuals has a surprisingly broad affinity range of 1000-fold composed of diverse TCR sequences. Within this range, samples from older individuals contained a reduced frequency of high affinity T cells compared to young individuals, demonstrating an age-related effect of T cell attrition that could cause holes in the repertoire. iTAST should enable the rapid selection of high affinity TCRs ex vivo for adoptive immunotherapy and measurement of T cell response for immune monitoring applications. PMID:27252176

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

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

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

Determination of EGFR mutations in single cells microdissected from enriched lung tumor cells in peripheral blood.

PubMed

Ran, Ran; Li, Longyun; Wang, Mengzhao; Wang, Shulan; Zheng, Zhi; Lin, Peter Ping

2013-09-01

A minimally invasive and repeatable approach for real-time epidermal growth factor receptor (EGFR) mutation surveillance would be highly beneficial for individualized therapy of late stage lung cancer patients whose surgical specimens are often not available. We aim to develop a viable method to detect EGFR mutations in single circulating tumor cells (CTCs). Using a model CTC system of spiked tumor cells in whole blood, we evaluated EGFR mutation determination in single tumor cells enriched from blood. We used magnetic beads labeled with antibody against leukocyte surface antigens to deplete leukocytes and enrich native CTCs independent of epithelial marker expression level. We then used laser cell microdissection (LCM) to isolate individual CTCs, followed by whole-genome amplification of the DNA for exon 19 microdeletion, L858R and T790M mutation detection by PCR sequencing. EGFR mutations were successfully measured in individual spiked tumor cells enriched from 7.5 ml whole blood. Whole-genome amplification provided sufficient DNA for mutation determination at multiple sites. Ninety-five percent of the single CTCs microdissected by LCM (19/20) yielded PCR amplicons for at least one of the three mutation sites. The amplification success rates were 55 % (11/20) for exon 19 deletion, 45 % (9/20) for T790M, and 85 % (17/20) for L858R. Sequencing of the amplicons showed allele dropout in the amplification reactions, but mutations were correctly identified in 80 % of the amplicons. EGFR mutation determination from single captured tumor cells from blood is feasible with the approach described here. However, to overcome allele dropout and to obtain reliable information about the tumor's EGFR status, multiple individual tumor cells should be assayed.

Clustering Single-Cell Expression Data Using Random Forest Graphs.

PubMed

Pouyan, Maziyar Baran; Nourani, Mehrdad

2017-07-01

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

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.

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

PubMed

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

2018-06-01

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

Very Low Abundance Single-Cell Transcript Quantification with 5-Plex ddPCRTM Assays.

PubMed

Karlin-Neumann, George; Zhang, Bin; Litterst, Claudia

2018-01-01

Gene expression studies have provided one of the most accessible windows for understanding the molecular basis of cell and tissue phenotypes and how these change in response to stimuli. Current PCR-based and next generation sequencing methods offer great versatility in allowing the focused study of the roles of small numbers of genes or comprehensive profiling of the entire transcriptome of a sample at one time. Marrying of these approaches to various cell sorting technologies has recently enabled the profiling of expression in single cells, thereby increasing the resolution and sensitivity and strengthening the inferences from observed expression levels and changes. This chapter presents a quick and efficient 1-day workflow for sorting single cells with a small laboratory cell-sorter followed by an ultrahigh sensitivity, multiplexed digital PCR method for quantitative tracking of changes in 5-10 genes per single cell.

Spectrum of benzo[a]pyrene-induced mutations in the Pig-a gene of L5178YTk+/- cells identified with next generation sequencing.

PubMed

Revollo, Javier; Wang, Yiying; McKinzie, Page; Dad, Azra; Pearce, Mason; Heflich, Robert H; Dobrovolsky, Vasily N

2017-12-01

We used Sanger sequencing and next generation sequencing (NGS) for analysis of mutations in the endogenous X-linked Pig-a gene of clonally expanded L5178YTk +/- cells. The clones developed from single cells that were sorted on a flow cytometer based upon the expression pattern of the GPI-anchored marker, CD90, on their surface. CD90-deficient and CD90-proficient cells were sorted from untreated cultures and CD90-deficient cells were sorted from cultures treated with benzo[a]pyrene (B[a]P). Pig-a mutations were identified in all clones developed from CD90-deficient cells; no Pig-a mutations were found in clones of CD90-proficient cells. The spectrum of B[a]P-induced Pig-a mutations was dominated by basepair substitutions, small insertions and deletions at G:C, or at sequences rich in G:C content. We observed high concordance between Pig-a mutations determined by Sanger sequencing and by NGS, but NGS was able to identify mutations in samples that were difficult to analyze by Sanger sequencing (e.g., mixtures of two mutant clones). Overall, the NGS method is a cost and labor efficient high throughput approach for analysis of a large number of mutant clones. Published by Elsevier B.V.

Transcriptional Noise and Somatic Mutations in the Aging Pancreas.

PubMed

Swisa, Avital; Kaestner, Klaus H; Dor, Yuval

2017-12-05

The underlying mechanisms and functional significance of pancreatic β cell heterogeneity are an intensive area of investigation. In a recent Cell paper, Enge and colleagues (2017) performed single-cell RNA sequencing of human pancreatic cells and concluded that with age, pancreatic cells become transcriptionally noisy and accumulate somatic mutations. Copyright © 2017. Published by Elsevier Inc.

Low incidence of DNA sequence variation in human induced pluripotent stem cells generated by non-integrating plasmid expression

PubMed Central

Cheng, Linzhao; Hansen, Nancy F.; Zhao, Ling; Du, Yutao; Zou, Chunlin; Donovan, Frank X.; Chou, Bin-Kuan; Zhou, Guangyu; Li, Shijie; Dowey, Sarah N.; Ye, Zhaohui; Chandrasekharappa, Settara C.; Yang, Huanming; Mullikin, James C.; Liu, P. Paul

2012-01-01

Summary The utility of induced pluripotent stem cells (iPSCs) as models to study diseases and as sources for cell therapy depends on the integrity of their genomes. Despite recent publications of DNA sequence variations in the iPSCs, the true scope of such changes for the entire genome is not clear. Here we report the whole-genome sequencing of three human iPSC lines derived from two cell types of an adult donor by episomal vectors. The vector sequence was undetectable in the deeply sequenced iPSC lines. We identified 1058–1808 heterozygous single nucleotide variants (SNVs), but no copy number variants, in each iPSC line. Six to twelve of these SNVs were within coding regions in each iPSC line, but ~50% of them are synonymous changes and the remaining are not selectively enriched for known genes associated with cancers. Our data thus suggest that episome-mediated reprogramming is not inherently mutagenic during integration-free iPSC induction. PMID:22385660

The structure of cell adhesion molecule uvomorulin. Insights into the molecular mechanism of Ca2+-dependent cell adhesion.

PubMed Central

Ringwald, M; Schuh, R; Vestweber, D; Eistetter, H; Lottspeich, F; Engel, J; Dölz, R; Jähnig, F; Epplen, J; Mayer, S

1987-01-01

We have determined the amino acid sequence of the Ca2+-dependent cell adhesion molecule uvomorulin as it appears on the cell surface. The extracellular part of the molecule exhibits three internally repeated domains of 112 residues which are most likely generated by gene duplication. Each of the repeated domains contains two highly conserved units which could represent putative Ca2+-binding sites. Secondary structure predictions suggest that the putative Ca2+-binding units are located in external loops at the surface of the protein. The protein sequence exhibits a single membrane-spanning region and a cytoplasmic domain. Sequence comparison reveals extensive homology to the chicken L-CAM. Both uvomorulin and L-CAM are identical in 65% of their entire amino acid sequence suggesting a common origin for both CAMs. Images Fig. 1. Fig. 4. Fig. 7. PMID:3501370

Single-cell sequencing deciphers a convergent evolution of copy number alterations from primary to circulating tumor cells.

PubMed

Gao, Yan; Ni, Xiaohui; Guo, Hua; Su, Zhe; Ba, Yi; Tong, Zhongsheng; Guo, Zhi; Yao, Xin; Chen, Xixi; Yin, Jian; Yan, Zhao; Guo, Lin; Liu, Ying; Bai, Fan; Xie, X Sunney; Zhang, Ning

2017-08-01

Copy number alteration (CNA) is a major contributor to genome instability, a hallmark of cancer. Here, we studied genomic alterations in single primary tumor cells and circulating tumor cells (CTCs) from the same patient. Single-nucleotide variants (SNVs) in single cells from both samples occurred sporadically, whereas CNAs among primary tumor cells emerged accumulatively rather than abruptly, converging toward the CNA in CTCs. Focal CNAs affecting the MYC gene and the PTEN gene were observed only in a minor portion of primary tumor cells but were present in all CTCs, suggesting a strong selection toward metastasis. Single-cell structural variant (SV) analyses revealed a two-step mechanism, a complex rearrangement followed by gene amplification, for the simultaneous formation of anomalous CNAs in multiple chromosome regions. Integrative CNA analyses of 97 CTCs from 23 patients confirmed the convergence of CNAs and revealed single, concurrent, and mutually exclusive CNAs that could be the driving events in cancer metastasis. © 2017 Gao et al.; Published by Cold Spring Harbor Laboratory Press.

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 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

Enabling multiplexed testing of pooled donor cells through whole-genome sequencing.

PubMed

Chan, Yingleong; Chan, Ying Kai; Goodman, Daniel B; Guo, Xiaoge; Chavez, Alejandro; Lim, Elaine T; Church, George M

2018-04-19

We describe a method that enables the multiplex screening of a pool of many different donor cell lines. Our method accurately predicts each donor proportion from the pool without requiring the use of unique DNA barcodes as markers of donor identity. Instead, we take advantage of common single nucleotide polymorphisms, whole-genome sequencing, and an algorithm to calculate the proportions from the sequencing data. By testing using simulated and real data, we showed that our method robustly predicts the individual proportions from a mixed-pool of numerous donors, thus enabling the multiplexed testing of diverse donor cells en masse.More information is available at https://pgpresearch.med.harvard.edu/poolseq/.

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.

Detection of BRAF mutations from solid tumors using Tumorplex™ technology

PubMed Central

Yo, Jacob; Hay, Katie S.L.; Vinayagamoorthy, Dilanthi; Maryanski, Danielle; Carter, Mark; Wiegel, Joseph; Vinayagamoorthy, Thuraiayah

2015-01-01

Allele specific multiplex sequencing (Tumorplex™) is a new molecular platform for the detection of single base mutation in tumor biopsies with high sensitivity for clinical testing. Tumorplex™ is a novel modification of Sanger sequencing technology that generates both mutant and wild type nucleotide sequences simultaneously in the same electropherogram. The molecular weight of the two sequencing primers are different such that the two sequences generated are separated, thus eliminating possible suppression of mutant signal by the more abundant wild type signal. Tumorplex™ platform technology was tested using BRAF mutation V600E. These studies were performed with cloned BRAF mutations and genomic DNA extracted from tumor cells carrying 50% mutant allele. The lower limit of detection for BRAF V600E was found to be 20 genome equivalents (GE) using genomic DNA extracted from mutation specific cell lines. Sensitivity of the assay was tested by challenging the mutant allele with wild type allele at 20 GE, and was able to detect BRAF mutant signal at a GE ration of 20:1 × 107 (mutant to wild-type). This level of sensitivity can detect low abundance of clonal mutations in tumor biopsies and eliminate the need for cell enrichment. • Tumorplex™ is a single tube assay that permits the recognition of mutant allele without suppression by wildtype signal. • Tumorplex™ provides a high level of sensitivity. • Tumorplex™ can be used with small sample size with mixed population of cells carrying heterogeneous gDNA. PMID:26258049

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.

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

PubMed

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

2017-10-01

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

T-cell receptor repertoire of human peripheral CD161hiTRAV1-2+ MAIT cells revealed by next generation sequencing and single cell analysis.

PubMed

Held, Kathrin; Beltrán, Eduardo; Moser, Markus; Hohlfeld, Reinhard; Dornmair, Klaus

2015-09-01

Mucosal-associated invariant T (MAIT) cells are a T-cell subset that expresses a conserved TRAV1-2 (Vα7.2) T-cell receptor (TCR) chain and the surface marker CD161. They are involved in the defence against microbes as they recognise small organic molecules of microbial origin that are presented by the non-classical MHC molecule 1 (MR1). MAIT cells express a semi-restricted TCR α chain with TRAV1-2 preferentially linked to TRAJ33, TRAJ12, or TRAJ20 which pairs with a limited set of β chains. To investigate the TCR repertoire of human CD161(hi)TRAV1-2(+) T cells in depth we analysed the α and β chains of this T-cell subset by next generation sequencing. Concomitantly we analysed 132 paired α and β chains from single cells to assess the αβ pairing preferences. We found that the CD161(hi)TRAV1-2(+) TCR repertoire in addition to the typical MAIT TCRs further contains polyclonal elements reminiscent of classical αβ T cells. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

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

PubMed

de Vargas Roditi, Laura; Claassen, Manfred

2015-08-01

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

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.

Comprehensive profiling and quantitation of oncogenic mutations in non-small cell lung carcinoma using single-molecule amplification and re-sequencing technology.

PubMed

Shi, Jian; Yuan, Meng; Wang, Zhan-Dong; Xu, Xiao-Li; Hong, Lei; Sun, Shenglin

2017-02-01

The carcinogenesis of non-small cell lung carcinoma has been found to associate with activating and resistant mutations in the tyrosine kinase domain of specific oncogenes. Here, we assessed the type, frequency, and abundance of epithelial growth factor receptor, KRAS, BRAF, and ALK mutations in 154 non-small cell lung carcinoma specimens using single-molecule amplification and re-sequencing technology. We found that epithelial growth factor receptor mutations were the most prevalent (44.2%), followed by KRAS (18.8%), ALK (7.8%), and BRAF (5.8%) mutations. The type and abundance of the mutations in tumor specimens appeared to be heterogeneous. Thus, we conclude that identification of clinically significant oncogenic mutations may improve the classification of patients and provide valuable information for determination of the therapeutic strategies.

Whole exome sequencing to estimate alloreactivity potential between donors and recipients in stem cell transplantation

PubMed Central

Sampson, Juliana K.; Sheth, Nihar U.; Koparde, Vishal N.; Scalora, Allison F.; Serrano, Myrna G.; Lee, Vladimir; Roberts, Catherine H.; Jameson-Lee, Max; Ferreira-Gonzalez, Andrea; Manjili, Masoud H.; Buck, Gregory A.; Neale, Michael C.; Toor, Amir A.

2016-01-01

Summary Whole exome sequencing (WES) was performed on stem cell transplant donor-recipient (D-R) pairs to determine the extent of potential antigenic variation at a molecular level. In a small cohort of D-R pairs, a high frequency of sequence variation was observed between the donor and recipient exomes independent of human leucocyte antigen (HLA) matching. Nonsynonymous, nonconservative single nucleotide polymorphisms were approximately twice as frequent in HLA-matched unrelated, compared with related D-R pairs. When mapped to individual chromosomes, these polymorphic nucleotides were uniformly distributed across the entire exome. In conclusion, WES reveals extensive nucleotide sequence variation in the exomes of HLA-matched donors and recipients. PMID:24749631

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

PubMed Central

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

2017-01-01

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

Highly multiplexed subcellular RNA sequencing in situ

PubMed Central

Lee, Je Hyuk; Daugharthy, Evan R.; Scheiman, Jonathan; Kalhor, Reza; Ferrante, Thomas C.; Yang, Joyce L.; Terry, Richard; Jeanty, Sauveur S. F.; Li, Chao; Amamoto, Ryoji; Peters, Derek T.; Turczyk, Brian M.; Marblestone, Adam H.; Inverso, Samuel A.; Bernard, Amy; Mali, Prashant; Rios, Xavier; Aach, John; Church, George M.

2014-01-01

Understanding the spatial organization of gene expression with single nucleotide resolution requires localizing the sequences of expressed RNA transcripts within a cell in situ. Here we describe fluorescent in situ RNA sequencing (FISSEQ), in which stably cross-linked cDNA amplicons are sequenced within a biological sample. Using 30-base reads from 8,742 genes in situ, we examined RNA expression and localization in human primary fibroblasts using a simulated wound healing assay. FISSEQ is compatible with tissue sections and whole mount embryos, and reduces the limitations of optical resolution and noisy signals on single molecule detection. Our platform enables massively parallel detection of genetic elements, including gene transcripts and molecular barcodes, and can be used to investigate cellular phenotype, gene regulation, and environment in situ. PMID:24578530

Molecular cloning of an inducible serine esterase gene from human cytotoxic lymphocytes.

PubMed Central

Trapani, J A; Klein, J L; White, P C; Dupont, B

1988-01-01

A cDNA clone encoding a human serine esterase gene was isolated from a library constructed from poly(A)+ RNA of allogeneically stimulated, interleukin 2-expanded peripheral blood mononuclear cells. The clone, designated HSE26.1, represents a full-length copy of a 0.9-kilobase mRNA present in human cytotoxic cells but absent from a wide variety of noncytotoxic cell lines. Clone HSE26.1 contains an 892-base-pair sequence, including a single 741-base-pair open reading frame encoding a putative 247-residue polypeptide. The first 20 amino acids of the polypeptide form a leader sequence. The mature protein is predicted to have an unglycosylated Mr of approximately equal to 26,000 and contains a single potential site for N-linked glycosylation. The nucleotide and predicted amino acid sequences of clone HSE26.1 are homologous with all murine and human serine esterases cloned thus far but are most similar to mouse granzyme B (70% nucleotide and 68% amino acid identity). HSE26.1 protein is expressed weakly in unstimulated peripheral blood mononuclear cells but is strongly induced within 6-hr incubation in medium containing phytohemagglutinin. The data suggest that the protein encoded by HSE26.1 plays a role in cell-mediated cytotoxicity. Images PMID:3261871

Visualizing Clonal Evolution in Cancer.

PubMed

Krzywinski, Martin

2016-06-02

Rapid and inexpensive single-cell sequencing is driving new visualizations of cancer instability and evolution. Krzywinski discusses how to present clone evolution plots in order to visualize temporal, phylogenetic, and spatial aspects of a tumor in a single static image. Copyright © 2016 Elsevier Inc. All rights reserved.

Molecular phylogeny of choanoflagellates, the sister group to Metazoa

PubMed Central

Carr, M.; Leadbeater, B. S. C.; Hassan, R.; Nelson, M.; Baldauf, S. L.

2008-01-01

Choanoflagellates are single-celled aquatic flagellates with a unique morphology consisting of a cell with a single flagellum surrounded by a “collar” of microvilli. They have long interested evolutionary biologists because of their striking resemblance to the collared cells (choanocytes) of sponges. Molecular phylogeny has confirmed a close relationship between choanoflagellates and Metazoa, and the first choanoflagellate genome sequence has recently been published. However, molecular phylogenetic studies within choanoflagellates are still extremely limited. Thus, little is known about choanoflagellate evolution or the exact nature of the relationship between choanoflagellates and Metazoa. We have sequenced four genes from a broad sampling of the morphological diversity of choanoflagellates including most species currently available in culture. Phylogenetic analyses of these sequences, alone and in combination, reject much of the traditional taxonomy of the group. The molecular data also strongly support choanoflagellate monophyly rejecting proposals that Metazoa were derived from a true choanoflagellate ancestor. Mapping of a complementary matrix of morphological and ecological traits onto the phylogeny allows a reinterpretation of choanoflagellate character evolution and predicts the nature of their last common ancestor. PMID:18922774

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

Nonspatial Sequence Coding in CA1 Neurons

PubMed Central

Allen, Timothy A.; Salz, Daniel M.; McKenzie, Sam

2016-01-01

The hippocampus is critical to the memory for sequences of events, a defining feature of episodic memory. However, the fundamental neuronal mechanisms underlying this capacity remain elusive. While considerable research indicates hippocampal neurons can represent sequences of locations, direct evidence of coding for the memory of sequential relationships among nonspatial events remains lacking. To address this important issue, we recorded neural activity in CA1 as rats performed a hippocampus-dependent sequence-memory task. Briefly, the task involves the presentation of repeated sequences of odors at a single port and requires rats to identify each item as “in sequence” or “out of sequence”. We report that, while the animals' location and behavior remained constant, hippocampal activity differed depending on the temporal context of items—in this case, whether they were presented in or out of sequence. Some neurons showed this effect across items or sequence positions (general sequence cells), while others exhibited selectivity for specific conjunctions of item and sequence position information (conjunctive sequence cells) or for specific probe types (probe-specific sequence cells). We also found that the temporal context of individual trials could be accurately decoded from the activity of neuronal ensembles, that sequence coding at the single-cell and ensemble level was linked to sequence memory performance, and that slow-gamma oscillations (20–40 Hz) were more strongly modulated by temporal context and performance than theta oscillations (4–12 Hz). These findings provide compelling evidence that sequence coding extends beyond the domain of spatial trajectories and is thus a fundamental function of the hippocampus. SIGNIFICANCE STATEMENT The ability to remember the order of life events depends on the hippocampus, but the underlying neural mechanisms remain poorly understood. Here we addressed this issue by recording neural activity in hippocampal region CA1 while rats performed a nonspatial sequence memory task. We found that hippocampal neurons code for the temporal context of items (whether odors were presented in the correct or incorrect sequential position) and that this activity is linked with memory performance. The discovery of this novel form of temporal coding in hippocampal neurons advances our fundamental understanding of the neurobiology of episodic memory and will serve as a foundation for our cross-species, multitechnique approach aimed at elucidating the neural mechanisms underlying memory impairments in aging and dementia. PMID:26843637

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

Random Mutagenesis, Clonal Events, and Embryonic or Somatic Origin Determine the mtDNA Variant Type and Load in Human Pluripotent Stem Cells.

PubMed

Zambelli, Filippo; Mertens, Joke; Dziedzicka, Dominika; Sterckx, Johan; Markouli, Christina; Keller, Alexander; Tropel, Philippe; Jung, Laura; Viville, Stephane; Van de Velde, Hilde; Geens, Mieke; Seneca, Sara; Sermon, Karen; Spits, Claudia

2018-06-07

In this study, we deep-sequenced the mtDNA of human embryonic and induced pluripotent stem cells (hESCs and hiPSCs) and their source cells and found that the majority of variants pre-existed in the cells used to establish the lines. Early-passage hESCs carried few and low-load heteroplasmic variants, similar to those identified in oocytes and inner cell masses. The number and heteroplasmic loads of these variants increased with prolonged cell culture. The study of 120 individual cells of early- and late-passage hESCs revealed a significant diversity in mtDNA heteroplasmic variants at the single-cell level and that the variants that increase during time in culture are always passenger to the appearance of chromosomal abnormalities. We found that early-passage hiPSCs carry much higher loads of mtDNA variants than hESCs, which single-fibroblast sequencing proved pre-existed in the source cells. Finally, we show that these variants are stably transmitted during short-term differentiation. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Intracellular diversity of the V4 and V9 regions of the 18S rRNA in marine protists (radiolarians) assessed by high-throughput sequencing.

PubMed

Decelle, Johan; Romac, Sarah; Sasaki, Eriko; Not, Fabrice; Mahé, Frédéric

2014-01-01

Metabarcoding is a powerful tool for exploring microbial diversity in the environment, but its accurate interpretation is impeded by diverse technical (e.g. PCR and sequencing errors) and biological biases (e.g. intra-individual polymorphism) that remain poorly understood. To help interpret environmental metabarcoding datasets, we investigated the intracellular diversity of the V4 and V9 regions of the 18S rRNA gene from Acantharia and Nassellaria (radiolarians) using 454 pyrosequencing. Individual cells of radiolarians were isolated, and PCRs were performed with generalist primers to amplify the V4 and V9 regions. Different denoising procedures were employed to filter the pyrosequenced raw amplicons (Acacia, AmpliconNoise, Linkage method). For each of the six isolated cells, an average of 541 V4 and 562 V9 amplicons assigned to radiolarians were obtained, from which one numerically dominant sequence and several minor variants were found. At the 97% identity, a diversity metrics commonly used in environmental surveys, up to 5 distinct OTUs were detected in a single cell. However, most amplicons grouped within a single OTU whereas other OTUs contained very few amplicons. Different analytical methods provided evidence that most minor variants forming different OTUs correspond to PCR and sequencing artifacts. Duplicate PCR and sequencing from the same DNA extract of a single cell had only 9 to 16% of unique amplicons in common, and alignment visualization of V4 and V9 amplicons showed that most minor variants contained substitutions in highly-conserved regions. We conclude that intracellular variability of the 18S rRNA in radiolarians is very limited despite its multi-copy nature and the existence of multiple nuclei in these protists. Our study recommends some technical guidelines to conservatively discard artificial amplicons from metabarcoding datasets, and thus properly assess the diversity and richness of protists in the environment.

Tracking single mRNA molecules in live cells

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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.

Distinctive archaebacterial species associated with anaerobic rumen protozoan Entodinium caudatum.

PubMed

Tóthová, T; Piknová, M; Kisidayová, S; Javorský, P; Pristas, P

2008-01-01

The diversity of archaebacteria associated with anaerobic rumen protozoan Entodinium caudatum in long term in vitro culture was investigated by denaturing gradient gel electrophoresis (DGGE) analysis of hypervariable V3 region of archaebacterial 16S rRNA gene. PCR was accomplished directly from DNA extracted from a single protozoal cell and from total community genomic DNA and the obtained fingerprints were compared. The analysis indicated the presence of a solitary intensive band present in Entodinium caudatum single cell DNA, which had no counterparts in the profile from total DNA. The identity of archaebacterium represented by this band was determined by sequence analysis which showed that the sequence fell to the cluster of ciliate symbiotic methanogens identified recently by 16S gene library approach.

Formation of rings from segments of HeLa-cell nuclear deoxyribonucleic acid

PubMed Central

Hardman, Norman

1974-01-01

Duplex segments of HeLa-cell nuclear DNA were generated by cleavage with DNA restriction endonuclease from Haemophilus influenzae. About 20–25% of the DNA segments produced, when partly degraded with exonuclease III and annealed, were found to form rings visible in the electron microscope. A further 5% of the DNA segments formed structures that were branched in configuration. Similar structures were generated from HeLa-cell DNA, without prior treatment with restriction endonuclease, when the complementary polynucleotide chains were exposed by exonuclease III action at single-chain nicks. After exposure of an average single-chain length of 1400 nucleotides per terminus at nicks in HeLa-cell DNA by exonuclease III, followed by annealing, the physical length of ring closures was estimated and found to be 0.02–0.1μm, or 50–300 base pairs. An almost identical distribution of lengths was recorded for the regions of complementary base sequence responsible for branch formation. It is proposed that most of the rings and branches are formed from classes of reiterated base sequence with an average length of 180 base pairs arranged intermittenly in HeLa-cell DNA. From the rate of formation of branched structures when HeLa-cell DNA segments were heat-denatured and annealed, it is estimated that the reiterated sequences are in families containing approximately 2400–24000 copies. ImagesPLATE 2PLATE 1 PMID:4462738

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.

Unbiased Combinatorial Genomic Approaches to Identify Alternative Therapeutic Targets within the TSC Signaling Network

DTIC Science & Technology

2014-06-01

Specifically, we combined the CRISPR genome editing system with a novel approach allowing efficient single cell cloning of Drosophila cells with the aim of...and culture these to produce cultures completely lacking wildtype sequence at the target locus. No robust methods existed to clone single Drosophila ...targeting all kinases and phosphatases (563 genes) in the Drosophila genome . 65 samples that displayed synthetic lethality (15 genes) or synthetic

Expression cloning of human B cell immunoglobulins.

PubMed

Wardemann, Hedda; Kofer, Juliane

2013-01-01

The majority of lymphomas originate from B cells at the germinal center stage or beyond. Preferential selection of B cell clones by a limited set of antigens has been suggested to drive lymphoma development. However, little is known about the specificity of the antibodies expressed by lymphoma cells, and the role of antibody-specificity in lymphomagenesis remains elusive. Here, we describe a strategy to characterize the antibody reactivity of human B cells. The approach allows the unbiased characterization of the human antibody repertoire on a single cell level through the generation of recombinant monoclonal antibodies from single primary human B cells of defined origin. This protocol offers a detailed description of the method starting from the flow cytometric isolation of single human B cells, to the RT-PCR-based amplification of the expressed Igh, Igκ, and Igλ chain genes, and Ig gene expression vector cloning for the in vitro production of monoclonal antibodies. The strategy may be used to obtain information on the clonal evolution of B cell lymphomas by single cell Ig gene sequencing and on the antibody reactivity of human lymphoma B cells.

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

PubMed

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

2017-10-01

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

JingleBells: A Repository of Immune-Related Single-Cell RNA-Sequencing Datasets.

PubMed

Ner-Gaon, Hadas; Melchior, Ariel; Golan, Nili; Ben-Haim, Yael; Shay, Tal

2017-05-01

Recent advances in single-cell RNA-sequencing (scRNA-seq) technology increase the understanding of immune differentiation and activation processes, as well as the heterogeneity of immune cell types. Although the number of available immune-related scRNA-seq datasets increases rapidly, their large size and various formats render them hard for the wider immunology community to use, and read-level data are practically inaccessible to the non-computational immunologist. To facilitate datasets reuse, we created the JingleBells repository for immune-related scRNA-seq datasets ready for analysis and visualization of reads at the single-cell level (http://jinglebells.bgu.ac.il/). To this end, we collected the raw data of publicly available immune-related scRNA-seq datasets, aligned the reads to the relevant genome, and saved aligned reads in a uniform format, annotated for cell of origin. We also added scripts and a step-by-step tutorial for visualizing each dataset at the single-cell level, through the commonly used Integrated Genome Viewer (www.broadinstitute.org/igv/). The uniform scRNA-seq format used in JingleBells can facilitate reuse of scRNA-seq data by computational biologists. It also enables immunologists who are interested in a specific gene to visualize the reads aligned to this gene to estimate cell-specific preferences for splicing, mutation load, or alleles. Thus JingleBells is a resource that will extend the usefulness of scRNA-seq datasets outside the programming aficionado realm. Copyright © 2017 by The American Association of Immunologists, Inc.

SELEX-Based Screening of Exosome-Tropic RNA.

PubMed

Yamashita, Takuma; Shinotsuka, Haruka; Takahashi, Yuki; Kato, Kana; Nishikawa, Makiya; Takakura, Yoshinobu

2017-01-01

Cell-derived nanosized vesicles or exosomes are expected to become delivery carriers for functional RNAs, such as small interfering RNA (siRNA). A method to efficiently load functional RNAs into exosomes is required for the development of exosome-based delivery carriers of functional RNAs. However, there is no method to find exosome-tropic exogenous RNA sequences. In this study, we used a systematic evolution of ligands by exponential enrichment (SELEX) method to screen exosome-tropic RNAs that can be used to load functional RNAs into exosomes by conjugation. Pooled single stranded 80-base RNAs, each of which contains a randomized 40-base sequence, were transfected into B16-BL6 murine melanoma cells and exosomes were collected from the cells. RNAs extracted from the exosomes were subjected to next round of SELEX. Cloning and sequencing of RNAs in SELEX-screened RNA pools showed that 29 of 56 clones had a typical RNA sequence. The sequence found by SELEX was enriched in exosomes after transfection to B16-BL6 cells. The results show that the SELEX-based method can be used for screening of exosome-tropic RNAs.

dropEst: pipeline for accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments.

PubMed

Petukhov, Viktor; Guo, Jimin; Baryawno, Ninib; Severe, Nicolas; Scadden, David T; Samsonova, Maria G; Kharchenko, Peter V

2018-06-19

Recent single-cell RNA-seq protocols based on droplet microfluidics use massively multiplexed barcoding to enable simultaneous measurements of transcriptomes for thousands of individual cells. The increasing complexity of such data creates challenges for subsequent computational processing and troubleshooting of these experiments, with few software options currently available. Here, we describe a flexible pipeline for processing droplet-based transcriptome data that implements barcode corrections, classification of cell quality, and diagnostic information about the droplet libraries. We introduce advanced methods for correcting composition bias and sequencing errors affecting cellular and molecular barcodes to provide more accurate estimates of molecular counts in individual cells.

Compartmentalization of HIV-1 within the female genital tract is due to monotypic and low-diversity variants not distinct viral populations.

PubMed

Bull, Marta; Learn, Gerald; Genowati, Indira; McKernan, Jennifer; Hitti, Jane; Lockhart, David; Tapia, Kenneth; Holte, Sarah; Dragavon, Joan; Coombs, Robert; Mullins, James; Frenkel, Lisa

2009-09-22

Compartmentalization of HIV-1 between the genital tract and blood was noted in half of 57 women included in 12 studies primarily using cell-free virus. To further understand differences between genital tract and blood viruses of women with chronic HIV-1 infection cell-free and cell-associated virus populations were sequenced from these tissues, reasoning that integrated viral DNA includes variants archived from earlier in infection, and provides a greater array of genotypes for comparisons. Multiple sequences from single-genome-amplification of HIV-1 RNA and DNA from the genital tract and blood of each woman were compared in a cross-sectional study. Maximum likelihood phylogenies were evaluated for evidence of compartmentalization using four statistical tests. Genital tract and blood HIV-1 appears compartmentalized in 7/13 women by >/=2 statistical analyses. These subjects' phylograms were characterized by low diversity genital-specific viral clades interspersed between clades containing both genital and blood sequences. Many of the genital-specific clades contained monotypic HIV-1 sequences. In 2/7 women, HIV-1 populations were significantly compartmentalized across all four statistical tests; both had low diversity genital tract-only clades. Collapsing monotypic variants into a single sequence diminished the prevalence and extent of compartmentalization. Viral sequences did not demonstrate tissue-specific signature amino acid residues, differential immune selection, or co-receptor usage. In women with chronic HIV-1 infection multiple identical sequences suggest proliferation of HIV-1-infected cells, and low diversity tissue-specific phylogenetic clades are consistent with bursts of viral replication. These monotypic and tissue-specific viruses provide statistical support for compartmentalization of HIV-1 between the female genital tract and blood. However, the intermingling of these clades with clades comprised of both genital and blood sequences and the absence of tissue-specific genetic features suggests compartmentalization between blood and genital tract may be due to viral replication and proliferation of infected cells, and questions whether HIV-1 in the female genital tract is distinct from blood.

Target sequencing and CRISPR/Cas editing reveal simultaneous loss of UTX and UTY in urothelial bladder cancer.

PubMed

Ahn, Jinwoo; Kim, Kwang Hyun; Park, Sanghui; Ahn, Young-Ho; Kim, Ha Young; Yoon, Hana; Lee, Ji Hyun; Bang, Duhee; Lee, Dong Hyeon

2016-09-27

UTX is a histone demethylase gene located on the X chromosome and is a frequently mutated gene in urothelial bladder cancer (UBC). UTY is a paralog of UTX located on the Y chromosome. We performed target capture sequencing on 128 genes in 40 non-metastatic UBC patients. UTX was the most frequently mutated gene (30%, 12/40). Of the genetic alterations identified, 75% were truncating mutations. UTY copy number loss was detected in 8 male patients (22.8%, 8/35). Of the 9 male patients with UTX mutations, 6 also had copy number loss (66.7%). To evaluate the functional roles of UTX and UTY in tumor progression, we designed UTX and UTY single knockout and UTX-UTY double knockout experiments using a CRISPR/Cas9 lentiviral system, and compared the proliferative capacities of two UBC cell lines in vitro. Single UTX or UTY knockout increased cell proliferation as compared to UTX-UTY wild-type cells. UTX-UTY double knockout cells exhibited greater proliferation than single knockout cells. These findings suggest both UTX and UTY function as dose-dependent suppressors of UBC development. While UTX escapes X chromosome inactivation in females, UTY may function as a male homologue of UTX, which could compensate for dosage imbalances.

Whole exome sequencing to estimate alloreactivity potential between donors and recipients in stem cell transplantation.

PubMed

Sampson, Juliana K; Sheth, Nihar U; Koparde, Vishal N; Scalora, Allison F; Serrano, Myrna G; Lee, Vladimir; Roberts, Catherine H; Jameson-Lee, Max; Ferreira-Gonzalez, Andrea; Manjili, Masoud H; Buck, Gregory A; Neale, Michael C; Toor, Amir A

2014-08-01

Whole exome sequencing (WES) was performed on stem cell transplant donor-recipient (D-R) pairs to determine the extent of potential antigenic variation at a molecular level. In a small cohort of D-R pairs, a high frequency of sequence variation was observed between the donor and recipient exomes independent of human leucocyte antigen (HLA) matching. Nonsynonymous, nonconservative single nucleotide polymorphisms were approximately twice as frequent in HLA-matched unrelated, compared with related D-R pairs. When mapped to individual chromosomes, these polymorphic nucleotides were uniformly distributed across the entire exome. In conclusion, WES reveals extensive nucleotide sequence variation in the exomes of HLA-matched donors and recipients. © 2014 John Wiley & Sons Ltd.

A conserved post-transcriptional BMP2 switch in lung cells.

PubMed

Jiang, Shan; Fritz, David T; Rogers, Melissa B

2010-05-15

An ultra-conserved sequence in the bone morphogenetic protein 2 (BMP2) 3' untranslated region (UTR) markedly represses BMP2 expression in non-transformed lung cells. In contrast, the ultra-conserved sequence stimulates BMP2 expression in transformed lung cells. The ultra-conserved sequence functions as a post-transcriptional cis-regulatory switch. A common single-nucleotide polymorphism (SNP, rs15705, +A1123C), which has been shown to influence human morphology, disrupts a conserved element within the ultra-conserved sequence and altered reporter gene activity in non-transformed lung cells. This polymorphism changed the affinity of the BMP2 RNA for several proteins including nucleolin, which has an increased affinity for the C allele. Elevated BMP2 synthesis is associated with increased malignancy in mouse models of lung cancer and poor lung cancer patient prognosis. Understanding the cis- and trans-regulatory factors that control BMP2 synthesis is relevant to the initiation or progression of pathologies associated with abnormal BMP2 levels. (c) 2010 Wiley-Liss, Inc.

Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity

PubMed Central

Li, Chang-Lin; Li, Kai-Cheng; Wu, Dan; Chen, Yan; Luo, Hao; Zhao, Jing-Rong; Wang, Sa-Shuang; Sun, Ming-Ming; Lu, Ying-Jin; Zhong, Yan-Qing; Hu, Xu-Ye; Hou, Rui; Zhou, Bei-Bei; Bao, Lan; Xiao, Hua-Sheng; Zhang, Xu

2016-01-01

Sensory neurons are distinguished by distinct signaling networks and receptive characteristics. Thus, sensory neuron types can be defined by linking transcriptome-based neuron typing with the sensory phenotypes. Here we classify somatosensory neurons of the mouse dorsal root ganglion (DRG) by high-coverage single-cell RNA-sequencing (10 950 ± 1 218 genes per neuron) and neuron size-based hierarchical clustering. Moreover, single DRG neurons responding to cutaneous stimuli are recorded using an in vivo whole-cell patch clamp technique and classified by neuron-type genetic markers. Small diameter DRG neurons are classified into one type of low-threshold mechanoreceptor and five types of mechanoheat nociceptors (MHNs). Each of the MHN types is further categorized into two subtypes. Large DRG neurons are categorized into four types, including neurexophilin 1-expressing MHNs and mechanical nociceptors (MNs) expressing BAI1-associated protein 2-like 1 (Baiap2l1). Mechanoreceptors expressing trafficking protein particle complex 3-like and Baiap2l1-marked MNs are subdivided into two subtypes each. These results provide a new system for cataloging somatosensory neurons and their transcriptome databases. PMID:26691752

Development of a novel cell sorting method that samples population diversity in flow cytometry.

PubMed

Osborne, Geoffrey W; Andersen, Stacey B; Battye, Francis L

2015-11-01

Flow cytometry based electrostatic cell sorting is an important tool in the separation of cell populations. Existing instruments can sort single cells into multi-well collection plates, and keep track of cell of origin and sorted well location. However currently single sorted cell results reflect the population distribution and fail to capture the population diversity. Software was designed that implements a novel sorting approach, "Slice and Dice Sorting," that links a graphical representation of a multi-well plate to logic that ensures that single cells are sampled and sorted from all areas defined by the sort region/s. Therefore the diversity of the total population is captured, and the more frequently occurring or rarer cell types are all sampled. The sorting approach was tested computationally, and using functional cell based assays. Computationally we demonstrate that conventional single cell sorting can sample as little as 50% of the population diversity dependant on the population distribution, and that Slice and Dice sorting samples much more of the variety present within a cell population. We then show by sorting single cells into wells using the Slice and Dice sorting method that there are cells sorted using this method that would be either rarely sorted, or not sorted at all using conventional single cell sorting approaches. The present study demonstrates a novel single cell sorting method that samples much more of the population diversity than current methods. It has implications in clonal selection, stem cell sorting, single cell sequencing and any areas where population heterogeneity is of importance. © 2015 International Society for Advancement of Cytometry.

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.

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.

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

Next-Generation Immune Repertoire Sequencing as a Clue to Elucidate the Landscape of Immune Modulation by Host-Gut Microbiome Interactions.

PubMed

Ichinohe, Tatsuo; Miyama, Takahiko; Kawase, Takakazu; Honjo, Yasuko; Kitaura, Kazutaka; Sato, Hiroyuki; Shin-I, Tadasu; Suzuki, Ryuji

2018-01-01

The human immune system is a fine network consisted of the innumerable numbers of functional cells that balance the immunity and tolerance against various endogenous and environmental challenges. Although advances in modern immunology have revealed a role of many unique immune cell subsets, technologies that enable us to capture the whole landscape of immune responses against specific antigens have been not available to date. Acquired immunity against various microorganisms including host microbiome is principally founded on T cell and B cell populations, each of which expresses antigen-specific receptors that define a unique clonotype. Over the past several years, high-throughput next-generation sequencing has been developed as a powerful tool to profile T- and B-cell receptor repertoires in a given individual at the single-cell level. Sophisticated immuno-bioinformatic analyses by use of this innovative methodology have been already implemented in clinical development of antibody engineering, vaccine design, and cellular immunotherapy. In this article, we aim to discuss the possible application of high-throughput immune receptor sequencing in the field of nutritional and intestinal immunology. Although there are still unsolved caveats, this emerging technology combined with single-cell transcriptomics/proteomics provides a critical tool to unveil the previously unrecognized principle of host-microbiome immune homeostasis. Accumulation of such knowledge will lead to the development of effective ways for personalized immune modulation through deeper understanding of the mechanisms by which the intestinal environment affects our immune ecosystem.

Functional role of SETD2, BAP1, PARP-3 and PBRM1 candidate genes on the regulation of hTERT gene expression

PubMed Central

Linne, Hannah; Yasaei, Hemad; Marriott, Alison; Harvey, Amanda; Mokbel, Kefah; Newbold, Robert; Roberts, Terry

2017-01-01

Narrowing the search for the critical hTERT repressor sequence(s) has identified three regions on chromosome 3p (3p12-p21.1, 3p21.2 and 3p21.3-p22). However, the precise location and identity of the sequence(s) responsible for hTERT transcriptional repression remains elusive. In order to identify critical hTERT repressor sequences located within human chromosome 3p12-p22, we investigated hTERT transcriptional activity within 21NT microcell hybrid clones containing chromosome 3 fragments. Mapping of chromosome 3 structure in a single hTERT-repressed 21NT-#3fragment hybrid clone, revealed a 490kb region of deletion localised to 3p21.3 and encompassing the histone H3, lysine 36 (H3K36) trimethyltransferase enzyme SETD2; a putative tumour suppressor gene in breast cancer. Three additional genes, BAP1, PARP-3 and PBRM1, were also selected for further investigation based on their location within the 3p21.1-p21.3 region, together with their documented role in the epigenetic regulation of target gene expression or hTERT regulation. All four genes (SETD2, BAP1, PARP-3 and PBRM1) were found to be expressed at low levels in 21NT. Gene copy number variation (CNV) analysis of SETD2, BAP1, PARP-3 and PBRM1 within a panel of nine breast cancer cell lines demonstrated single copy number loss of all candidate genes within five (56%) cell lines (including 21NT cells). Stable, forced overexpression of BAP1, but not PARP2, SETD2 or PBRM1, within 21NT cells was associated with a significant reduction in hTERT expression levels relative to wild-type controls. We propose that at least two sequences exist on human chromosome 3p, that function to regulate hTERT transcription within human breast cancer cells. PMID:28977912

Functional role of SETD2, BAP1, PARP-3 and PBRM1 candidate genes on the regulation of hTERT gene expression.

PubMed

Linne, Hannah; Yasaei, Hemad; Marriott, Alison; Harvey, Amanda; Mokbel, Kefah; Newbold, Robert; Roberts, Terry

2017-09-22

Narrowing the search for the critical hTERT repressor sequence(s) has identified three regions on chromosome 3p (3p12-p21.1, 3p21.2 and 3p21.3-p22). However, the precise location and identity of the sequence(s) responsible for hTERT transcriptional repression remains elusive. In order to identify critical hTERT repressor sequences located within human chromosome 3p12-p22, we investigated hTERT transcriptional activity within 21NT microcell hybrid clones containing chromosome 3 fragments. Mapping of chromosome 3 structure in a single hTERT- repressed 21NT-#3fragment hybrid clone, revealed a 490kb region of deletion localised to 3p21.3 and encompassing the histone H3, lysine 36 (H3K36) trimethyltransferase enzyme SETD2; a putative tumour suppressor gene in breast cancer. Three additional genes, BAP1, PARP-3 and PBRM1, were also selected for further investigation based on their location within the 3p21.1-p21.3 region, together with their documented role in the epigenetic regulation of target gene expression or hTERT regulation. All four genes (SETD2, BAP1, PARP-3 and PBRM1) were found to be expressed at low levels in 21NT. Gene copy number variation (CNV) analysis of SETD2, BAP1, PARP-3 and PBRM1 within a panel of nine breast cancer cell lines demonstrated single copy number loss of all candidate genes within five (56%) cell lines (including 21NT cells). Stable, forced overexpression of BAP1, but not PARP2, SETD2 or PBRM1, within 21NT cells was associated with a significant reduction in hTERT expression levels relative to wild-type controls. We propose that at least two sequences exist on human chromosome 3p, that function to regulate hTERT transcription within human breast cancer cells.

Unexpected heterogeneity derived from Cas9 ribonucleoprotein-introduced clonal cells at the HPRT1 locus.

PubMed

Sakuma, Tetsushi; Mochida, Keiji; Nakade, Shota; Ezure, Toru; Minagawa, Sachi; Yamamoto, Takashi

2018-04-01

Single-cell cloning is an essential technique for establishing genome-edited cell clones mediated by programmable nucleases such as CRISPR-Cas9. However, residual genome-editing activity after single-cell cloning may cause heterogeneity in the clonal cells. Previous studies showed efficient mutagenesis and rapid degradation of CRISPR-Cas9 components in cultured cells by introducing Cas9 ribonucleoproteins (RNPs). In this study, we investigated how the timing for single-cell cloning of Cas9 RNP-transfected cells affected the heterogeneity of the resultant clones. We carried out transfection of Cas9 RNPs targeting several loci in the HPRT1 gene in HCT116 cells, followed by single-cell cloning at 24, 48, 72 hr and 1 week post-transfection. After approximately 3 weeks of incubation, the clonal cells were collected and genotyped by high-resolution microchip electrophoresis and Sanger sequencing. Unexpectedly, long-term incubation before single-cell cloning resulted in highly heterogeneous clones. We used a lipofection method for transfection, and the media containing transfectable RNPs were not removed before single-cell cloning. Therefore, the active Cas9 RNPs were considered to be continuously incorporated into cells during the precloning incubation. Our findings provide a warning that lipofection of Cas9 RNPs may cause continuous introduction of gene mutations depending on the experimental procedures. © 2018 Molecular Biology Society of Japan and John Wiley & Sons Australia, Ltd.

Enhanced sequencing coverage with digital droplet multiple displacement amplification

PubMed Central

Sidore, Angus M.; Lan, Freeman; Lim, Shaun W.; Abate, Adam R.

2016-01-01

Sequencing small quantities of DNA is important for applications ranging from the assembly of uncultivable microbial genomes to the identification of cancer-associated mutations. To obtain sufficient quantities of DNA for sequencing, the small amount of starting material must be amplified significantly. However, existing methods often yield errors or non-uniform coverage, reducing sequencing data quality. Here, we describe digital droplet multiple displacement amplification, a method that enables massive amplification of low-input material while maintaining sequence accuracy and uniformity. The low-input material is compartmentalized as single molecules in millions of picoliter droplets. Because the molecules are isolated in compartments, they amplify to saturation without competing for resources; this yields uniform representation of all sequences in the final product and, in turn, enhances the quality of the sequence data. We demonstrate the ability to uniformly amplify the genomes of single Escherichia coli cells, comprising just 4.7 fg of starting DNA, and obtain sequencing coverage distributions that rival that of unamplified material. Digital droplet multiple displacement amplification provides a simple and effective method for amplifying minute amounts of DNA for accurate and uniform sequencing. PMID:26704978

Novel Method for High-Throughput Full-Length IGHV-D-J Sequencing of the Immune Repertoire from Bulk B-Cells with Single-Cell Resolution.

PubMed

Vergani, Stefano; Korsunsky, Ilya; Mazzarello, Andrea Nicola; Ferrer, Gerardo; Chiorazzi, Nicholas; Bagnara, Davide

2017-01-01

Efficient and accurate high-throughput DNA sequencing of the adaptive immune receptor repertoire (AIRR) is necessary to study immune diversity in healthy subjects and disease-related conditions. The high complexity and diversity of the AIRR coupled with the limited amount of starting material, which can compromise identification of the full biological diversity makes such sequencing particularly challenging. AIRR sequencing protocols often fail to fully capture the sampled AIRR diversity, especially for samples containing restricted numbers of B lymphocytes. Here, we describe a library preparation method for immunoglobulin sequencing that results in an exhaustive full-length repertoire where virtually every sampled B-cell is sequenced. This maximizes the likelihood of identifying and quantifying the entire IGHV-D-J repertoire of a sample, including the detection of rearrangements present in only one cell in the starting population. The methodology establishes the importance of circumventing genetic material dilution in the preamplification phases and incorporates the use of certain described concepts: (1) balancing the starting material amount and depth of sequencing, (2) avoiding IGHV gene-specific amplification, and (3) using Unique Molecular Identifier. Together, this methodology is highly efficient, in particular for detecting rare rearrangements in the sampled population and when only a limited amount of starting material is available.

Cloning and characterization of human immunodeficiency virus type 1 variants diminished in the ability to induce syncytium-independent cytolysis.

PubMed Central

Stevenson, M; Haggerty, S; Lamonica, C; Mann, A M; Meier, C; Wasiak, A

1990-01-01

The phenomenon of interference was exploited to isolate low-abundance noncytopathic human immunodeficiency virus type 1 (HIV-1) variants from a primary HIV-1 isolate from an asymptomatic HIV-1-seropositive hemophiliac. Successive rounds of virus infection of a cytolysis-susceptible CD4+ cell line and isolation of surviving cells resulted in selective amplification of an HIV-1 variant reduced in the ability to induce cytolysis. The presence of a PvuII polymorphism facilitated subsequent amplification and cloning of cytopathic and noncytopathic HIV-1 variants from the primary isolate. Cloned virus stocks from cytopathic and noncytopathic variants exhibited similar replication kinetics, infectivity, and syncytium induction in susceptible host cells. The noncytopathic HIV-1 variant was unable, however, to induce single-cell killing in susceptible host cells. Construction of viral hybrids in which regions of cytopathic and noncytopathic variants were exchanged indicated that determinants for the noncytopathic phenotype map to the envelope glycoprotein. Sequence analysis of the envelope coding regions indicated the absence of two highly conserved N-linked glycosylation sites in the noncytopathic HIV-1 variant, which accompanied differences in processing of precursor gp160 envelope glycoprotein. These results demonstrate that determinants for syncytium-independent single-cell killing are located within the envelope glycoprotein and suggest that single-cell killing is profoundly influenced by alterations in envelope sequence which affect posttranslational processing of HIV-1 envelope glycoprotein within the infected cell. Images PMID:1695254

Heterotrophic potential of Atribacteria from deep marine Antarctic sediment

NASA Astrophysics Data System (ADS)

Carr, S. A.; Orcutt, B.; Mandernack, K. W.; Spear, J. R.

2015-12-01

Bacteria belonging to the newly classified candidate phylum "Atribacteria" (formerly referred to as "OP9" and "JS1") are common in anoxic methane-rich sediments. However, the metabolic functions and biogeochemical role of these microorganisms in the subsurface remains unrealized due to the lack of pure culture representatives. This study observed a steady increase of Atribacteria-related sequences with increasing sediment depth throughout the methane-rich zone of the Adélie Basin, Antarctica (according to a 16S rRNA gene survey). To explore the functional potential of Atribacteria in this basin, samples from various depths (14, 25 and 97 meters below seafloor), were subjected to metagenomic sequencing. Additionally, individual cells were separated from frozen, unpreserved sediment for whole genome amplification. The successful isolation and sequencing of a single-amplified Atribacteria genome from these unpreserved sediments demonstrates a future use of single cell techniques with previously collected and frozen sediments. Our resulting single-cell amplified genome, combined with metagenomic interpretations, provides our first insights to the functional potential of Atribacteria in deep subsurface settings. As observed for non-marine Atribacteria, genomic analyses suggest a heterotrophic metabolism, with Atribacteria potentially producing fermentation products such as acetate, ethanol and CO2. These products may in turn support methanogens within the sediment microbial community and explain the frequent occurrence of Atribacteria in anoxic methane-rich sediments.

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

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.

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.

Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

PubMed

Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

2013-08-01

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Quantification of Functionalised Gold Nanoparticle-Targeted Knockdown of Gene Expression in HeLa Cells

PubMed Central

Jiwaji, Meesbah; Sandison, Mairi E.; Reboud, Julien; Stevenson, Ross; Daly, Rónán; Barkess, Gráinne; Faulds, Karen; Kolch, Walter; Graham, Duncan; Girolami, Mark A.; Cooper, Jonathan M.; Pitt, Andrew R.

2014-01-01

Introduction Gene therapy continues to grow as an important area of research, primarily because of its potential in the treatment of disease. One significant area where there is a need for better understanding is in improving the efficiency of oligonucleotide delivery to the cell and indeed, following delivery, the characterization of the effects on the cell. Methods In this report, we compare different transfection reagents as delivery vehicles for gold nanoparticles functionalized with DNA oligonucleotides, and quantify their relative transfection efficiencies. The inhibitory properties of small interfering RNA (siRNA), single-stranded RNA (ssRNA) and single-stranded DNA (ssDNA) sequences targeted to human metallothionein hMT-IIa are also quantified in HeLa cells. Techniques used in this study include fluorescence and confocal microscopy, qPCR and Western analysis. Findings We show that the use of transfection reagents does significantly increase nanoparticle transfection efficiencies. Furthermore, siRNA, ssRNA and ssDNA sequences all have comparable inhibitory properties to ssDNA sequences immobilized onto gold nanoparticles. We also show that functionalized gold nanoparticles can co-localize with autophagosomes and illustrate other factors that can affect data collection and interpretation when performing studies with functionalized nanoparticles. Conclusions The desired outcome for biological knockdown studies is the efficient reduction of a specific target; which we demonstrate by using ssDNA inhibitory sequences targeted to human metallothionein IIa gene transcripts that result in the knockdown of both the mRNA transcript and the target protein. PMID:24926959

Single-Cell RNA Sequencing Reveals Expanded Clones of Islet Antigen-Reactive CD4+ T Cells in Peripheral Blood of Subjects with Type 1 Diabetes.

PubMed

Cerosaletti, Karen; Barahmand-Pour-Whitman, Fariba; Yang, Junbao; DeBerg, Hannah A; Dufort, Matthew J; Murray, Sara A; Israelsson, Elisabeth; Speake, Cate; Gersuk, Vivian H; Eddy, James A; Reijonen, Helena; Greenbaum, Carla J; Kwok, William W; Wambre, Erik; Prlic, Martin; Gottardo, Raphael; Nepom, Gerald T; Linsley, Peter S

2017-07-01

The significance of islet Ag-reactive T cells found in peripheral blood of type 1 diabetes (T1D) subjects is unclear, partly because similar cells are also found in healthy control (HC) subjects. We hypothesized that key disease-associated cells would show evidence of prior Ag exposure, inferred from expanded TCR clonotypes, and essential phenotypic properties in their transcriptomes. To test this, we developed single-cell RNA sequencing procedures for identifying TCR clonotypes and transcript phenotypes in individual T cells. We applied these procedures to analysis of islet Ag-reactive CD4 + memory T cells from the blood of T1D and HC individuals after activation with pooled immunodominant islet peptides. We found extensive TCR clonotype sharing in Ag-activated cells, especially from individual T1D subjects, consistent with in vivo T cell expansion during disease progression. The expanded clonotype from one T1D subject was detected at repeat visits spanning >15 mo, demonstrating clonotype stability. Notably, we found no clonotype sharing between subjects, indicating a predominance of "private" TCR specificities. Expanded clones from two T1D subjects recognized distinct IGRP peptides, implicating this molecule as a trigger for CD4 + T cell expansion. Although overall transcript profiles of cells from HC and T1D subjects were similar, profiles from the most expanded clones were distinctive. Our findings demonstrate that islet Ag-reactive CD4 + memory T cells with unique Ag specificities and phenotypes are expanded during disease progression and can be detected by single-cell analysis of peripheral blood. Copyright © 2017 by The American Association of Immunologists, Inc.

Evaluation of targeted exome sequencing for 28 protein-based blood group systems, including the homologous gene systems, for blood group genotyping.

PubMed

Schoeman, Elizna M; Lopez, Genghis H; McGowan, Eunike C; Millard, Glenda M; O'Brien, Helen; Roulis, Eileen V; Liew, Yew-Wah; Martin, Jacqueline R; McGrath, Kelli A; Powley, Tanya; Flower, Robert L; Hyland, Catherine A

2017-04-01

Blood group single nucleotide polymorphism genotyping probes for a limited range of polymorphisms. This study investigated whether massively parallel sequencing (also known as next-generation sequencing), with a targeted exome strategy, provides an extended blood group genotype and the extent to which massively parallel sequencing correctly genotypes in homologous gene systems, such as RH and MNS. Donor samples (n = 28) that were extensively phenotyped and genotyped using single nucleotide polymorphism typing, were analyzed using the TruSight One Sequencing Panel and MiSeq platform. Genes for 28 protein-based blood group systems, GATA1, and KLF1 were analyzed. Copy number variation analysis was used to characterize complex structural variants in the GYPC and RH systems. The average sequencing depth per target region was 66.2 ± 39.8. Each sample harbored on average 43 ± 9 variants, of which 10 ± 3 were used for genotyping. For the 28 samples, massively parallel sequencing variant sequences correctly matched expected sequences based on single nucleotide polymorphism genotyping data. Copy number variation analysis defined the Rh C/c alleles and complex RHD hybrids. Hybrid RHD*D-CE-D variants were correctly identified, but copy number variation analysis did not confidently distinguish between D and CE exon deletion versus rearrangement. The targeted exome sequencing strategy employed extended the range of blood group genotypes detected compared with single nucleotide polymorphism typing. This single-test format included detection of complex MNS hybrid cases and, with copy number variation analysis, defined RH hybrid genes along with the RHCE*C allele hitherto difficult to resolve by variant detection. The approach is economical compared with whole-genome sequencing and is suitable for a red blood cell reference laboratory setting. © 2017 AABB.

An intergenic non-coding rRNA correlated with expression of the rRNA and frequency of an rRNA single nucleotide polymorphism in lung cancer cells.

PubMed

Shiao, Yih-Horng; Lupascu, Sorin T; Gu, Yuhan D; Kasprzak, Wojciech; Hwang, Christopher J; Fields, Janet R; Leighty, Robert M; Quiñones, Octavio; Shapiro, Bruce A; Alvord, W Gregory; Anderson, Lucy M

2009-10-19

Ribosomal RNA (rRNA) is a central regulator of cell growth and may control cancer development. A cis noncoding rRNA (nc-rRNA) upstream from the 45S rRNA transcription start site has recently been implicated in control of rRNA transcription in mouse fibroblasts. We investigated whether a similar nc-rRNA might be expressed in human cancer epithelial cells, and related to any genomic characteristics. Using quantitative rRNA measurement, we demonstrated that a nc-rRNA is transcribed in human lung epithelial and lung cancer cells, starting from approximately -1000 nucleotides upstream of the rRNA transcription start site (+1) and extending at least to +203. This nc-rRNA was significantly more abundant in the majority of lung cancer cell lines, relative to a nontransformed lung epithelial cell line. Its abundance correlated negatively with total 45S rRNA in 12 of 13 cell lines (P = 0.014). During sequence analysis from -388 to +306, we observed diverse, frequent intercopy single nucleotide polymorphisms (SNPs) in rRNA, with a frequency greater than predicted by chance at 12 sites. A SNP at +139 (U/C) in the 5' leader sequence varied among the cell lines and correlated negatively with level of the nc-rRNA (P = 0.014). Modelling of the secondary structure of the rRNA 5'-leader sequence indicated a small increase in structural stability due to the +139 U/C SNP and a minor shift in local configuration occurrences. The results demonstrate occurrence of a sense nc-rRNA in human lung epithelial and cancer cells, and imply a role in regulation of the rRNA gene, which may be affected by a +139 SNP in the 5' leader sequence of the primary rRNA transcript.

Extreme heterogeneity of influenza virus infection in single cells

PubMed Central

Russell, Alistair B; Trapnell, Cole

2018-01-01

Viral infection can dramatically alter a cell’s transcriptome. However, these changes have mostly been studied by bulk measurements on many cells. Here we use single-cell mRNA sequencing to examine the transcriptional consequences of influenza virus infection. We find extremely wide cell-to-cell variation in the productivity of viral transcription – viral transcripts comprise less than a percent of total mRNA in many infected cells, but a few cells derive over half their mRNA from virus. Some infected cells fail to express at least one viral gene, but this gene absence only partially explains variation in viral transcriptional load. Despite variation in viral load, the relative abundances of viral mRNAs are fairly consistent across infected cells. Activation of innate immune pathways is rare, but some cellular genes co-vary in abundance with the amount of viral mRNA. Overall, our results highlight the complexity of viral infection at the level of single cells. PMID:29451492

Deep Sequencing of T-cell Receptor DNA as a Biomarker of Clonally Expanded TILs in Breast Cancer after Immunotherapy.

PubMed

Page, David B; Yuan, Jianda; Redmond, David; Wen, Y Hanna; Durack, Jeremy C; Emerson, Ryan; Solomon, Stephen; Dong, Zhiwan; Wong, Phillip; Comstock, Christopher; Diab, Adi; Sung, Janice; Maybody, Majid; Morris, Elizabeth; Brogi, Edi; Morrow, Monica; Sacchini, Virgilio; Elemento, Olivier; Robins, Harlan; Patil, Sujata; Allison, James P; Wolchok, Jedd D; Hudis, Clifford; Norton, Larry; McArthur, Heather L

2016-10-01

In early-stage breast cancer, the degree of tumor-infiltrating lymphocytes (TIL) predicts response to chemotherapy and overall survival. Combination immunotherapy with immune checkpoint antibody plus tumor cryoablation can induce lymphocytic infiltrates and improve survival in mice. We used T-cell receptor (TCR) DNA sequencing to evaluate both the effect of cryoimmunotherapy in humans and the feasibility of TCR sequencing in early-stage breast cancer. In a pilot clinical trial, 18 women with early-stage breast cancer were treated preoperatively with cryoablation, single-dose anti-CTLA-4 (ipilimumab), or cryoablation + ipilimumab. TCRs within serially collected peripheral blood and tumor tissue were sequenced. In baseline tumor tissues, T-cell density as measured by TCR sequencing correlated with TIL scores obtained by hematoxylin and eosin (H&E) staining. However, tumors with little or no lymphocytes by H&E contained up to 3.6 × 10 6 TCR DNA sequences, highlighting the sensitivity of the ImmunoSEQ platform. In this dataset, ipilimumab increased intratumoral T-cell density over time, whereas cryoablation ± ipilimumab diversified and remodeled the intratumoral T-cell clonal repertoire. Compared with monotherapy, cryoablation plus ipilimumab was associated with numerically greater numbers of peripheral blood and intratumoral T-cell clones expanding robustly following therapy. In conclusion, TCR sequencing correlates with H&E lymphocyte scoring and provides additional information on clonal diversity. These findings support further study of the use of TCR sequencing as a biomarker for T-cell responses to therapy and for the study of cryoimmunotherapy in early-stage breast cancer. Cancer Immunol Res; 4(10); 835-44. ©2016 AACR. ©2016 American Association for Cancer Research.

Single-cell RNA sequencing identifies diverse roles of epithelial cells in idiopathic pulmonary fibrosis

PubMed Central

Mizuno, Takako; Sridharan, Anusha; Du, Yina; Guo, Minzhe; Wikenheiser-Brokamp, Kathryn A.; Perl, Anne-Karina T.; Funari, Vincent A.; Gokey, Jason J.; Stripp, Barry R.; Whitsett, Jeffrey A.

2016-01-01

Idiopathic pulmonary fibrosis (IPF) is a lethal interstitial lung disease characterized by airway remodeling, inflammation, alveolar destruction, and fibrosis. We utilized single-cell RNA sequencing (scRNA-seq) to identify epithelial cell types and associated biological processes involved in the pathogenesis of IPF. Transcriptomic analysis of normal human lung epithelial cells defined gene expression patterns associated with highly differentiated alveolar type 2 (AT2) cells, indicated by enrichment of RNAs critical for surfactant homeostasis. In contrast, scRNA-seq of IPF cells identified 3 distinct subsets of epithelial cell types with characteristics of conducting airway basal and goblet cells and an additional atypical transitional cell that contributes to pathological processes in IPF. Individual IPF cells frequently coexpressed alveolar type 1 (AT1), AT2, and conducting airway selective markers, demonstrating “indeterminate” states of differentiation not seen in normal lung development. Pathway analysis predicted aberrant activation of canonical signaling via TGF-β, HIPPO/YAP, P53, WNT, and AKT/PI3K. Immunofluorescence confocal microscopy identified the disruption of alveolar structure and loss of the normal proximal-peripheral differentiation of pulmonary epithelial cells. scRNA-seq analyses identified loss of normal epithelial cell identities and unique contributions of epithelial cells to the pathogenesis of IPF. The present study provides a rich data source to further explore lung health and disease. PMID:27942595

Single-Step Conversion of Cells to Retrovirus Vector Producers with Herpes Simplex Virus–Epstein-Barr Virus Hybrid Amplicons

PubMed Central

Sena-Esteves, Miguel; Saeki, Yoshinaga; Camp, Sara M.; Chiocca, E. Antonio; Breakefield, Xandra O.

1999-01-01

We report here on the development and characterization of a novel herpes simplex virus type 1 (HSV-1) amplicon-based vector system which takes advantage of the host range and retention properties of HSV–Epstein-Barr virus (EBV) hybrid amplicons to efficiently convert cells to retrovirus vector producer cells after single-step transduction. The retrovirus genes gag-pol and env (GPE) and retroviral vector sequences were modified to minimize sequence overlap and cloned into an HSV-EBV hybrid amplicon. Retrovirus expression cassettes were used to generate the HSV-EBV-retrovirus hybrid vectors, HERE and HERA, which code for the ecotropic and the amphotropic envelopes, respectively. Retrovirus vector sequences encoding lacZ were cloned downstream from the GPE expression unit. Transfection of 293T/17 cells with amplicon plasmids yielded retrovirus titers between 106 and 107 transducing units/ml, while infection of the same cells with amplicon vectors generated maximum titers 1 order of magnitude lower. Retrovirus titers were dependent on the extent of transduction by amplicon vectors for the same cell line, but different cell lines displayed varying capacities to produce retrovirus vectors even at the same transduction efficiencies. Infection of human and dog primary gliomas with this system resulted in the production of retrovirus vectors for more than 1 week and the long-term retention and increase in transgene activity over time in these cell populations. Although the efficiency of this system still has to be determined in vivo, many applications are foreseeable for this approach to gene delivery. PMID:10559361

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

PubMed

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

2018-05-23

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

Magnetophoretic circuits for digital control of single particles and cells

NASA Astrophysics Data System (ADS)

Lim, Byeonghwa; Reddy, Venu; Hu, Xinghao; Kim, Kunwoo; Jadhav, Mital; Abedini-Nassab, Roozbeh; Noh, Young-Woock; Lim, Yong Taik; Yellen, Benjamin B.; Kim, Cheolgi

2014-05-01

The ability to manipulate small fluid droplets, colloidal particles and single cells with the precision and parallelization of modern-day computer hardware has profound applications for biochemical detection, gene sequencing, chemical synthesis and highly parallel analysis of single cells. Drawing inspiration from general circuit theory and magnetic bubble technology, here we demonstrate a class of integrated circuits for executing sequential and parallel, timed operations on an ensemble of single particles and cells. The integrated circuits are constructed from lithographically defined, overlaid patterns of magnetic film and current lines. The magnetic patterns passively control particles similar to electrical conductors, diodes and capacitors. The current lines actively switch particles between different tracks similar to gated electrical transistors. When combined into arrays and driven by a rotating magnetic field clock, these integrated circuits have general multiplexing properties and enable the precise control of magnetizable objects.

Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation.

PubMed

Stephenson, William; Donlin, Laura T; Butler, Andrew; Rozo, Cristina; Bracken, Bernadette; Rashidfarrokhi, Ali; Goodman, Susan M; Ivashkiv, Lionel B; Bykerk, Vivian P; Orange, Dana E; Darnell, Robert B; Swerdlow, Harold P; Satija, Rahul

2018-02-23

Droplet-based single-cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While this approach offers the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we developed a 3D-printed, low-cost droplet microfluidic control instrument and deploy it in a clinical environment to perform single-cell transcriptome profiling of disaggregated synovial tissue from five rheumatoid arthritis patients. We sequence 20,387 single cells revealing 13 transcriptomically distinct clusters. These encompass an unsupervised draft atlas of the autoimmune infiltrate that contribute to disease biology. Additionally, we identify previously uncharacterized fibroblast subpopulations and discern their spatial location within the synovium. We envision that this instrument will have broad utility in both research and clinical settings, enabling low-cost and routine application of microfluidic techniques.

Tracing the temporal-spatial transcriptome landscapes of the human fetal digestive tract using single-cell RNA-sequencing.

PubMed

Gao, Shuai; Yan, Liying; Wang, Rui; Li, Jingyun; Yong, Jun; Zhou, Xin; Wei, Yuan; Wu, Xinglong; Wang, Xiaoye; Fan, Xiaoying; Yan, Jie; Zhi, Xu; Gao, Yun; Guo, Hongshan; Jin, Xiao; Wang, Wendong; Mao, Yunuo; Wang, Fengchao; Wen, Lu; Fu, Wei; Ge, Hao; Qiao, Jie; Tang, Fuchou

2018-06-01

The development of the digestive tract is critical for proper food digestion and nutrient absorption. Here, we analyse the main organs of the digestive tract, including the oesophagus, stomach, small intestine and large intestine, from human embryos between 6 and 25 weeks of gestation as well as the large intestine from adults using single-cell RNA-seq analyses. In total, 5,227 individual cells are analysed and 40 cell types clearly identified. Their crucial biological features, including developmental processes, signalling pathways, cell cycle, nutrient digestion and absorption metabolism, and transcription factor networks, are systematically revealed. Moreover, the differentiation and maturation processes of the large intestine are thoroughly investigated by comparing the corresponding transcriptome profiles between embryonic and adult stages. Our work offers a rich resource for investigating the gene regulation networks of the human fetal digestive tract and adult large intestine at single-cell resolution.

Human IgG repertoire of malaria antigen-immunized human immune system (HIS) mice.

PubMed

Nogueira, Raquel Tayar; Sahi, Vincent; Huang, Jing; Tsuji, Moriya

2017-08-01

Humanized mouse models present an important tool for preclinical evaluation of new vaccines and therapeutics. Here we show the human variable repertoire of antibody sequences cloned from a previously described human immune system (HIS) mouse model that possesses functional human CD4+ T cells and B cells, namely HIS-CD4/B mice. We sequenced variable IgG genes from single memory B-cell and plasma-cell sorted from splenocytes or whole blood lymphocytes of HIS-CD4/B mice that were vaccinated with a human plasmodial antigen, a recombinant Plasmodium falciparum circumsporozoite protein (rPfCSP). We demonstrate that rPfCSP immunization triggers a diverse B-cell IgG repertoire composed of various human VH family genes and distinct V(D)J recombinations that constitute diverse CDR3 sequences similar to humans, although low hypermutated sequences were generated. These results demonstrate the substantial genetic diversity of responding human B cells of HIS-CD4/B mice and their capacity to mount human IgG class-switched antibody response upon vaccination. Copyright © 2017 European Federation of Immunological Societies. Published by Elsevier B.V. All rights reserved.

Novel high-speed droplet-allele specific-polymerase chain reaction: application in the rapid genotyping of single nucleotide polymorphisms.

PubMed

Taira, Chiaki; Matsuda, Kazuyuki; Yamaguchi, Akemi; Sueki, Akane; Koeda, Hiroshi; Takagi, Fumio; Kobayashi, Yukihiro; Sugano, Mitsutoshi; Honda, Takayuki

2013-09-23

Single nucleotide alterations such as single nucleotide polymorphisms (SNP) and single nucleotide mutations are associated with responses to drugs and predisposition to several diseases, and they contribute to the pathogenesis of malignancies. We developed a rapid genotyping assay based on the allele-specific polymerase chain reaction (AS-PCR) with our droplet-PCR machine (droplet-AS-PCR). Using 8 SNP loci, we evaluated the specificity and sensitivity of droplet-AS-PCR. Buccal cells were pretreated with proteinase K and subjected directly to the droplet-AS-PCR without DNA extraction. The genotypes determined using the droplet-AS-PCR were then compared with those obtained by direct sequencing. Specific PCR amplifications for the 8 SNP loci were detected, and the detection limit of the droplet-AS-PCR was found to be 0.1-5.0% by dilution experiments. Droplet-AS-PCR provided specific amplification when using buccal cells, and all the genotypes determined within 9 min were consistent with those obtained by direct sequencing. Our novel droplet-AS-PCR assay enabled high-speed amplification retaining specificity and sensitivity and provided ultra-rapid genotyping. Crude samples such as buccal cells were available for the droplet-AS-PCR assay, resulting in the reduction of the total analysis time. Droplet-AS-PCR may therefore be useful for genotyping or the detection of single nucleotide alterations. Copyright © 2013 Elsevier B.V. All rights reserved.

Advances for Studying Clonal Evolution in Cancer

PubMed Central

Raphael, Benjamin J.; Chen, Feng; Wendl, Michael C.

2013-01-01

The “clonal evolution” model of cancer emerged and “evolved” amid ongoing advances in technology, especially in recent years during which next generation sequencing instruments have provided ever higher resolution pictures of the genetic changes in cancer cells and heterogeneity in tumors. It has become increasingly clear that clonal evolution is not a single sequential process, but instead frequently involves simultaneous evolution of multiple subclones that co-exist because they are of similar fitness or are spatially separated. Co-evolution of subclones also occurs when they complement each other’s survival advantages. Recent studies have also shown that clonal evolution is highly heterogeneous: different individual tumors of the same type may undergo very different paths of clonal evolution. New methodological advancements, including deep digital sequencing of a mixed tumor population, single cell sequencing, and the development of more sophisticated computational tools, will continue to shape and reshape the models of clonal evolution. In turn, these will provide both an improved framework for the understanding of cancer progression and a guide for treatment strategies aimed at the elimination of all, rather than just some, of the cancer cells within a patient. PMID:23353056

Advances for studying clonal evolution in cancer.

PubMed

Ding, Li; Raphael, Benjamin J; Chen, Feng; Wendl, Michael C

2013-11-01

The "clonal evolution" model of cancer emerged and "evolved" amid ongoing advances in technology, especially in recent years during which next generation sequencing instruments have provided ever higher resolution pictures of the genetic changes in cancer cells and heterogeneity in tumors. It has become increasingly clear that clonal evolution is not a single sequential process, but instead frequently involves simultaneous evolution of multiple subclones that co-exist because they are of similar fitness or are spatially separated. Co-evolution of subclones also occurs when they complement each other's survival advantages. Recent studies have also shown that clonal evolution is highly heterogeneous: different individual tumors of the same type may undergo very different paths of clonal evolution. New methodological advancements, including deep digital sequencing of a mixed tumor population, single cell sequencing, and the development of more sophisticated computational tools, will continue to shape and reshape the models of clonal evolution. In turn, these will provide both an improved framework for the understanding of cancer progression and a guide for treatment strategies aimed at the elimination of all, rather than just some, of the cancer cells within a patient. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2017-01-05

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

Detection of the free living amoeba Naegleria fowleri by using conventional and real-time PCR based on a single copy DNA sequence.

PubMed

Régoudis, Estelle; Pélandakis, Michel

2016-02-01

The amoeba-flagellate Naegleria fowleri is a causative agent of primary amoebic meningoencephalitis (PAM). This thermophilic species occurs worldwide and tends to proliferate in warm aquatic environment. The PAM cases remain rare but this infection is mostly fatal. Here, we describe a single copy region which has been cloned and sequenced, and was used for both conventional and real-time PCR. Targeting a single-copy DNA sequence allows to directly quantify the N. fowleri cells. The real-time PCR results give a detection limit of 1 copy per reaction with high reproducibility without the need of a Taqman probe. This procedure is of interest as compared to other procedures which are mostly based on the detection of multi-copy DNA associated with a Taqman probe. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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.

Lack of Heterologous Cross-reactivity toward HLA-A*02:01 Restricted Viral Epitopes Is Underpinned by Distinct αβT Cell Receptor Signatures.

PubMed

Grant, Emma J; Josephs, Tracy M; Valkenburg, Sophie A; Wooldridge, Linda; Hellard, Margaret; Rossjohn, Jamie; Bharadwaj, Mandvi; Kedzierska, Katherine; Gras, Stephanie

2016-11-18

αβT cell receptor (TCR) genetic diversity is outnumbered by the quantity of pathogenic epitopes to be recognized. To provide efficient protective anti-viral immunity, a single TCR ideally needs to cross-react with a multitude of pathogenic epitopes. However, the frequency, extent, and mechanisms of TCR cross-reactivity remain unclear, with conflicting results on anti-viral T cell cross-reactivity observed in humans. Namely, both the presence and lack of T cell cross-reactivity have been reported with HLA-A*02:01-restricted epitopes from the Epstein-Barr and influenza viruses (BMLF-1 and M1 58 , respectively) or with the hepatitis C and influenza viruses (NS3 1073 and NA 231 , respectively). Given the high sequence similarity of these paired viral epitopes (56 and 88%, respectively), the ubiquitous nature of the three viruses, and the high frequency of the HLA-A*02:01 allele, we selected these epitopes to establish the extent of T cell cross-reactivity. We combined ex vivo and in vitro functional assays, single-cell αβTCR repertoire sequencing, and structural analysis of these four epitopes in complex with HLA-A*02:01 to determine whether they could lead to heterologous T cell cross-reactivity. Our data show that sequence similarity does not translate to structural mimicry of the paired epitopes in complexes with HLA-A*02:01, resulting in induction of distinct αβTCR repertoires. The differences in epitope architecture might be an obstacle for TCR recognition, explaining the lack of T cell cross-reactivity observed. In conclusion, sequence similarity does not necessarily result in structural mimicry, and despite the need for cross-reactivity, antigen-specific TCR repertoires can remain highly specific. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Two divergent endo-beta-1,4-glucanase genes exhibit overlapping expression in ripening fruit and abscising flowers.

PubMed Central

Lashbrook, C C; Gonzalez-Bosch, C; Bennett, A B

1994-01-01

Two structurally divergent endo-beta-1,4-glucanase (EGase) cDNAs were cloned from tomato. Although both cDNAs (Cel1 and Cel2) encode potentially glycosylated, basic proteins of 51 to 53 kD and possess multiple amino acid domains conserved in both plant and microbial EGases, Cel1 and Cel2 exhibit only 50% amino acid identity at the overall sequence level. Amino acid sequence comparisons to other plant EGases indicate that tomato Cel1 is most similar to bean abscission zone EGase (68%), whereas Cel2 exhibits greatest sequence identity to avocado fruit EGase (57%). Sequence comparisons suggest the presence of at least two structurally divergent EGase families in plants. Unlike ripening avocado fruit and bean abscission zones in which a single EGase mRNA predominates, EGase expression in tomato reflects the overlapping accumulation of both Cel1 and Cel2 transcripts in ripening fruit and in plant organs undergoing cell separation. Cel1 mRNA contributes significantly to total EGase mRNA accumulation within plant organs undergoing cell separation (abscission zones and mature anthers), whereas Cel2 mRNA is most abundant in ripening fruit. The overlapping expression of divergent EGase genes within a single species may suggest that multiple activities are required for the cooperative disassembly of cell wall components during fruit ripening, floral abscission, and anther dehiscence. PMID:7994180

Fluorescence-tunable Ag-DNA biosensor with tailored cytotoxicity for live-cell applications

NASA Astrophysics Data System (ADS)

Bossert, Nelli; de Bruin, Donny; Götz, Maria; Bouwmeester, Dirk; Heinrich, Doris

2016-11-01

DNA-stabilized silver clusters (Ag-DNA) show excellent promise as a multi-functional nanoagent for molecular investigations in living cells. The unique properties of these fluorescent nanomaterials allow for intracellular optical sensors with tunable cytotoxicity based on simple modifications of the DNA sequences. Three Ag-DNA nanoagent designs are investigated, exhibiting optical responses to the intracellular environments and sensing-capability of ions, functional inside living cells. Their sequence-dependent fluorescence responses inside living cells include (1) a strong splitting of the fluorescence peak for a DNA hairpin construct, (2) an excitation and emission shift of up to 120 nm for a single-stranded DNA construct, and (3) a sequence robust in fluorescence properties. Additionally, the cytotoxicity of these Ag-DNA constructs is tunable, ranging from highly cytotoxic to biocompatible Ag-DNA, independent of their optical sensing capability. Thus, Ag-DNA represents a versatile live-cell nanoagent addressable towards anti-cancer, patient-specific and anti-bacterial applications.

Spatial and temporal single-cell volume estimation by a fluorescence imaging technique with application to astrocytes in primary culture

NASA Astrophysics Data System (ADS)

Khatibi, Siamak; Allansson, Louise; Gustavsson, Tomas; Blomstrand, Fredrik; Hansson, Elisabeth; Olsson, Torsten

1999-05-01

Cell volume changes are often associated with important physiological and pathological processes in the cell. These changes may be the means by which the cell interacts with its surrounding. Astroglial cells change their volume and shape under several circumstances that affect the central nervous system. Following an incidence of brain damage, such as a stroke or a traumatic brain injury, one of the first events seen is swelling of the astroglial cells. In order to study this and other similar phenomena, it is desirable to develop technical instrumentation and analysis methods capable of detecting and characterizing dynamic cell shape changes in a quantitative and robust way. We have developed a technique to monitor and to quantify the spatial and temporal volume changes in a single cell in primary culture. The technique is based on two- and three-dimensional fluorescence imaging. The temporal information is obtained from a sequence of microscope images, which are analyzed in real time. The spatial data is collected in a sequence of images from the microscope, which is automatically focused up and down through the specimen. The analysis of spatial data is performed off-line and consists of photobleaching compensation, focus restoration, filtering, segmentation and spatial volume estimation.

Near-complete genome sequence of the cellulolytic Bacterium Bacteroides ( Pseudobacteroides) cellulosolvens ATCC 35603

DOE PAGES

Dassa, Bareket; Utturkar, Sagar M.; Hurt, Richard A.; ...

2015-09-24

We report the single-contig genome sequence of the anaerobic, mesophilic, cellulolytic bacterium, Bacteroides cellulosolvens. The bacterium produces a particularly elaborate cellulosome system, whereas the types of cohesin-dockerin interactions are opposite of other known cellulosome systems: cell-surface attachment is thus mediated via type-I interactions whereas enzymes are integrated via type-II interactions.

The cDNA sequence of mouse Pgp-1 and homology to human CD44 cell surface antigen and proteoglycan core/link proteins.

PubMed

Wolffe, E J; Gause, W C; Pelfrey, C M; Holland, S M; Steinberg, A D; August, J T

1990-01-05

We describe the isolation and sequencing of a cDNA encoding mouse Pgp-1. An oligonucleotide probe corresponding to the NH2-terminal sequence of the purified protein was synthesized by the polymerase chain reaction and used to screen a mouse macrophage lambda gt11 library. A cDNA clone with an insert of 1.2 kilobases was selected and sequenced. In Northern blot analysis, only cells expressing Pgp-1 contained mRNA species that hybridized with this Pgp-1 cDNA. The nucleotide sequence of the cDNA has a single open reading frame that yields a protein-coding sequence of 1076 base pairs followed by a 132-base pair 3'-untranslated sequence that includes a putative polyadenylation signal but no poly(A) tail. The translated sequence comprises a 13-amino acid signal peptide followed by a polypeptide core of 345 residues corresponding to an Mr of 37,800. Portions of the deduced amino acid sequence were identical to those obtained by amino acid sequence analysis from the purified glycoprotein, confirming that the cDNA encodes Pgp-1. The predicted structure of Pgp-1 includes an NH2-terminal extracellular domain (residues 14-265), a transmembrane domain (residues 266-286), and a cytoplasmic tail (residues 287-358). Portions of the mouse Pgp-1 sequence are highly similar to that of the human CD44 cell surface glycoprotein implicated in cell adhesion. The protein also shows sequence similarity to the proteoglycan tandem repeat sequences found in cartilage link protein and cartilage proteoglycan core protein which are thought to be involved in binding to hyaluronic acid.

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 .

Two estrogen response element sequences near the PCNA gene are not responsible for its estrogen-enhanced expression in MCF7 cells.

PubMed

Wang, Cheng; Yu, Jie; Kallen, Caleb B

2008-01-01

The proliferating cell nuclear antigen (PCNA) is an essential component of DNA replication, cell cycle regulation, and epigenetic inheritance. High expression of PCNA is associated with poor prognosis in patients with breast cancer. The 5'-region of the PCNA gene contains two computationally-detected estrogen response element (ERE) sequences, one of which is evolutionarily conserved. Both of these sequences are of undocumented cis-regulatory function. We recently demonstrated that estradiol (E2) enhances PCNA mRNA expression in MCF7 breast cancer cells. MCF7 cells proliferate in response to E2. Here, we demonstrate that E2 rapidly enhanced PCNA mRNA and protein expression in a process that requires ERalpha as well as de novo protein synthesis. One of the two upstream ERE sequences was specifically bound by ERalpha-containing protein complexes, in vitro, in gel shift analysis. Yet, each ERE sequence, when cloned as a single copy, or when engineered as two tandem copies of the ERE-containing sequence, was not capable of activating a luciferase reporter construct in response to E2. In MCF7 cells, neither ERE-containing genomic region demonstrated E2-dependent recruitment of ERalpha by sensitive ChIP-PCR assays. We conclude that E2 enhances PCNA gene expression by an indirect process and that computational detection of EREs, even when evolutionarily conserved and when near E2-responsive genes, requires biochemical validation.

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

PubMed Central

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

2017-01-01

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

Single-Molecule Counting of Point Mutations by Transient DNA Binding

NASA Astrophysics Data System (ADS)

Su, Xin; Li, Lidan; Wang, Shanshan; Hao, Dandan; Wang, Lei; Yu, Changyuan

2017-03-01

High-confidence detection of point mutations is important for disease diagnosis and clinical practice. Hybridization probes are extensively used, but are hindered by their poor single-nucleotide selectivity. Shortening the length of DNA hybridization probes weakens the stability of the probe-target duplex, leading to transient binding between complementary sequences. The kinetics of probe-target binding events are highly dependent on the number of complementary base pairs. Here, we present a single-molecule assay for point mutation detection based on transient DNA binding and use of total internal reflection fluorescence microscopy. Statistical analysis of single-molecule kinetics enabled us to effectively discriminate between wild type DNA sequences and single-nucleotide variants at the single-molecule level. A higher single-nucleotide discrimination is achieved than in our previous work by optimizing the assay conditions, which is guided by statistical modeling of kinetics with a gamma distribution. The KRAS c.34 A mutation can be clearly differentiated from the wild type sequence (KRAS c.34 G) at a relative abundance as low as 0.01% mutant to WT. To demonstrate the feasibility of this method for analysis of clinically relevant biological samples, we used this technology to detect mutations in single-stranded DNA generated from asymmetric RT-PCR of mRNA from two cancer cell lines.

Fluorescence Detection of KRAS2 mRNA Hybridization in Lung Cancer Cells with PNA-Peptides Containing an Internal Thiazole Orange

PubMed Central

2015-01-01

We previously developed reporter-peptide nucleic acid (PNA)-peptides for sequence-specific radioimaging and fluorescence imaging of particular mRNAs in cells and tumors. However, a direct test for PNA-peptide hybridization with RNA in the cytoplasm would be desirable. Thiazole orange (TO) dye at the 5′ end of a hybridization agent shows a strong increase in fluorescence quantum yield when stacked upon a 5′ terminal base pair, in solution and in cells. We hypothesized that hybridization agents with an internal TO could distinguish a single base mutation in RNA. Thus, we designed KRAS2 PNA-IGF1 tetrapeptide agents with an internal TO adjacent to the middle base of the 12th codon, a frequent site of cancer-initiating mutations. Our molecular dynamics calculations predicted a disordered bulge with weaker hybridization resulting from a single RNA mismatch. We observed that single-stranded PNA-IGF1 tetrapeptide agents with an internal TO showed low fluorescence, but fluorescence escalated 5–6-fold upon hybridization with KRAS2 RNA. Circular dichroism melting curves showed ∼10 °C higher Tm for fully complementary vs single base mismatch TO-PNA-peptide agent duplexes with KRAS2 RNA. Fluorescence measurements of treated human lung cancer cells similarly showed elevated cytoplasmic fluorescence intensity with fully complementary vs single base mismatch agents. Sequence-specific elevation of internal TO fluorescence is consistent with our hypothesis of detecting cytoplasmic PNA-peptide:RNA hybridization if a mutant agent encounters the corresponding mutant mRNA. PMID:25180641

SALP, a new single-stranded DNA library preparation method especially useful for the high-throughput characterization of chromatin openness states.

PubMed

Wu, Jian; Dai, Wei; Wu, Lin; Wang, Jinke

2018-02-13

Next-generation sequencing (NGS) is fundamental to the current biological and biomedical research. Construction of sequencing library is a key step of NGS. Therefore, various library construction methods have been explored. However, the current methods are still limited by some shortcomings. This study developed a new NGS library construction method, Single strand Adaptor Library Preparation (SALP), by using a novel single strand adaptor (SSA). SSA is a double-stranded oligonucleotide with a 3' overhang of 3 random nucleotides, which can be efficiently ligated to the 3' end of single strand DNA by T4 DNA ligase. SALP can be started with any denatured DNA fragments such as those sheared by Tn5 tagmentation, enzyme digestion and sonication. When started with Tn5-tagmented chromatin, SALP can overcome a key limitation of ATAC-seq and become a high-throughput NGS library construction method, SALP-seq, which can be used to comparatively characterize the chromatin openness state of multiple cells unbiasly. In this way, this study successfully characterized the comparative chromatin openness states of four different cell lines, including GM12878, HepG2, HeLa and 293T, with SALP-seq. Similarly, this study also successfully characterized the chromatin openness states of HepG2 cells with SALP-seq by using 10 5 to 500 cells. This study developed a new NGS library construction method, SALP, by using a novel kind of single strand adaptor (SSA), which should has wide applications in the future due to its unique performance.

Abundant cytomegalovirus (CMV) reactive clonotypes in the CD8(+) T cell receptor alpha repertoire following allogeneic transplantation.

PubMed

Link, C S; Eugster, A; Heidenreich, F; Rücker-Braun, E; Schmiedgen, M; Oelschlägel, U; Kühn, D; Dietz, S; Fuchs, Y; Dahl, A; Domingues, A M J; Klesse, C; Schmitz, M; Ehninger, G; Bornhäuser, M; Schetelig, J; Bonifacio, E

2016-06-01

Allogeneic stem cell transplantation is potentially curative, but associated with post-transplantation complications, including cytomegalovirus (CMV) infections. An effective immune response requires T cells recognizing CMV epitopes via their T cell receptors (TCRs). Little is known about the TCR repertoire, in particular the TCR-α repertoire and its clinical relevance in patients following stem cell transplantation. Using next-generation sequencing we examined the TCR-α repertoire of CD8(+) T cells and CMV-specific CD8(+) T cells in four patients. Additionally, we performed single-cell TCR-αβ sequencing of CMV-specific CD8(+) T cells. The TCR-α composition of human leucocyte antigen (HLA)-A*0201 CMVpp65- and CMVIE -specific T cells was oligoclonal and defined by few dominant clonotypes. Frequencies of single clonotypes reached up to 11% of all CD8(+) T cells and half of the total CD8(+) T cell repertoire was dominated by few CMV-reactive clonotypes. Some TCR-α clonotypes were shared between patients. Gene expression of the circulating CMV-specific CD8(+) T cells was consistent with chronically activated effector memory T cells. The CD8(+) T cell response to CMV reactivation resulted in an expansion of a few TCR-α clonotypes to dominate the CD8(+) repertoires. These results warrant further larger studies to define the ability of oligoclonally expanded T cell clones to achieve an effective anti-viral T cell response in this setting. © 2016 British Society for Immunology.

HeLa Nucleic Acid Contamination in The Cancer Genome Atlas Leads to the Misidentification of Human Papillomavirus 18

PubMed Central

Cantalupo, Paul G.; Katz, Joshua P.

2015-01-01

ABSTRACT We searched The Cancer Genome Atlas (TCGA) database for viruses by comparing non-human reads present in transcriptome sequencing (RNA-Seq) and whole-exome sequencing (WXS) data to viral sequence databases. Human papillomavirus 18 (HPV18) is an etiologic agent of cervical cancer, and as expected, we found robust expression of HPV18 genes in cervical cancer samples. In agreement with previous studies, we also found HPV18 transcripts in non-cervical cancer samples, including those from the colon, rectum, and normal kidney. However, in each of these cases, HPV18 gene expression was low, and single-nucleotide variants and positions of genomic alignments matched the integrated portion of HPV18 present in HeLa cells. Chimeric reads that match a known virus-cell junction of HPV18 integrated in HeLa cells were also present in some samples. We hypothesize that HPV18 sequences in these non-cervical samples are due to nucleic acid contamination from HeLa cells. This finding highlights the problems that contamination presents in computational virus detection pipelines. IMPORTANCE Viruses associated with cancer can be detected by searching tumor sequence databases. Several studies involving searches of the TCGA database have reported the presence of HPV18, a known cause of cervical cancer, in a small number of additional cancers, including those of the rectum, kidney, and colon. We have determined that the sequences related to HPV18 in non-cervical samples are due to nucleic acid contamination from HeLa cells. To our knowledge, this is the first report of the misidentification of viruses in next-generation sequencing data of tumors due to contamination with a cancer cell line. These results raise awareness of the difficulty of accurately identifying viruses in human sequence databases. PMID:25631090

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

Clonal expansion of genome-intact HIV-1 in functionally polarized Th1 CD4+ T cells

PubMed Central

Orlova-Fink, Nina; Einkauf, Kevin; Chowdhury, Fatema Z.; Sun, Xiaoming; Harrington, Sean; Kuo, Hsiao-Hsuan; Hua, Stephane; Chen, Hsiao-Rong; Ouyang, Zhengyu; Reddy, Kavidha; Dong, Krista; Ndung’u, Thumbi; Walker, Bruce D.; Rosenberg, Eric S.; Yu, Xu G.

2017-01-01

HIV-1 causes a chronic, incurable disease due to its persistence in CD4+ T cells that contain replication-competent provirus, but exhibit little or no active viral gene expression and effectively resist combination antiretroviral therapy (cART). These latently infected T cells represent an extremely small proportion of all circulating CD4+ T cells but possess a remarkable long-term stability and typically persist throughout life, for reasons that are not fully understood. Here we performed massive single-genome, near-full-length next-generation sequencing of HIV-1 DNA derived from unfractionated peripheral blood mononuclear cells, ex vivo-isolated CD4+ T cells, and subsets of functionally polarized memory CD4+ T cells. This approach identified multiple sets of independent, near-full-length proviral sequences from cART-treated individuals that were completely identical, consistent with clonal expansion of CD4+ T cells harboring intact HIV-1. Intact, near-full-genome HIV-1 DNA sequences that were derived from such clonally expanded CD4+ T cells constituted 62% of all analyzed genome-intact sequences in memory CD4 T cells, were preferentially observed in Th1-polarized cells, were longitudinally detected over a duration of up to 5 years, and were fully replication- and infection-competent. Together, these data suggest that clonal proliferation of Th1-polarized CD4+ T cells encoding for intact HIV-1 represents a driving force for stabilizing the pool of latently infected CD4+ T cells. PMID:28628034

Clonal expansion of genome-intact HIV-1 in functionally polarized Th1 CD4+ T cells.

PubMed

Lee, Guinevere Q; Orlova-Fink, Nina; Einkauf, Kevin; Chowdhury, Fatema Z; Sun, Xiaoming; Harrington, Sean; Kuo, Hsiao-Hsuan; Hua, Stephane; Chen, Hsiao-Rong; Ouyang, Zhengyu; Reddy, Kavidha; Dong, Krista; Ndung'u, Thumbi; Walker, Bruce D; Rosenberg, Eric S; Yu, Xu G; Lichterfeld, Mathias

2017-06-30

HIV-1 causes a chronic, incurable disease due to its persistence in CD4+ T cells that contain replication-competent provirus, but exhibit little or no active viral gene expression and effectively resist combination antiretroviral therapy (cART). These latently infected T cells represent an extremely small proportion of all circulating CD4+ T cells but possess a remarkable long-term stability and typically persist throughout life, for reasons that are not fully understood. Here we performed massive single-genome, near-full-length next-generation sequencing of HIV-1 DNA derived from unfractionated peripheral blood mononuclear cells, ex vivo-isolated CD4+ T cells, and subsets of functionally polarized memory CD4+ T cells. This approach identified multiple sets of independent, near-full-length proviral sequences from cART-treated individuals that were completely identical, consistent with clonal expansion of CD4+ T cells harboring intact HIV-1. Intact, near-full-genome HIV-1 DNA sequences that were derived from such clonally expanded CD4+ T cells constituted 62% of all analyzed genome-intact sequences in memory CD4 T cells, were preferentially observed in Th1-polarized cells, were longitudinally detected over a duration of up to 5 years, and were fully replication- and infection-competent. Together, these data suggest that clonal proliferation of Th1-polarized CD4+ T cells encoding for intact HIV-1 represents a driving force for stabilizing the pool of latently infected CD4+ T cells.

RNA-ID, a Powerful Tool for Identifying and Characterizing Regulatory Sequences.

PubMed

Brule, C E; Dean, K M; Grayhack, E J

2016-01-01

The identification and analysis of sequences that regulate gene expression is critical because regulated gene expression underlies biology. RNA-ID is an efficient and sensitive method to discover and investigate regulatory sequences in the yeast Saccharomyces cerevisiae, using fluorescence-based assays to detect green fluorescent protein (GFP) relative to a red fluorescent protein (RFP) control in individual cells. Putative regulatory sequences can be inserted either in-frame or upstream of a superfolder GFP fusion protein whose expression, like that of RFP, is driven by the bidirectional GAL1,10 promoter. In this chapter, we describe the methodology to identify and study cis-regulatory sequences in the RNA-ID system, explaining features and variations of the RNA-ID reporter, as well as some applications of this system. We describe in detail the methods to analyze a single regulatory sequence, from construction of a single GFP variant to assay of variants by flow cytometry, as well as modifications required to screen libraries of different strains simultaneously. We also describe subsequent analyses of regulatory sequences. © 2016 Elsevier Inc. All rights reserved.

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

PubMed

Chen, Shuonan; Mar, Jessica C

2018-06-19

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

Caulobacter crescentus Cell Cycle-Regulated DNA Methyltransferase Uses a Novel Mechanism for Substrate Recognition.

PubMed

Woodcock, Clayton B; Yakubov, Aziz B; Reich, Norbert O

2017-08-01

Caulobacter crescentus relies on DNA methylation by the cell cycle-regulated methyltransferase (CcrM) in addition to key transcription factors to control the cell cycle and direct cellular differentiation. CcrM is shown here to efficiently methylate its cognate recognition site 5'-GANTC-3' in single-stranded and hemimethylated double-stranded DNA. We report the K m , k cat , k methylation , and K d for single-stranded and hemimethylated substrates, revealing discrimination of 10 7 -fold for noncognate sequences. The enzyme also shows a similar discrimination against single-stranded RNA. Two independent assays clearly show that CcrM is highly processive with single-stranded and hemimethylated DNA. Collectively, the data provide evidence that CcrM and other DNA-modifying enzymes may use a new mechanism to recognize DNA in a key epigenetic process.

Library construction for next-generation sequencing: Overviews and challenges

PubMed Central

Head, Steven R.; Komori, H. Kiyomi; LaMere, Sarah A.; Whisenant, Thomas; Van Nieuwerburgh, Filip; Salomon, Daniel R.; Ordoukhanian, Phillip

2014-01-01

High-throughput sequencing, also known as next-generation sequencing (NGS), has revolutionized genomic research. In recent years, NGS technology has steadily improved, with costs dropping and the number and range of sequencing applications increasing exponentially. Here, we examine the critical role of sequencing library quality and consider important challenges when preparing NGS libraries from DNA and RNA sources. Factors such as the quantity and physical characteristics of the RNA or DNA source material as well as the desired application (i.e., genome sequencing, targeted sequencing, RNA-seq, ChIP-seq, RIP-seq, and methylation) are addressed in the context of preparing high quality sequencing libraries. In addition, the current methods for preparing NGS libraries from single cells are also discussed. PMID:24502796

Evaluation and verification of epitaxial process sequence for silicon solar-cell production

NASA Technical Reports Server (NTRS)

Redfield, D.

1981-01-01

To achieve the program goals, 28 minimodules were fabricated and tested, using 600 cells made from three-inch-diameter wafers processed by the sequence chosen for this purpose. Of these 600 cells, half were made from epitaxially grown layers on potentially low-cost substrates. The other half were made from commercial semiconductor-grade (SG), single-crystal silicon wafers that served as controls. Cell processing was normally performed on mixed lots containing significant numbers of each of these two types of wafers. After evaluation of the performance of all cells, they were separated by types for incorporation into modules that were to be tested for electrical performance and response to environmental stress. A simplified flow chart displaying this scheme, for quantities representing half of the planned total to be processed, is presented.

Design and fabrication of silver-hydrogen cells

NASA Technical Reports Server (NTRS)

Klein, M. G.

1975-01-01

The design and fabrication of silver-hydrogen secondary cells capable of delivering higher energy densities than comparable nickel-cadmium and nickel-hydrogen cells and relatively high cycle life is presented. An experimental task utilizing single electrode pairs for the optimization of the individual electrode components, the preparation of a design for lightweight 20Ahr cells, and the fabrication of four 20Ahr cells in heavy wall test housing containing electrode stacks of the lightweight design are described. The design approach is based on the use of a single cylindrical self-contained cell with a stacked disc sequence of electrodes. The electrode stack design is based on the use of NASA- Astropower Separator Material, PPF fuel cell anodes, an intercell electrolyte reservoir concept and sintered silver electrodes. Results of performance tests are given.

DNA strand-displacement-induced fluorescence enhancement for highly sensitive and selective assay of multiple microRNA in cancer cells.

PubMed

Wu, Ping; Tu, Yunqiu; Qian, Yingdan; Zhang, Hui; Cai, Chenxin

2014-01-28

We report a new strategy for evaluating multiple miRNA expressions in cancer cells based on DNA strand-displacement-induced fluorescence enhancement. This assay has the ability to discriminate the target from even single-base mismatched sequences or other miRNAs.

In trans paired nicking triggers seamless genome editing without double-stranded DNA cutting.

PubMed

Chen, Xiaoyu; Janssen, Josephine M; Liu, Jin; Maggio, Ignazio; 't Jong, Anke E J; Mikkers, Harald M M; Gonçalves, Manuel A F V

2017-09-22

Precise genome editing involves homologous recombination between donor DNA and chromosomal sequences subjected to double-stranded DNA breaks made by programmable nucleases. Ideally, genome editing should be efficient, specific, and accurate. However, besides constituting potential translocation-initiating lesions, double-stranded DNA breaks (targeted or otherwise) are mostly repaired through unpredictable and mutagenic non-homologous recombination processes. Here, we report that the coordinated formation of paired single-stranded DNA breaks, or nicks, at donor plasmids and chromosomal target sites by RNA-guided nucleases based on CRISPR-Cas9 components, triggers seamless homology-directed gene targeting of large genetic payloads in human cells, including pluripotent stem cells. Importantly, in addition to significantly reducing the mutagenicity of the genome modification procedure, this in trans paired nicking strategy achieves multiplexed, single-step, gene targeting, and yields higher frequencies of accurately edited cells when compared to the standard double-stranded DNA break-dependent approach.CRISPR-Cas9-based gene editing involves double-strand breaks at target sequences, which are often repaired by mutagenic non-homologous end-joining. Here the authors use Cas9 nickases to generate coordinated single-strand breaks in donor and target DNA for precise homology-directed gene editing.

Lineage Tracking for Probing Heritable Phenotypes at Single-Cell Resolution

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons

PubMed Central

Krishnaswami, Suguna Rani; Grindberg, Rashel V; Novotny, Mark; Venepally, Pratap; Lacar, Benjamin; Bhutani, Kunal; Linker, Sara B; Pham, Son; Erwin, Jennifer A; Miller, Jeremy A; Hodge, Rebecca; McCarthy, James K; Kelder, Martin; McCorrison, Jamison; Aevermann, Brian D; Fuertes, Francisco Diez; Scheuermann, Richard H; Lee, Jun; Lein, Ed S; Schork, Nicholas; McConnell, Michael J; Gage, Fred H; Lasken, Roger S

2016-01-01

A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at −80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing. PMID:26890679

Postdoctoral Fellows | Center for Cancer Research

Cancer.gov

The Oncogenomics section of the Genetics Branch is a multidisciplinary and interdisciplinary translational research programmatic effort with the goal of utilizing genomics to develop novel immunotherapies for cancer. Our group is applying high throughput applied genomics methods including single cell RNAseq, single cell TCR sequencing, DNA sequencing, CRISPR/Cas9, bioinformatics combined with T cell based therapeutics to identify and develop novel immunotherapeutics for human cancer. We work with other investigators within the intramural program as well as industrial and pharmaceutical partners to rapidly translate our findings to the clinic. The program takes advantage of the uniqueness of the National Cancer Institute, (NCI), Center for Cancer Research (CCR) intramural program in that it spans high-risk basic discovery research in immunology, genomics and tumor biology, through preclinical translational research, to paradigm-shifting clinical trials. The position is available immediately. The appointment duration is up to 5 years. Stipends are commensurate with education and experience. Additional information can be found on Dr. Khan’s profile page: https://ccr.cancer.gov/Genetics-Branch/javed-khan

Live single-cell laser tag.

PubMed

Binan, Loïc; Mazzaferri, Javier; Choquet, Karine; Lorenzo, Louis-Etienne; Wang, Yu Chang; Affar, El Bachir; De Koninck, Yves; Ragoussis, Jiannis; Kleinman, Claudia L; Costantino, Santiago

2016-05-20

The ability to conduct image-based, non-invasive cell tagging, independent of genetic engineering, is key to cell biology applications. Here we introduce cell labelling via photobleaching (CLaP), a method that enables instant, specific tagging of individual cells based on a wide array of criteria such as shape, behaviour or positional information. CLaP uses laser illumination to crosslink biotin onto the plasma membrane, coupled with streptavidin conjugates to label individual cells for genomic, cell-tracking, flow cytometry or ultra-microscopy applications. We show that the incorporated mark is stable, non-toxic, retained for several days, and transferred by cell division but not to adjacent cells in culture. To demonstrate the potential of CLaP for genomic applications, we combine CLaP with microfluidics-based single-cell capture followed by transcriptome-wide next-generation sequencing. Finally, we show that CLaP can also be exploited for inducing transient cell adhesion to substrates for microengineering cultures with spatially patterned cell types.

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

PubMed Central

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

2015-01-01

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

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.

The first whole transcriptomic exploration of pre-oviposited early chicken embryos using single and bulked embryonic RNA-sequencing.

PubMed

Hwang, Young Sun; Seo, Minseok; Choi, Hee Jung; Kim, Sang Kyung; Kim, Heebal; Han, Jae Yong

2018-04-01

The chicken is a valuable model organism, especially in evolutionary and embryology research because its embryonic development occurs in the egg. However, despite its scientific importance, no transcriptome data have been generated for deciphering the early developmental stages of the chicken because of practical and technical constraints in accessing pre-oviposited embryos. Here, we determine the entire transcriptome of pre-oviposited avian embryos, including oocyte, zygote, and intrauterine embryos from Eyal-giladi and Kochav stage I (EGK.I) to EGK.X collected using a noninvasive approach for the first time. We also compare RNA-sequencing data obtained using a bulked embryo sequencing and single embryo/cell sequencing technique. The raw sequencing data were preprocessed with two genome builds, Galgal4 and Galgal5, and the expression of 17,108 and 26,102 genes was quantified in the respective builds. There were some differences between the two techniques, as well as between the two genome builds, and these were affected by the emergence of long intergenic noncoding RNA annotations. The first transcriptome datasets of pre-oviposited early chicken embryos based on bulked and single embryo sequencing techniques will serve as a valuable resource for investigating early avian embryogenesis, for comparative studies among vertebrates, and for novel gene annotation in the chicken genome.

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

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.

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

PubMed

Yáñez-Cuna, J Omar; van Steensel, Bas

2017-04-01

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

Single cells from human primary colorectal tumors exhibit polyfunctional heterogeneity in secretions of ELR+ CXC chemokines.

PubMed

Adalsteinsson, Viktor A; Tahirova, Narmin; Tallapragada, Naren; Yao, Xiaosai; Campion, Liam; Angelini, Alessandro; Douce, Thomas B; Huang, Cindy; Bowman, Brittany; Williamson, Christina A; Kwon, Douglas S; Wittrup, K Dane; Love, J Christopher

2013-10-01

Cancer is an inflammatory disease of tissue that is largely influenced by the interactions between multiple cell types, secreted factors, and signal transduction pathways. While single-cell sequencing continues to refine our understanding of the clonotypic heterogeneity within tumors, the complex interplay between genetic variations and non-genetic factors ultimately affects therapeutic outcome. Much has been learned through bulk studies of secreted factors in the tumor microenvironment, but the secretory behavior of single cells has been largely uncharacterized. Here we directly profiled the secretions of ELR+ CXC chemokines from thousands of single colorectal tumor and stromal cells, using an array of subnanoliter wells and a technique called microengraving to characterize both the rates of secretion of several factors at once and the numbers of cells secreting each chemokine. The ELR+ CXC chemokines are highly redundant, pro-angiogenic cytokines that signal via the CXCR1 and CXCR2 receptors, influencing tumor growth and progression. We find that human primary colorectal tumor and stromal cells exhibit polyfunctional heterogeneity in the combinations and magnitudes of secretions for these chemokines. In cell lines, we observe similar variance: phenotypes observed in bulk can be largely absent among the majority of single cells, and discordances exist between secretory states measured and gene expression for these chemokines among single cells. Together, these measures suggest secretory states among tumor cells are complex and can evolve dynamically. Most importantly, this study reveals new insight into the intratumoral phenotypic heterogeneity of human primary tumors.

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.

Enlightenment of Yeast Mitochondrial Homoplasmy: Diversified Roles of Gene Conversion

PubMed Central

Ling, Feng; Mikawa, Tsutomu; Shibata, Takehiko

2011-01-01

Mitochondria have their own genomic DNA. Unlike the nuclear genome, each cell contains hundreds to thousands of copies of mitochondrial DNA (mtDNA). The copies of mtDNA tend to have heterogeneous sequences, due to the high frequency of mutagenesis, but are quickly homogenized within a cell (“homoplasmy”) during vegetative cell growth or through a few sexual generations. Heteroplasmy is strongly associated with mitochondrial diseases, diabetes and aging. Recent studies revealed that the yeast cell has the machinery to homogenize mtDNA, using a common DNA processing pathway with gene conversion; i.e., both genetic events are initiated by a double-stranded break, which is processed into 3′ single-stranded tails. One of the tails is base-paired with the complementary sequence of the recipient double-stranded DNA to form a D-loop (homologous pairing), in which repair DNA synthesis is initiated to restore the sequence lost by the breakage. Gene conversion generates sequence diversity, depending on the divergence between the donor and recipient sequences, especially when it occurs among a number of copies of a DNA sequence family with some sequence variations, such as in immunoglobulin diversification in chicken. MtDNA can be regarded as a sequence family, in which the members tend to be diversified by a high frequency of spontaneous mutagenesis. Thus, it would be interesting to determine why and how double-stranded breakage and D-loop formation induce sequence homogenization in mitochondria and sequence diversification in nuclear DNA. We will review the mechanisms and roles of mtDNA homoplasmy, in contrast to nuclear gene conversion, which diversifies gene and genome sequences, to provide clues toward understanding how the common DNA processing pathway results in such divergent outcomes. PMID:24710143

Dynamic processes of the microbiota - from metagenomics to biofilms

NASA Astrophysics Data System (ADS)

Wingreen, Ned

The extent, origin, and impact of microbial diversity is a central question in biology. We expect that physical processes contribute to this diversity, but we are only beginning to explore the nature of these interactions. I will briefly discuss two approaches to this question, one based on metagenomics the other on observation of bacterial biofilms. First, I will address the challenge of identifying the constituents of microbial systems by presenting a new approach to analyzing community sequencing data that identifies microbial subpopulations while avoiding problematic clustering-based methods. Using data from a time-series study of human tongue microbiota, we were able to resolve within the standard definition of a ``species'' up to 20 ecologically distinct subpopulations with tag sequences differing by as little as one nucleotide (99.2% similarity). This fine resolution allowed us decouple sequence similarity from dynamical similarity, and to resolve dynamics on multiple time scales, including the slow appearance and disappearance of strains over months. Second, I will present recent results on the growth and competition of bacteria within biofilms. We imaged the growth ofliving biofilms of Vibrio choleraefrom single founder cells to ten thousand cells at single cell spatial resolution and with temporal resolution of one cell cycle. We discovered a transition from a branched 2D colony to a dense 3D cluster, in which cells at the biofilm center exhibit collective vertical alignment and local nematic packing. Our results suggest that biofilm cells exploit mechanics to simultaneously achieve strong surface adhesion, access to 3D space, resistance to invasion, and dominance over surface territory.

The LAM-PCR Method to Sequence LV Integration Sites.

PubMed

Wang, Wei; Bartholomae, Cynthia C; Gabriel, Richard; Deichmann, Annette; Schmidt, Manfred

2016-01-01

Integrating viral gene transfer vectors are commonly used gene delivery tools in clinical gene therapy trials providing stable integration and continuous gene expression of the transgene in the treated host cell. However, integration of the reverse-transcribed vector DNA into the host genome is a potentially mutagenic event that may directly contribute to unwanted side effects. A comprehensive and accurate analysis of the integration site (IS) repertoire is indispensable to study clonality in transduced cells obtained from patients undergoing gene therapy and to identify potential in vivo selection of affected cell clones. To date, next-generation sequencing (NGS) of vector-genome junctions allows sophisticated studies on the integration repertoire in vitro and in vivo. We have explored the use of the Illumina MiSeq Personal Sequencer platform to sequence vector ISs amplified by non-restrictive linear amplification-mediated PCR (nrLAM-PCR) and LAM-PCR. MiSeq-based high-quality IS sequence retrieval is accomplished by the introduction of a double-barcode strategy that substantially minimizes the frequency of IS sequence collisions compared to the conventionally used single-barcode protocol. Here, we present an updated protocol of (nr)LAM-PCR for the analysis of lentiviral IS using a double-barcode system and followed by deep sequencing using the MiSeq device.

Pathologic Stimulus Determines Lineage Commitment of Cardiac C-kit+ Cells.

PubMed

Chen, Zhongming; Zhu, Wuqiang; Bender, Ingrid; Gong, Wuming; Kwak, Il-Youp; Yellamilli, Amritha; Hodges, Thomas J; Nemoto, Natsumi; Zhang, Jianyi; Garry, Daniel J; van Berlo, Jop H

2017-12-12

Although cardiac c-kit + cells are being tested in clinical trials, the circumstances that determine lineage differentiation of c-kit + cells in vivo are unknown. Recent findings suggest that endogenous cardiac c-kit + cells rarely contribute cardiomyocytes to the adult heart. We assessed whether various pathological stimuli differentially affect the eventual cell fates of c-kit + cells. We used single-cell sequencing and genetic lineage tracing of c-kit + cells to determine whether various pathological stimuli would result in different fates of c-kit + cells. Single-cell sequencing of cardiac CD45 - c-kit + cells showed innate heterogeneity, indicative of the existence of vascular and mesenchymal c-kit + cells in normal hearts. Cardiac pressure overload resulted in a modest increase in c-kit-derived cardiomyocytes, with significant increases in the numbers of endothelial cells and fibroblasts. Doxorubicin-induced acute cardiotoxicity did not increase c-kit-derived endothelial cell fates but instead induced cardiomyocyte differentiation. Mechanistically, doxorubicin-induced DNA damage in c-kit + cells resulted in expression of p53. Inhibition of p53 blocked cardiomyocyte differentiation in response to doxorubicin, whereas stabilization of p53 was sufficient to increase c-kit-derived cardiomyocyte differentiation. These results demonstrate that different pathological stimuli induce different cell fates of c-kit + cells in vivo. Although the overall rate of cardiomyocyte formation from c-kit + cells is still below clinically relevant levels, we show that p53 is central to the ability of c-kit + cells to adopt cardiomyocyte fates, which could lead to the development of strategies to preferentially generate cardiomyocytes from c-kit + cells. © 2017 American Heart Association, Inc.

Diagnostic Applications of Next Generation Sequencing in Immunogenetics and Molecular Oncology

PubMed Central

Grumbt, Barbara; Eck, Sebastian H.; Hinrichsen, Tanja; Hirv, Kaimo

2013-01-01

Summary With the introduction of the next generation sequencing (NGS) technologies, remarkable new diagnostic applications have been established in daily routine. Implementation of NGS is challenging in clinical diagnostics, but definite advantages and new diagnostic possibilities make the switch to the technology inevitable. In addition to the higher sequencing capacity, clonal sequencing of single molecules, multiplexing of samples, higher diagnostic sensitivity, workflow miniaturization, and cost benefits are some of the valuable features of the technology. After the recent advances, NGS emerged as a proven alternative for classical Sanger sequencing in the typing of human leukocyte antigens (HLA). By virtue of the clonal amplification of single DNA molecules ambiguous typing results can be avoided. Simultaneously, a higher sample throughput can be achieved by tagging of DNA molecules with multiplex identifiers and pooling of PCR products before sequencing. In our experience, up to 380 samples can be typed for HLA-A, -B, and -DRB1 in high-resolution during every sequencing run. In molecular oncology, NGS shows a markedly increased sensitivity in comparison to the conventional Sanger sequencing and is developing to the standard diagnostic tool in detection of somatic mutations in cancer cells with great impact on personalized treatment of patients. PMID:23922545

Automated single cell sorting and deposition in submicroliter drops

NASA Astrophysics Data System (ADS)

Salánki, Rita; Gerecsei, Tamás; Orgovan, Norbert; Sándor, Noémi; Péter, Beatrix; Bajtay, Zsuzsa; Erdei, Anna; Horvath, Robert; Szabó, Bálint

2014-08-01

Automated manipulation and sorting of single cells are challenging, when intact cells are needed for further investigations, e.g., RNA or DNA sequencing. We applied a computer controlled micropipette on a microscope admitting 80 PCR (Polymerase Chain Reaction) tubes to be filled with single cells in a cycle. Due to the Laplace pressure, fluid starts to flow out from the micropipette only above a critical pressure preventing the precise control of drop volume in the submicroliter range. We found an anomalous pressure additive to the Laplace pressure that we attribute to the evaporation of the drop. We have overcome the problem of the critical dropping pressure with sequentially operated fast fluidic valves timed with a millisecond precision. Minimum drop volume was 0.4-0.7 μl with a sorting speed of 15-20 s per cell. After picking NE-4C neuroectodermal mouse stem cells and human primary monocytes from a standard plastic Petri dish we could gently deposit single cells inside tiny drops. 94 ± 3% and 54 ± 7% of the deposited drops contained single cells for NE-4C and monocytes, respectively. 7.5 ± 4% of the drops contained multiple cells in case of monocytes. Remaining drops were empty. Number of cells deposited in a drop could be documented by imaging the Petri dish before and after sorting. We tuned the adhesion force of cells to make the manipulation successful without the application of microstructures for trapping cells on the surface. We propose that our straightforward and flexible setup opens an avenue for single cell isolation, critically needed for the rapidly growing field of single cell biology.

Termite hindguts and the ecology of microbial communities in the sequencing age.

PubMed

Tai, Vera; Keeling, Patrick J

2013-01-01

Advances in high-throughput nucleic acid sequencing have improved our understanding of microbial communities in a number of ways. Deeper sequence coverage provides the means to assess diversity at the resolution necessary to recover ecological and biogeographic patterns, and at the same time single-cell genomics provides detailed information about the interactions between members of a microbial community. Given the vastness and complexity of microbial ecosystems, such analyses remain challenging for most environments, so greater insight can also be drawn from analysing less dynamic ecosystems. Here, we outline the advantages of one such environment, the wood-digesting hindgut communities of termites and cockroaches, and how it is a model to examine and compare both protist and bacterial communities. Beyond the analysis of diversity, our understanding of protist community ecology will depend on using statistically sound sampling regimes at biologically relevant scales, transitioning from discovery-based to experimental ecology, incorporating single-cell microbiology and other data sources, and continued development of analytical tools. © 2013 The Author(s) Journal of Eukaryotic Microbiology © 2013 International Society of Protistologists.

Single-molecule protein sequencing through fingerprinting: computational assessment

NASA Astrophysics Data System (ADS)

Yao, Yao; Docter, Margreet; van Ginkel, Jetty; de Ridder, Dick; Joo, Chirlmin

2015-10-01

Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences.

Identification of HIV-1 genitourinary tract compartmentalization by analyzing the env gene sequences in urine.

PubMed

Blasi, Maria; Carpenter, J Harris; Balakumaran, Bala; Cara, Andrea; Gao, Feng; Klotman, Mary E

2015-08-24

HIV-1 persists indefinitely in memory CD4 T cells and other long-lived cellular reservoirs despite antiretroviral therapy. Our group had previously demonstrated that HIV-1 can establish a productive infection in renal epithelial cells and that the kidney represents a separate compartment for HIV-1 replication. Here, to better understand the viruses in this unique site, we genetically characterized and compared the viruses in blood and urine specimens from 24 HIV-1 infected patients with detectable viremia. Blood and urine samples were obtained from 35 HIV-1 positive patients. Single-genome amplification was performed on HIV-1 env RNA and DNA isolated from urine supernatants and urine-derived cell pellets, respectively, as well as from plasma and peripheral blood mononuclear cell from the same individuals. Neighbor-joining trees were constructed under the Kimura 2-parameter model. We amplified and sequenced the full-length HIV-1 envelope (env) gene from 12 of the 24 individuals, indicating that 50% of the viremic HIV-1-positive patients had viral RNA in their urine. Phylogenetic analysis of the env sequences from four individuals with more than 15 urine-derived env sequences showed that the majority of the sequences from urine formed distinct cluster(s) independent of those peripheral blood mononuclear cell and plasma-derived sequences, consistent with viral compartmentalization in the urine. Our results suggest the presence of a distinct HIV compartment in the genitourinary tract.

BAIT: Organizing genomes and mapping rearrangements in single cells.

PubMed

Hills, Mark; O'Neill, Kieran; Falconer, Ester; Brinkman, Ryan; Lansdorp, Peter M

2013-01-01

Strand-seq is a single-cell sequencing technique to finely map sister chromatid exchanges (SCEs) and other rearrangements. To analyze these data, we introduce BAIT, software which assigns templates and identifies and localizes SCEs. We demonstrate BAIT can refine completed reference assemblies, identifying approximately 21 Mb of incorrectly oriented fragments and placing over half (2.6 Mb) of the orphan fragments in mm10/GRCm38. BAIT also stratifies scaffold-stage assemblies, potentially accelerating the assembling and finishing of reference genomes. BAIT is available at http://sourceforge.net/projects/bait/.

Direct typing of Canine parvovirus (CPV) from infected dog faeces by rapid mini sequencing technique.

PubMed

V, Pavana Jyothi; S, Akila; Selvan, Malini K; Naidu, Hariprasad; Raghunathan, Shwethaa; Kota, Sathish; Sundaram, R C Raja; Rana, Samir Kumar; Raj, G Dhinakar; Srinivasan, V A; Mohana Subramanian, B

2016-12-01

Canine parvovirus (CPV) is a non-enveloped single stranded DNA virus with an icosahedral capsid. Mini-sequencing based CPV typing was developed earlier to detect and differentiate all the CPV types and FPV in a single reaction. This technique was further evaluated in the present study by performing the mini-sequencing directly from fecal samples which avoided tedious virus isolation steps by cell culture system. Fecal swab samples were collected from 84 dogs with enteritis symptoms, suggestive of parvoviral infection from different locations across India. Seventy six of these samples were positive by PCR; the subsequent mini-sequencing reaction typed 74 of them as type 2a virus, and 2 samples as type 2b. Additionally, 25 of the positive samples were typed by cycle sequencing of PCR products. Direct CPV typing from fecal samples using mini-sequencing showed 100% correlation with CPV typing by cycle sequencing. Moreover, CPV typing was achieved by mini-sequencing even with faintly positive PCR amplicons which was not possible by cycle sequencing. Therefore, the mini-sequencing technique is recommended for regular epidemiological follow up of CPV types, since the technique is rapid, highly sensitive and high capacity method for CPV typing. Copyright © 2016. Published by Elsevier B.V.

Sequence specificity of the human mRNA N6-adenosine methylase in vitro.

PubMed Central

Harper, J E; Miceli, S M; Roberts, R J; Manley, J L

1990-01-01

N6-adenosine methylation is a frequent modification of mRNAs and their precursors, but little is known about the mechanism of the reaction or the function of the modification. To explore these questions, we developed conditions to examine N6-adenosine methylase activity in HeLa cell nuclear extracts. Transfer of the methyl group from S-[3H methyl]-adenosylmethionine to unlabeled random copolymer RNA substrates of varying ribonucleotide composition revealed a substrate specificity consistent with a previously deduced consensus sequence, Pu[G greater than A]AC[A/C/U]. 32-P labeled RNA substrates of defined sequence were used to examine the minimum sequence requirements for methylation. Each RNA was 20 nucleotides long, and contained either the core consensus sequence GGACU, or some variation of this sequence. RNAs containing GGACU, either in single or multiple copies, were good substrates for methylation, whereas RNAs containing single base substitutions within the GGACU sequence gave dramatically reduced methylation. These results demonstrate that the N6-adenosine methylase has a strict sequence specificity, and that there is no requirement for extended sequences or secondary structures for methylation. Recognition of this sequence does not require an RNA component, as micrococcal nuclease pretreatment of nuclear extracts actually increased methylation efficiency. Images PMID:2216767

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.

Protein profiling of single epidermal cell types from Arabidopsis thaliana using surface-enhanced laser desorption and ionization technology.

PubMed

Ebert, Berit; Melle, Christian; Lieckfeldt, Elke; Zöller, Daniela; von Eggeling, Ferdinand; Fisahn, Joachim

2008-08-25

Here, we describe a novel approach for investigating differential protein expression within three epidermal cell types. In particular, 3000 single pavement, basal, and trichome cells from leaves of Arabidopsis thaliana were harvested by glass micro-capillaries. Subsequently, these single cell samples were joined to form pools of 100 individual cells and analyzed using the ProteinChip technology; SELDI: surface-enhanced laser desorption and ionization. As a result, numerous protein signals that were differentially expressed in the three epidermal cell types could be detected. One of these proteins was characterized by tryptical digestion and subsequent identification via tandem quadrupole-time of flight (Q-TOF) mass spectrometry. Down regulation of this sequenced small subunit precursor of ribulose-1,5 bisphosphate carboxylase(C) oxygenase(O) (RuBisCo) in trichome and basal cells indicates the sink status of these cell types that are located on the surface of A. thaliana source leaves. Based on the obtained protein profiles, we suggest a close functional relationship between basal and trichome cells at the protein level.

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

PubMed

Zhu, Zhi; Yang, Chaoyong James

2017-01-17

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

Transcriptogenomics identification and characterization of RNA editing sites in human primary monocytes using high-depth next generation sequencing data.

PubMed

Leong, Wai-Mun; Ripen, Adiratna Mat; Mirsafian, Hoda; Mohamad, Saharuddin Bin; Merican, Amir Feisal

2018-06-07

High-depth next generation sequencing data provide valuable insights into the number and distribution of RNA editing events. Here, we report the RNA editing events at cellular level of human primary monocyte using high-depth whole genomic and transcriptomic sequencing data. We identified over a ten thousand putative RNA editing sites and 69% of the sites were A-to-I editing sites. The sites enriched in repetitive sequences and intronic regions. High-depth sequencing datasets revealed that 90% of the canonical sites were edited at lower frequencies (<0.7). Single and multiple human monocytes and brain tissues samples were analyzed through genome sequence independent approach. The later approach was observed to identify more editing sites. Monocytes was observed to contain more C-to-U editing sites compared to brain tissues. Our results establish comparable pipeline that can address current limitations as well as demonstrate the potential for highly sensitive detection of RNA editing events in single cell type. Copyright © 2018 Elsevier Inc. All rights reserved.

Multiplexed enrichment of rare DNA variants via sequence-selective and temperature-robust amplification

PubMed Central

Wu, Lucia R.; Chen, Sherry X.; Wu, Yalei; Patel, Abhijit A.; Zhang, David Yu

2018-01-01

Rare DNA-sequence variants hold important clinical and biological information, but existing detection techniques are expensive, complex, allele-specific, or don’t allow for significant multiplexing. Here, we report a temperature-robust polymerase-chain-reaction method, which we term blocker displacement amplification (BDA), that selectively amplifies all sequence variants, including single-nucleotide variants (SNVs), within a roughly 20-nucleotide window by 1,000-fold over wild-type sequences. This allows for easy detection and quantitation of hundreds of potential variants originally at ≤0.1% in allele frequency. BDA is compatible with inexpensive thermocycler instrumentation and employs a rationally designed competitive hybridization reaction to achieve comparable enrichment performance across annealing temperatures ranging from 56 °C to 64 °C. To show the sequence generality of BDA, we demonstrate enrichment of 156 SNVs and the reliable detection of single-digit copies. We also show that the BDA detection of rare driver mutations in cell-free DNA samples extracted from the blood plasma of lung-cancer patients is highly consistent with deep sequencing using molecular lineage tags, with a receiver operator characteristic accuracy of 95%. PMID:29805844

A Single Multiplex crRNA Array for FnCpf1-Mediated Human Genome Editing.

PubMed

Sun, Huihui; Li, Fanfan; Liu, Jie; Yang, Fayu; Zeng, Zhenhai; Lv, Xiujuan; Tu, Mengjun; Liu, Yeqing; Ge, Xianglian; Liu, Changbao; Zhao, Junzhao; Zhang, Zongduan; Qu, Jia; Song, Zongming; Gu, Feng

2018-06-15

Cpf1 has been harnessed as a tool for genome manipulation in various species because of its simplicity and high efficiency. Our recent study demonstrated that FnCpf1 could be utilized for human genome editing with notable advantages for target sequence selection due to the flexibility of the protospacer adjacent motif (PAM) sequence. Multiplex genome editing provides a powerful tool for targeting members of multigene families, dissecting gene networks, modeling multigenic disorders in vivo, and applying gene therapy. However, there are no reports at present that show FnCpf1-mediated multiplex genome editing via a single customized CRISPR RNA (crRNA) array. In the present study, we utilize a single customized crRNA array to simultaneously target multiple genes in human cells. In addition, we also demonstrate that a single customized crRNA array to target multiple sites in one gene could be achieved. Collectively, FnCpf1, a powerful genome-editing tool for multiple genomic targets, can be harnessed for effective manipulation of the human genome. Copyright © 2018 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs.

PubMed

Parekh, Swati; Ziegenhain, Christoph; Vieth, Beate; Enard, Wolfgang; Hellmann, Ines

2018-06-01

Single-cell RNA-sequencing (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific bar codes (BCs), and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus, the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI. zUMIs is a pipeline that can handle both known and random BCs and also efficiently collapse UMIs, either just for exon mapping reads or for both exon and intron mapping reads. If BC annotation is missing, zUMIs can accurately detect intact cells from the distribution of sequencing reads. Another unique feature of zUMIs is the adaptive downsampling function that facilitates dealing with hugely varying library sizes but also allows the user to evaluate whether the library has been sequenced to saturation. To illustrate the utility of zUMIs, we analyzed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to introns. Also, we show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution. zUMIs flexibility makes if possible to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs and is the most feature-rich, fast, and user-friendly pipeline to process such scRNA-seq data.

DNA confinement in nanochannels: physics and biological applications

NASA Astrophysics Data System (ADS)

Reisner, Walter; Pedersen, Jonas N.; Austin, Robert H.

2012-10-01

DNA is the central storage molecule of genetic information in the cell, and reading that information is a central problem in biology. While sequencing technology has made enormous advances over the past decade, there is growing interest in platforms that can readout genetic information directly from long single DNA molecules, with the ultimate goal of single-cell, single-genome analysis. Such a capability would obviate the need for ensemble averaging over heterogeneous cellular populations and eliminate uncertainties introduced by cloning and molecular amplification steps (thus enabling direct assessment of the genome in its native state). In this review, we will discuss how the information contained in genomic-length single DNA molecules can be accessed via physical confinement in nanochannels. Due to self-avoidance interactions, DNA molecules will stretch out when confined in nanochannels, creating a linear unscrolling of the genome along the channel for analysis. We will first review the fundamental physics of DNA nanochannel confinement—including the effect of varying ionic strength—and then discuss recent applications of these systems to genomic mapping. Apart from the intense biological interest in extracting linear sequence information from elongated DNA molecules, from a physics view these systems are fascinating as they enable probing of single-molecule conformation in environments with dimensions that intersect key physical length-scales in the 1 nm to 100 µm range.

DNA confinement in nanochannels: physics and biological applications.

PubMed

Reisner, Walter; Pedersen, Jonas N; Austin, Robert H

2012-10-01

DNA is the central storage molecule of genetic information in the cell, and reading that information is a central problem in biology. While sequencing technology has made enormous advances over the past decade, there is growing interest in platforms that can readout genetic information directly from long single DNA molecules, with the ultimate goal of single-cell, single-genome analysis. Such a capability would obviate the need for ensemble averaging over heterogeneous cellular populations and eliminate uncertainties introduced by cloning and molecular amplification steps (thus enabling direct assessment of the genome in its native state). In this review, we will discuss how the information contained in genomic-length single DNA molecules can be accessed via physical confinement in nanochannels. Due to self-avoidance interactions, DNA molecules will stretch out when confined in nanochannels, creating a linear unscrolling of the genome along the channel for analysis. We will first review the fundamental physics of DNA nanochannel confinement--including the effect of varying ionic strength--and then discuss recent applications of these systems to genomic mapping. Apart from the intense biological interest in extracting linear sequence information from elongated DNA molecules, from a physics view these systems are fascinating as they enable probing of single-molecule conformation in environments with dimensions that intersect key physical length-scales in the 1 nm to 100 µm range.

Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes and progenitors

PubMed Central

Villani, Alexandra-Chloé; Satija, Rahul; Reynolds, Gary; Sarkizova, Siranush; Shekhar, Karthik; Fletcher, James; Griesbeck, Morgane; Butler, Andrew; Zheng, Shiwei; Lazo, Suzan; Jardine, Laura; Dixon, David; Stephenson, Emily; Nilsson, Emil; Grundberg, Ida; McDonald, David; Filby, Andrew; Li, Weibo; De Jager, Philip L.; Rozenblatt-Rosen, Orit; Lane, Andrew A.; Haniffa, Muzlifah; Regev, Aviv; Hacohen, Nir

2017-01-01

Dendritic cells (DCs) and monocytes play a central role in pathogen sensing, phagocytosis and antigen presentation and consist of multiple specialized subtypes. However, their identities and interrelationships are not fully understood. Using unbiased single-cell RNA sequencing (RNA-seq) of ~2400 cells, we identified six human DCs and four monocyte subtypes in human blood. Our study reveals: a new DC subset that shares properties with plasmacytoid DCs (pDCs) but potently activates T cells, thus redefining pDCs; a new subdivision within the CD1C+ subset of DCs; the relationship between blastic plasmacytoid DC neoplasia cells and healthy DCs; and circulating progenitor of conventional DCs (cDCs). Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. PMID:28428369

A genotyping system capable of simultaneously analyzing >1000 single nucleotide polymorphisms in a haploid genome.

PubMed

Wang, Hui-Yun; Luo, Minjie; Tereshchenko, Irina V; Frikker, Danielle M; Cui, Xiangfeng; Li, James Y; Hu, Guohong; Chu, Yi; Azaro, Marco A; Lin, Yong; Shen, Li; Yang, Qifeng; Kambouris, Manousos E; Gao, Richeng; Shih, Weichung; Li, Honghua

2005-02-01

A high-throughput genotyping system for scoring single nucleotide polymorphisms (SNPs) has been developed. With this system, >1000 SNPs can be analyzed in a single assay, with a sensitivity that allows the use of single haploid cells as starting material. In the multiplex polymorphic sequence amplification step, instead of attaching universal sequences to the amplicons, primers that are unlikely to have nonspecific and productive interactions are used. Genotypes of SNPs are then determined by using the widely accessible microarray technology and the simple single-base extension assay. Three SNP panels, each consisting of >1000 SNPs, were incorporated into this system. The system was used to analyze 24 human genomic DNA samples. With 5 ng of human genomic DNA, the average detection rate was 98.22% when single probes were used, and 96.71% could be detected by dual probes in different directions. When single sperm cells were used, 91.88% of the SNPs were detectable, which is comparable to the level that was reached when very few genetic markers were used. By using a dual-probe assay, the average genotyping accuracy was 99.96% for 5 ng of human genomic DNA and 99.95% for single sperm. This system may be used to significantly facilitate large-scale genetic analysis even if the amount of DNA template is very limited or even highly degraded as that obtained from paraffin-embedded cancer specimens, and to make many unpractical research projects highly realistic and affordable.

CD4+ T-cell recovery with suppressive ART-induced rapid sequence evolution in hepatitis C virus envelope but not NS3.

PubMed

Liu, Lin; Nardo, David; Li, Eric; Wang, Gary P

2016-03-13

CD4 T-cell depletion from HIV infection leads to a global decline in anti-hepatitis C virus (HCV) envelope neutralizing antibody (nAb) response, which may play a role in accelerating liver fibrosis. An increase in anti-HCV nAb titers has been reported during antiretroviral therapy (ART) but its impact on HCV remains poorly understood. The objective of this study is to determine the effects of ART on long-term HCV evolution. We examined HCV quasispecies structure and long-term evolution in HIV/HCV coinfected patients with ART-induced CD4 T-cell recovery, and compared with patients with CD4 T-cell depletion from delayed ART. We applied a single-variant sequencing (SVS) method to construct authentic viral quasispecies and compared sequence evolution in HCV envelope, the primary target for humoral immune responses, and NS3, a target for cellular immunity, between the two cohorts. The SVS method corrected biases known to skew the proportions of viral variants, revealing authentic HCV quasispeices structures. We observed higher rates of HCV envelope sequence evolution in patients with ART-induced CD4 T-cell recovery, compared with patients with CD4 T-cell depletion from delayed ART (P = 0.03). Evolutionary rates for NS3 were considerably lower than the rates for envelope (P < 0.01), with no significant difference observed between the two groups. ART-induced CD4 T-cell recovery results in rapid sequence evolution in HCV envelope, but not in NS3. These results suggest that suppressive ART disproportionally enhances HCV-specific humoral responses more than cellular responses, resulting in rapid sequence evolution in HCV envelope but not NS3.

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

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

PubMed

Menon, Vilas

2017-12-11

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

Single-cell 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.

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.

Single-Stranded γPNAs for In Vivo Site-Specific Genome Editing via Watson-Crick Recognition

PubMed Central

Bahal, Raman; Quijano, Elias; McNeer, Nicole Ali; Liu, Yanfeng; Bhunia, Dinesh C.; López-Giráldez, Francesco; Fields, Rachel J.; Saltzman, W. Mark; Ly, Danith H.; Glazer, Peter M.

2014-01-01

Triplex-forming peptide nucleic acids (PNAs) facilitate gene editing by stimulating recombination of donor DNAs within genomic DNA via site-specific formation of altered helical structures that further stimulate DNA repair. However, PNAs designed for triplex formation are sequence restricted to homopurine sites. Herein we describe a novel strategy where next generation single-stranded gamma PNAs (γPNAs) containing miniPEG substitutions at the gamma position can target genomic DNA in mouse bone marrow at mixed-sequence sites to induce targeted gene editing. In addition to enhanced binding, γPNAs confer increased solubility and improved formulation into poly(lactic-co-glycolic acid) (PLGA) nanoparticles for efficient intracellular delivery. Single-stranded γPNAs induce targeted gene editing at frequencies of 0.8% in mouse bone marrow cells treated ex vivo and 0.1% in vivo via IV injection, without detectable toxicity. These results suggest that γPNAs may provide a new tool for induced gene editing based on Watson-Crick recognition without sequence restriction. PMID:25174576

Single-stranded γPNAs for in vivo site-specific genome editing via Watson-Crick recognition.

PubMed

Bahal, Raman; Quijano, Elias; McNeer, Nicole A; Liu, Yanfeng; Bhunia, Dinesh C; Lopez-Giraldez, Francesco; Fields, Rachel J; Saltzman, William M; Ly, Danith H; Glazer, Peter M

2014-01-01

Triplex-forming peptide nucleic acids (PNAs) facilitate gene editing by stimulating recombination of donor DNAs within genomic DNA via site-specific formation of altered helical structures that further stimulate DNA repair. However, PNAs designed for triplex formation are sequence restricted to homopurine sites. Herein we describe a novel strategy where next generation single-stranded gamma PNAs (γPNAs) containing miniPEG substitutions at the gamma position can target genomic DNA in mouse bone marrow at mixed-sequence sites to induce targeted gene editing. In addition to enhanced binding, γPNAs confer increased solubility and improved formulation into poly(lactic-co-glycolic acid) (PLGA) nanoparticles for efficient intracellular delivery. Single-stranded γPNAs induce targeted gene editing at frequencies of 0.8% in mouse bone marrow cells treated ex vivo and 0.1% in vivo via IV injection, without detectable toxicity. These results suggest that γPNAs may provide a new tool for induced gene editing based on Watson-Crick recognition without sequence restriction.

Analysis of xylem formation in pine by cDNA sequencing

NASA Technical Reports Server (NTRS)

Allona, I.; Quinn, M.; Shoop, E.; Swope, K.; St Cyr, S.; Carlis, J.; Riedl, J.; Retzel, E.; Campbell, M. M.; Sederoff, R.;

Effect of Temporal Pattern of Radiation in Intensity Modulated Radiotherapy on Cell Cycle Progression and Apoptosis of ACHN Renal Cell Carcinoma Cell Line.

PubMed

Khorramizadeh, Maryam; Saberi, Alihossein; Tahmasebi-Birgani, Mohammadjavad; Shokrani, Parvaneh; Amouhedari, Alireza

The existence of a hypersensitive radiation response to doses below 1 Gy is well established for many normal and tumor cell lines. The aim of this study was to ascertain the impact of temporal pattern modeling IMRT on survival, cell cycle and apoptosis of human RCC cell line ACHN, so as to provide radiobiological basis for optimizing IMRT plans for this disease. The ACHN renal cell carcinoma cell line was used in this study. Impact of the triangle, V, small-large or large-small temporal patterns in the presence and absence of threshold dose of hyper-radiosensitivity at the beginning of patterns were studied using soft agarclonogenic assays. Cell cycle and apoptosis analysis were performed after irradiation with the temporal patterns. For triangle and small-large dose sequences, survival fraction was significantly reduced after irradiation with or without threshold dose of hyper-radiosensitivity at the beginning of the patterns. In all of the dose patterns, cell cycle distributions and the percentage of apoptotic cells at 24 h after irradiation with or without priming dose of hyper-radiosensitivity showed no significant difference. However, apoptotic cells were increased when beams with the smallest dose applied at the beginning of dose pattern like triangle and small-large dose sequence. These data show that the biologic effects of single fraction may differ in clinical settings depending on the size and sequence of the partial fractions. Doses at the beginning but not at the end of sequences may change cytotoxicity effects of radiation.

Tilted pillar array fabrication by the combination of proton beam writing and soft lithography for microfluidic cell capture Part 2: Image sequence analysis based evaluation and biological application.

PubMed

Járvás, Gábor; Varga, Tamás; Szigeti, Márton; Hajba, László; Fürjes, Péter; Rajta, István; Guttman, András

2018-02-01

As a continuation of our previously published work, this paper presents a detailed evaluation of a microfabricated cell capture device utilizing a doubly tilted micropillar array. The device was fabricated using a novel hybrid technology based on the combination of proton beam writing and conventional lithography techniques. Tilted pillars offer unique flow characteristics and support enhanced fluidic interaction for improved immunoaffinity based cell capture. The performance of the microdevice was evaluated by an image sequence analysis based in-house developed single-cell tracking system. Individual cell tracking allowed in-depth analysis of the cell-chip surface interaction mechanism from hydrodynamic point of view. Simulation results were validated by using the hybrid device and the optimized surface functionalization procedure. Finally, the cell capture capability of this new generation microdevice was demonstrated by efficiently arresting cells from a HT29 cell-line suspension. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Accurate multiplex polony sequencing of an evolved bacterial genome.

PubMed

Shendure, Jay; Porreca, Gregory J; Reppas, Nikos B; Lin, Xiaoxia; McCutcheon, John P; Rosenbaum, Abraham M; Wang, Michael D; Zhang, Kun; Mitra, Robi D; Church, George M

2005-09-09

We describe a DNA sequencing technology in which a commonly available, inexpensive epifluorescence microscope is converted to rapid nonelectrophoretic DNA sequencing automation. We apply this technology to resequence an evolved strain of Escherichia coli at less than one error per million consensus bases. A cell-free, mate-paired library provided single DNA molecules that were amplified in parallel to 1-micrometer beads by emulsion polymerase chain reaction. Millions of beads were immobilized in a polyacrylamide gel and subjected to automated cycles of sequencing by ligation and four-color imaging. Cost per base was roughly one-ninth as much as that of conventional sequencing. Our protocols were implemented with off-the-shelf instrumentation and reagents.

High-throughput automated microfluidic sample preparation for accurate microbial genomics

PubMed Central

Kim, Soohong; De Jonghe, Joachim; Kulesa, Anthony B.; Feldman, David; Vatanen, Tommi; Bhattacharyya, Roby P.; Berdy, Brittany; Gomez, James; Nolan, Jill; Epstein, Slava; Blainey, Paul C.

2017-01-01

Low-cost shotgun DNA sequencing is transforming the microbial sciences. Sequencing instruments are so effective that sample preparation is now the key limiting factor. Here, we introduce a microfluidic sample preparation platform that integrates the key steps in cells to sequence library sample preparation for up to 96 samples and reduces DNA input requirements 100-fold while maintaining or improving data quality. The general-purpose microarchitecture we demonstrate supports workflows with arbitrary numbers of reaction and clean-up or capture steps. By reducing the sample quantity requirements, we enabled low-input (∼10,000 cells) whole-genome shotgun (WGS) sequencing of Mycobacterium tuberculosis and soil micro-colonies with superior results. We also leveraged the enhanced throughput to sequence ∼400 clinical Pseudomonas aeruginosa libraries and demonstrate excellent single-nucleotide polymorphism detection performance that explained phenotypically observed antibiotic resistance. Fully-integrated lab-on-chip sample preparation overcomes technical barriers to enable broader deployment of genomics across many basic research and translational applications. PMID:28128213

An improved filtering algorithm for big read datasets and its application to single-cell assembly.

PubMed

Wedemeyer, Axel; Kliemann, Lasse; Srivastav, Anand; Schielke, Christian; Reusch, Thorsten B; Rosenstiel, Philip

2017-07-03

For single-cell or metagenomic sequencing projects, it is necessary to sequence with a very high mean coverage in order to make sure that all parts of the sample DNA get covered by the reads produced. This leads to huge datasets with lots of redundant data. A filtering of this data prior to assembly is advisable. Brown et al. (2012) presented the algorithm Diginorm for this purpose, which filters reads based on the abundance of their k-mers. We present Bignorm, a faster and quality-conscious read filtering algorithm. An important new algorithmic feature is the use of phred quality scores together with a detailed analysis of the k-mer counts to decide which reads to keep. We qualify and recommend parameters for our new read filtering algorithm. Guided by these parameters, we remove in terms of median 97.15% of the reads while keeping the mean phred score of the filtered dataset high. Using the SDAdes assembler, we produce assemblies of high quality from these filtered datasets in a fraction of the time needed for an assembly from the datasets filtered with Diginorm. We conclude that read filtering is a practical and efficient method for reducing read data and for speeding up the assembly process. This applies not only for single cell assembly, as shown in this paper, but also to other projects with high mean coverage datasets like metagenomic sequencing projects. Our Bignorm algorithm allows assemblies of competitive quality in comparison to Diginorm, while being much faster. Bignorm is available for download at https://git.informatik.uni-kiel.de/axw/Bignorm .

Dual-slit confocal light sheet microscopy for in vivo whole-brain imaging of zebrafish

PubMed Central

Yang, Zhe; Mei, Li; Xia, Fei; Luo, Qingming; Fu, Ling; Gong, Hui

2015-01-01

In vivo functional imaging at single-neuron resolution is an important approach to visualize biological processes in neuroscience. Light sheet microscopy (LSM) is a cutting edge in vivo imaging technique that provides micron-scale spatial resolution at high frame rate. Due to the scattering and absorption of tissue, however, conventional LSM is inadequate to resolve cells because of the attenuated signal to noise ratio (SNR). Using dual-beam illumination and confocal dual-slit detection, here a dual-slit confocal LSM is demonstrated to obtain the SNR enhanced images with frame rate twice as high as line confocal LSM method. Through theoretical calculations and experiments, the correlation between the slit’s width and SNR was determined to optimize the image quality. In vivo whole brain structural imaging stacks and the functional imaging sequences of single slice were obtained for analysis of calcium activities at single-cell resolution. A two-fold increase in imaging speed of conventional confocal LSM makes it possible to capture the sequence of the neurons’ activities and help reveal the potential functional connections in the whole zebrafish’s brain. PMID:26137381

Sequence of a cDNA encoding pancreatic preprosomatostatin-22.

PubMed Central

Magazin, M; Minth, C D; Funckes, C L; Deschenes, R; Tavianini, M A; Dixon, J E

1982-01-01

We report the nucleotide sequence of a precursor to somatostatin that upon proteolytic processing may give rise to a hormone of 22 amino acids. The nucleotide sequence of a cDNA from the channel catfish (Ictalurus punctatus) encodes a precursor to somatostatin that is 105 amino acids (Mr, 11,500). The cDNA coding for somatostatin-22 consists of 36 nucleotides in the 5' untranslated region, 315 nucleotides that code for the precursor to somatostatin-22, 269 nucleotides at the 3' untranslated region, and a variable length of poly(A). The putative preprohormone contains a sequence of hydrophobic amino acids at the amino terminus that has the properties of a "signal" peptide. A connecting sequence of approximately 57 amino acids is followed by a single Arg-Arg sequence, which immediately precedes the hormone. Somatostatin-22 is homologous to somatostatin-14 in 7 of the 14 amino acids, including the Phe-Trp-Lys sequence. Hybridization selection of mRNA, followed by its translation in a wheat germ cell-free system, resulted in the synthesis of a single polypeptide having a molecular weight of approximately 10,000 as estimated on Na-DodSO4/polyacrylamide gels. Images PMID:6127673

[Application of droplet digital PCR for non-invasive prenatal diagnosis of single gene disease in two families].

PubMed

Xu, Peiwen; Zou, Yang; Li, Jie; Huang, Sexin; Gao, Ming; Kang, Ranran; Xie, Hongqiang; Wang, Lijuan; Yan, Junhao; Gao, Yuan

2018-04-10

To assess the value of droplet digital PCR (ddPCR) for non-invasive prenatal diagnosis of single gene disease in two families. Paternal mutation in cell-free DNA derived from the maternal blood and amniotic fluid DNA was detected by ddPCR. Suspected mutation in the amniotic fluid DNA was verified with Sanger sequencing. The result of ddPCR and Sanger sequencing indicated that the fetuses have carried pathogenic mutations from the paternal side in both families. Droplet digital PCR can accurately detect paternal mutation carried by the fetus, and it is sensitive and reliable for analyzing trace samples. This method may be applied for the diagnosis of single gene diseases caused by paternal mutation using peripheral blood sample derived from the mother.

CRISPR-Cas9-Edited Site Sequencing (CRES-Seq): An Efficient and High-Throughput Method for the Selection of CRISPR-Cas9-Edited Clones.

PubMed

Veeranagouda, Yaligara; Debono-Lagneaux, Delphine; Fournet, Hamida; Thill, Gilbert; Didier, Michel

2018-01-16

The emergence of clustered regularly interspaced short palindromic repeats-Cas9 (CRISPR-Cas9) gene editing systems has enabled the creation of specific mutants at low cost, in a short time and with high efficiency, in eukaryotic cells. Since a CRISPR-Cas9 system typically creates an array of mutations in targeted sites, a successful gene editing project requires careful selection of edited clones. This process can be very challenging, especially when working with multiallelic genes and/or polyploid cells (such as cancer and plants cells). Here we described a next-generation sequencing method called CRISPR-Cas9 Edited Site Sequencing (CRES-Seq) for the efficient and high-throughput screening of CRISPR-Cas9-edited clones. CRES-Seq facilitates the precise genotyping up to 96 CRISPR-Cas9-edited sites (CRES) in a single MiniSeq (Illumina) run with an approximate sequencing cost of $6/clone. CRES-Seq is particularly useful when multiple genes are simultaneously targeted by CRISPR-Cas9, and also for screening of clones generated from multiallelic genes/polyploid cells. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Patterns of Viral DNA Integration in Cells Transformed by Wild Type or DNA-Binding Protein Mutants of Adenovirus Type 5 and Effect of Chemical Carcinogens on Integration

PubMed Central

Dorsch-Häsler, Karoline; Fisher, Paul B.; Weinstein, I. Bernard; Ginsberg, Harold S.

1980-01-01

The integration pattern of viral DNA was studied in a number of cell lines transformed by wild-type adenovirus type 5 (Ad5 WT) and two mutants of the DNA-binding protein gene, H5ts125 and H5ts107. The effect of chemical carcinogens on the integration of viral DNA was also investigated. Liquid hybridization (C0t) analyses showed that rat embryo cells transformed by Ad5 WT usually contained only the left-hand end of the viral genome, whereas cell lines transformed by H5ts125 or H5ts107 at either the semipermissive (36°C) or nonpermissive (39.5°C) temperature often contained one to five copies of all or most of the entire adenovirus genome. The arrangement of the integrated adenovirus DNA sequences was determined by cleavage of transformed cell DNA with restriction endonucleases XbaI, EcoRI, or HindIII followed by transfer of separated fragments to nitrocellulose paper and hybridization according to the technique of E. M. Southern (J. Mol. Biol. 98: 503-517, 1975). It was found that the adenovirus genome is integrated as a linear sequence covalently linked to host cell DNA; that the viral DNA is integrated into different host DNA sequences in each cell line studied; that in cell lines that contain multiple copies of the Ad5 genome the viral DNA sequences can be integrated in a single set of host cell DNA sequences and not as concatemers; and that chemical carcinogens do not alter the extent or pattern of viral DNA integration. Images PMID:6246266

Phylogenetic analysis of the complete genome of 11 BKV isolates obtained from allogenic stem cell transplant recipients in Ireland.

PubMed

Drew, Richard John; Walsh, Anne; Laoi, Bairbre Ni; Crowley, Brendan

2012-07-01

BK polyomavirus (family Polyomaviridae) may cause hemorrhagic cystitis (BKV-HC) in hematopoietic stem cell transplant recipients. Eleven complete BKV genomes (GenBank accession numbers: JN192431-JN192441) were sequenced from urine samples of allogenic hematopoietic stem cell transplant recipients and compared to complete BKV genomes in the published literature. Of the 11 isolates, seven (64%) were subgroup Ib-1, three (27%) isolates belonged to subgroup Ib-2 and a single isolate belonged to subtype III. The analysis of single-nucleotide polymorphisms in this study showed that isolates could be subclassified into subtypes I-IV and subgroups Ib-1 and Ib-2 on the basis of VP1 of the first part of the Large T-antigen (LTag). The non-coding control region (NCCR) of the 11 isolates was also sequenced. These sequences showed that there was consistent sequence homology within subgroups Ib-1 and Ib-2. Two new mutations were described in the isolates, G→C at O(84) in isolate SJH-LG-310, and a deletion at R(2-7) in isolate SJH-LG-309. No known transcription factor is thought to be present at the site of either of these mutations. There were no rearrangements seen in isolates and this may be because the patients were not followed up over time. There were five nucleotide positions at which subgroup Ib-1 isolated differed from subgroup Ib-2 isolates in the NCCR sequence, O(41) , P(18) , P(31) , R(4) , and S(18) . The mutation O(41) is present in the promoter granulocyte/macrophage stimulating factor) gene and the P(31) mutation is present in the NF-1 gene. Copyright © 2012 Wiley Periodicals, Inc.

Single-Cell Genome and Group-Specific dsrAB Sequencing Implicate Marine Members of the Class Dehalococcoidia (Phylum Chloroflexi) in Sulfur Cycling

PubMed Central

Cooper, Myriel; Schreiber, Lars; Lloyd, Karen G.; Baker, Brett J.; Petersen, Dorthe G.; Jørgensen, Bo Barker; Stepanauskas, Ramunas; Reinhardt, Richard; Schramm, Andreas; Loy, Alexander; Adrian, Lorenz

2016-01-01

ABSTRACT The marine subsurface sediment biosphere is widely inhabited by bacteria affiliated with the class Dehalococcoidia (DEH), phylum Chloroflexi, and yet little is known regarding their metabolisms. In this report, genomic content from a single DEH cell (DEH-C11) with a 16S rRNA gene that was affiliated with a diverse cluster of 16S rRNA gene sequences prevalent in marine sediments was obtained from sediments of Aarhus Bay, Denmark. The distinctive gene content of this cell suggests metabolic characteristics that differ from those of known DEH and Chloroflexi. The presence of genes encoding dissimilatory sulfite reductase (Dsr) suggests that DEH could respire oxidized sulfur compounds, although Chloroflexi have never been implicated in this mode of sulfur cycling. Using long-range PCR assays targeting DEH dsr loci, dsrAB genes were amplified and sequenced from various marine sediments. Many of the amplified dsrAB sequences were affiliated with the DEH Dsr clade, which we propose equates to a family-level clade. This provides supporting evidence for the potential for sulfite reduction by diverse DEH species. DEH-C11 also harbored genes encoding reductases for arsenate, dimethyl sulfoxide, and halogenated organics. The reductive dehalogenase homolog (RdhA) forms a monophyletic clade along with RdhA sequences from various DEH-derived contigs retrieved from available metagenomes. Multiple facts indicate that this RdhA may not be a terminal reductase. The presence of other genes indicated that nutrients and energy may be derived from the oxidation of substituted homocyclic and heterocyclic aromatic compounds. Together, these results suggest that marine DEH play a previously unrecognized role in sulfur cycling and reveal the potential for expanded catabolic and respiratory functions among subsurface DEH. PMID:27143384

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.

Texture analysis of common renal masses in multiple MR sequences for prediction of pathology

NASA Astrophysics Data System (ADS)

Hoang, Uyen N.; Malayeri, Ashkan A.; Lay, Nathan S.; Summers, Ronald M.; Yao, Jianhua

2017-03-01

This pilot study performs texture analysis on multiple magnetic resonance (MR) images of common renal masses for differentiation of renal cell carcinoma (RCC). Bounding boxes are drawn around each mass on one axial slice in T1 delayed sequence to use for feature extraction and classification. All sequences (T1 delayed, venous, arterial, pre-contrast phases, T2, and T2 fat saturated sequences) are co-registered and texture features are extracted from each sequence simultaneously. Random forest is used to construct models to classify lesions on 96 normal regions, 87 clear cell RCCs, 8 papillary RCCs, and 21 renal oncocytomas; ground truths are verified through pathology reports. The highest performance is seen in random forest model when data from all sequences are used in conjunction, achieving an overall classification accuracy of 83.7%. When using data from one single sequence, the overall accuracies achieved for T1 delayed, venous, arterial, and pre-contrast phase, T2, and T2 fat saturated were 79.1%, 70.5%, 56.2%, 61.0%, 60.0%, and 44.8%, respectively. This demonstrates promising results of utilizing intensity information from multiple MR sequences for accurate classification of renal masses.

Ovulation

MedlinePlus Videos and Cool Tools

... sequence of hormonal responses. Located deep within the brain, the pituitary gland releases the hormones FSH and LH, which travel through the blood stream to the ovaries. These hormones signal the development and release a single egg cell from one of the ovaries. The sweeping motion ...

A genetically encoded tool kit for manipulating and monitoring membrane phosphatidylinositol 4,5-bisphosphate in intact cells.

PubMed

Hertel, Fabian; Switalski, Agathe; Mintert-Jancke, Elisa; Karavassilidou, Katharina; Bender, Kirsten; Pott, Lutz; Kienitz, Marie-Cécile

2011-01-01

Most ion channels are regulated by phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P(2)) in the cell membrane by diverse mechanisms. Important molecular tools to study ion channel regulation by PtdIns(4,5)P(2) in living cells have been developed in the past. These include fluorescent PH-domains as sensors for Förster resonance energy transfer (FRET), to monitor changes in plasma membrane(.) For controlled and reversible depletion of PtdIns(4,5)P(2), voltage-sensing phosphoinositide phosphatases (VSD) have been demonstrated as a superior tool, since they are independent of cellular signaling pathways. Combining these methods in intact cells requires multiple transfections. We used self-cleaving viral 2A-peptide sequences for adenovirus driven expression of the PH-domain of phospholipase-Cδ1 (PLCδ1) fused to ECFP and EYFP respectively and Ciona intestinalis VSP (Ci-VSP), from a single open reading frame (ORF) in adult rat cardiac myocytes. Expression and correct targeting of ECFP-PH-PLCδ1(,) EYFP-PH-PLCδ1, and Ci-VSP from a single tricistronic vector containing 2A-peptide sequences first was demonstrated in HEK293 cells by voltage-controlled FRET measurements and Western blotting. Adult rat cardiac myocytes expressed Ci-VSP and the two fluorescent PH-domains within 4 days after gene transfer using the vector integrated into an adenoviral construct. Activation of Ci-VSP by depolarization resulted in rapid changes in FRET ratio indicating depletion of PtdIns(4,5)P(2) in the plasma membrane. This was paralleled by inhibition of endogenous G protein activated K(+) (GIRK) current. By comparing changes in FRET and current, a component of GIRK inhibition by adrenergic receptors unrelated to depletion of PtdIns(4,5)P(2) was identified. Expression of a FRET sensor pair and Ci-VSP from a single ORF provides a useful approach to study regulation of ion channels by phosphoinositides in cell lines and transfection-resistant postmitotic cells. Generally, adenoviral constructs containing self-cleaving 2A-peptide sequences are highly suited for simultaneous transfer of multiple genes in adult cardiac myocytes.

'Cold shock' increases the frequency of homology directed repair gene editing in induced pluripotent stem cells.

PubMed

Guo, Q; Mintier, G; Ma-Edmonds, M; Storton, D; Wang, X; Xiao, X; Kienzle, B; Zhao, D; Feder, John N

2018-02-01

Using CRISPR/Cas9 delivered as a RNA modality in conjunction with a lipid specifically formulated for large RNA molecules, we demonstrate that homology directed repair (HDR) rates between 20-40% can be achieved in induced pluripotent stem cells (iPSC). Furthermore, low HDR rates (between 1-20%) can be enhanced two- to ten-fold in both iPSCs and HEK293 cells by 'cold shocking' cells at 32 °C for 24-48 hours following transfection. This method can also increases the proportion of loci that have undergone complete sequence conversion across the donor sequence, or 'perfect HDR', as opposed to partial sequence conversion where nucleotides more distal to the CRISPR cut site are less efficiently incorporated ('partial HDR'). We demonstrate that the structure of the single-stranded DNA oligo donor can influence the fidelity of HDR, with oligos symmetric with respect to the CRISPR cleavage site and complementary to the target strand being more efficient at directing 'perfect HDR' compared to asymmetric non-target strand complementary oligos. Our protocol represents an efficient method for making CRISPR-mediated, specific DNA sequence changes within the genome that will facilitate the rapid generation of genetic models of human disease in iPSCs as well as other genome engineered cell lines.

Effects of Different Materials Used for Internal Floating Electrode on the Photovoltaic Properties of Tandem Type Organic Solar Cell

NASA Astrophysics Data System (ADS)

Triyana, Kuwat; Yasuda, Takeshi; Fujita, Katsuhiko; Tsutsui, Tetsuo

2004-04-01

Three thin heterojunctions sandwiched between indium tin oxide (ITO) and the top electrode as triple-heterojunction organic solar cells have been fabricated. Each heterojunction cell consists of CuPc as a donor layer and perilene tetracrboxylic-bis-benzimidazole (PTCBI) as an acceptor layer. Ultra thin (1 nm average thickness) layers of Ag or Au have been inserted between two heterojunctions as an internal electrode. Ag and Au were chosen as materials both for internal floating and top electrodes. Influences of different deposition sequences of the organic layer in each heterojunction cell and different electrode materials were also investigated. The optimum devices were obtained when the same material was used both as an internal electrode and a top electrode. When the deposition sequence of the heterojunction is PTCBI/CuPc, the most suitable electrode is Au and the ITO is negative relative to the top electrode. Meanwhile, Ag is suitable for an electrode when the deposition sequence is CuPc/PTCBI. In this second deposition sequence, the ITO is positive relative to the top electrode. The open circuit voltage (Voc) of both optimum devices is on the order of 1.35-1.5 V. These values are approximately three times higher than that in single-heterojunction organic solar cells.

A comparison of the effects of temporary hippocampal lesions on single and dual context versions of the olfactory sequence memory task.

PubMed

Sill, Orriana C; Smith, David M

2012-08-01

In recent years, many animal models of memory have focused on one or more of the various components of episodic memory. For example, the odor sequence memory task requires subjects to remember individual items and events (the odors) and the temporal aspects of the experience (the sequence of odor presentation). The well-known spatial context coding function of the hippocampus, as exemplified by place cell firing, may reflect the "where" component of episodic memory. In the present study, we added a contextual component to the odor sequence memory task by training rats to choose the earlier odor in one context and the later odor in another context and we compared the effects of temporary hippocampal lesions on performance of the original single context task and the new dual context task. Temporary lesions significantly impaired the single context task, although performance remained significantly above chance levels. In contrast, performance dropped all the way to chance when temporary lesions were used in the dual context task. These results demonstrate that rats can learn a dual context version of the odor sequence learning task that requires the use of contextual information along with the requirement to remember the "what" and "when" components of the odor sequence. Moreover, the addition of the contextual component made the task fully dependent on the hippocampus.

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

Production of foot-and-mouth disease virus capsid proteins by the TEV protease.

PubMed

Puckette, Michael; Smith, Justin D; Gabbert, Lindsay; Schutta, Christopher; Barrera, José; Clark, Benjamin A; Neilan, John G; Rasmussen, Max

2018-06-10

Protective immunity to viral pathogens often includes production of neutralizing antibodies to virus capsid proteins. Many viruses produce capsid proteins by expressing a precursor polyprotein and related protease from a single open reading frame. The foot-and-mouth disease virus (FMDV) expresses a 3C protease (3Cpro) that cleaves a P1 polyprotein intermediate into individual capsid proteins, but the FMDV 3Cpro also degrades many host cell proteins and reduces the viability of host cells, including subunit vaccine production cells. To overcome the limitations of using the a wild-type 3Cpro in FMDV subunit vaccine expression systems, we altered the protease restriction sequences within a FMDV P1 polyprotein to enable production of FMDV capsid proteins by the Tobacco Etch Virus NIa protease (TEVpro). Separate TEVpro and modified FMDV P1 proteins were produced from a single open reading frame by an intervening FMDV 2A sequence. The modified FMDV P1 polyprotein was successfully processed by the TEVpro in both mammalian and bacterial cells. More broadly, this method of polyprotein production and processing may be adapted to other recombinant expression systems, especially plant-based expression. Published by Elsevier B.V.

Methods of introducing nucleic acids into cellular DNA

DOEpatents

Lajoie, Marc J.; Gregg, Christopher J.; Mosberg, Joshua A.; Church, George M.

2017-06-27

A method of introducing a nucleic acid sequence into a cell is provided where the cell has impaired or inhibited or disrupted DnaG primase activity or impaired or inhibited or disrupted DnaB helicase activity, or larger or increased gaps or distance between Okazaki fragments or lowered or reduced frequency of Okazaki fragment initiation, or the cell has increased single stranded DNA (ssDNA) on the lagging strand of the replication fork including transforming the cell through recombination with a nucleic acid oligomer.

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.

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

In Vivo Control of CpG and Non-CpG DNA Methylation by DNA Methyltransferases

PubMed Central

Arand, Julia; Spieler, David; Karius, Tommy; Branco, Miguel R.; Meilinger, Daniela; Meissner, Alexander; Jenuwein, Thomas; Xu, Guoliang; Leonhardt, Heinrich; Wolf, Verena; Walter, Jörn

2012-01-01

The enzymatic control of the setting and maintenance of symmetric and non-symmetric DNA methylation patterns in a particular genome context is not well understood. Here, we describe a comprehensive analysis of DNA methylation patterns generated by high resolution sequencing of hairpin-bisulfite amplicons of selected single copy genes and repetitive elements (LINE1, B1, IAP-LTR-retrotransposons, and major satellites). The analysis unambiguously identifies a substantial amount of regional incomplete methylation maintenance, i.e. hemimethylated CpG positions, with variant degrees among cell types. Moreover, non-CpG cytosine methylation is confined to ESCs and exclusively catalysed by Dnmt3a and Dnmt3b. This sequence position–, cell type–, and region-dependent non-CpG methylation is strongly linked to neighboring CpG methylation and requires the presence of Dnmt3L. The generation of a comprehensive data set of 146,000 CpG dyads was used to apply and develop parameter estimated hidden Markov models (HMM) to calculate the relative contribution of DNA methyltransferases (Dnmts) for de novo and maintenance DNA methylation. The comparative modelling included wild-type ESCs and mutant ESCs deficient for Dnmt1, Dnmt3a, Dnmt3b, or Dnmt3a/3b, respectively. The HMM analysis identifies a considerable de novo methylation activity for Dnmt1 at certain repetitive elements and single copy sequences. Dnmt3a and Dnmt3b contribute de novo function. However, both enzymes are also essential to maintain symmetrical CpG methylation at distinct repetitive and single copy sequences in ESCs. PMID:22761581

Comparison of repair of DNA double-strand breaks in identical sequences in primary human fibroblast and immortal hamster-human hybrid cells harboring a single copy of human chromosome 11

NASA Technical Reports Server (NTRS)

Fouladi, B.; Waldren, C. A.; Rydberg, B.; Cooper, P. K.; Chatterjee, A. (Principal Investigator)

2000-01-01

We have optimized a pulsed-field gel electrophoresis assay that measures induction and repair of double-strand breaks (DSBs) in specific regions of the genome (Lobrich et al., Proc. Natl. Acad. Sci. USA 92, 12050-12054, 1995). The increased sensitivity resulting from these improvements makes it possible to analyze the size distribution of broken DNA molecules immediately after the introduction of DSBs and after repair incubation. This analysis shows that the distribution of broken DNA pieces after exposure to sparsely ionizing radiation is consistent with the distribution expected from randomly induced DSBs. It is apparent from the distribution of rejoined DNA pieces after repair incubation that DNA ends continue to rejoin between 3 and 24 h postirradiation and that some of these rejoining events are in fact misrejoining events, since novel restriction fragments both larger and smaller than the original fragment are generated after repair. This improved assay was also used to study the kinetics of DSB rejoining and the extent of misrejoining in identical DNA sequences in human GM38 cells and human-hamster hybrid A(L) cells containing a single human chromosome 11. Despite the numerous differences between these cells, which include species and tissue of origin, levels of TP53, expression of telomerase, and the presence or absence of a homologous chromosome for the restriction fragments examined, the kinetics of rejoining of radiation-induced DSBs and the extent of misrejoining were similar in the two cell lines when studied in the G(1) phase of the cell cycle. Furthermore, DSBs were removed from the single-copy human chromosome in the hamster A(L) cells with similar kinetics and misrejoining frequency as at a locus on this hybrid's CHO chromosomes.

Visible light-sensitive APTES-bound ZnO nanowire toward a potent nanoinjector sensing biomolecules in a living cell

NASA Astrophysics Data System (ADS)

Lee, Jooran; Choi, Sunyoung; Bae, Seon Joo; Yoon, Seok Min; Choi, Joon Sig; Yoon, Minjoong

2013-10-01

Nanoscale cell injection techniques combined with nanoscopic photoluminescence (PL) spectroscopy have been important issues in high-resolution optical biosensing, gene and drug delivery and single-cell endoscopy for medical diagnostics and therapeutics. However, the current nanoinjectors remain limited for optical biosensing and communication at the subwavelength level, requiring an optical probe such as semiconductor quantum dots, separately. Here, we show that waveguided red emission is observed at the tip of a single visible light-sensitive APTES-modified ZnO nanowire (APTES-ZnO NW) and it exhibits great enhancement upon interaction with a complementary sequence-based double stranded (ds) DNA, whereas it is not significantly affected by non-complementary ds DNA. Further, the tip of a single APTES-ZnO NW can be inserted into the subcellular region of living HEK 293 cells without significant toxicity, and it can also detect the enhancement of the tip emission from subcellular regions with high spatial resolution. These results indicate that the single APTES-ZnO NW would be useful as a potent nanoinjector which can guide visible light into intracellular compartments of mammalian cells, and can also detect nanoscopic optical signal changes induced by interaction with the subcellular specific target biomolecules without separate optical probes.Nanoscale cell injection techniques combined with nanoscopic photoluminescence (PL) spectroscopy have been important issues in high-resolution optical biosensing, gene and drug delivery and single-cell endoscopy for medical diagnostics and therapeutics. However, the current nanoinjectors remain limited for optical biosensing and communication at the subwavelength level, requiring an optical probe such as semiconductor quantum dots, separately. Here, we show that waveguided red emission is observed at the tip of a single visible light-sensitive APTES-modified ZnO nanowire (APTES-ZnO NW) and it exhibits great enhancement upon interaction with a complementary sequence-based double stranded (ds) DNA, whereas it is not significantly affected by non-complementary ds DNA. Further, the tip of a single APTES-ZnO NW can be inserted into the subcellular region of living HEK 293 cells without significant toxicity, and it can also detect the enhancement of the tip emission from subcellular regions with high spatial resolution. These results indicate that the single APTES-ZnO NW would be useful as a potent nanoinjector which can guide visible light into intracellular compartments of mammalian cells, and can also detect nanoscopic optical signal changes induced by interaction with the subcellular specific target biomolecules without separate optical probes. Electronic supplementary information (ESI) available: Synthesis of APTES-modified ZnO nanowires, DNA functionalization and spectroscopic measurements with additional fluorescence image ad fluorescence decay times, cell culture, injection of a single nanowire into living cells, subcellular imaging and determination of cytotoxicity. See DOI: 10.1039/c3nr03042c

Viral coinfection is shaped by host ecology and virus-virus interactions across diverse microbial taxa and environments.

PubMed

Díaz-Muñoz, Samuel L

2017-01-01

Infection of more than one virus in a host, coinfection, is common across taxa and environments. Viral coinfection can enable genetic exchange, alter the dynamics of infections, and change the course of viral evolution. Yet, a systematic test of the factors explaining variation in viral coinfection across different taxa and environments awaits completion. Here I employ three microbial data sets of virus-host interactions covering cross-infectivity, culture coinfection, and single-cell coinfection (total: 6,564 microbial hosts, 13,103 viruses) to provide a broad, comprehensive picture of the ecological and biological factors shaping viral coinfection. I found evidence that ecology and virus-virus interactions are recurrent factors shaping coinfection patterns. Host ecology was a consistent and strong predictor of coinfection across all three data sets: cross-infectivity, culture coinfection, and single-cell coinfection. Host phylogeny or taxonomy was a less consistent predictor, being weak or absent in the cross-infectivity and single-cell coinfection models, yet it was the strongest predictor in the culture coinfection model. Virus-virus interactions strongly affected coinfection. In the largest test of superinfection exclusion to date, prophage sequences reduced culture coinfection by other prophages, with a weaker effect on extrachromosomal virus coinfection. At the single-cell level, prophage sequences eliminated coinfection. Virus-virus interactions also increased culture coinfection with ssDNA-dsDNA coinfections >2× more likely than ssDNA-only coinfections. The presence of CRISPR spacers was associated with a ∼50% reduction in single-cell coinfection in a marine bacteria, despite the absence of exact spacer matches in any active infection. Collectively, these results suggest the environment bacteria inhabit and the interactions among surrounding viruses are two factors consistently shaping viral coinfection patterns. These findings highlight the role of virus-virus interactions in coinfection with implications for phage therapy, microbiome dynamics, and viral infection treatments.

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 Resolution of Temporal Gene Expression during Heart Development.

PubMed

DeLaughter, Daniel M; Bick, Alexander G; Wakimoto, Hiroko; McKean, David; Gorham, Joshua M; Kathiriya, Irfan S; Hinson, John T; Homsy, Jason; Gray, Jesse; Pu, William; Bruneau, Benoit G; Seidman, J G; Seidman, Christine E

2016-11-21

Activation of complex molecular programs in specific cell lineages governs mammalian heart development, from a primordial linear tube to a four-chamber organ. To characterize lineage-specific, spatiotemporal developmental programs, we performed single-cell RNA sequencing of >1,200 murine cells isolated at seven time points spanning embryonic day 9.5 (primordial heart tube) to postnatal day 21 (mature heart). Using unbiased transcriptional data, we classified cardiomyocytes, endothelial cells, and fibroblast-enriched cells, thus identifying markers for temporal and chamber-specific developmental programs. By harnessing these datasets, we defined developmental ages of human and mouse pluripotent stem-cell-derived cardiomyocytes and characterized lineage-specific maturation defects in hearts of mice with heterozygous mutations in Nkx2.5 that cause human heart malformations. This spatiotemporal transcriptome analysis of heart development reveals lineage-specific gene programs underlying normal cardiac development and congenital heart disease. Copyright © 2016 Elsevier Inc. All rights reserved.

Measles virus–specific plasma cells are prominent in subacute sclerosing panencephalitis CSF

PubMed Central

Owens, G.P.; Ritchie, A.M.; Gilden, D.H.; Burgoon, M.P.; Becker, D.; Bennett, J.L.

2012-01-01

Objective To demonstrate the specificity of expanded CD138+ plasma cell clones recovered from the CSF of a patient with subacute sclerosing panencephalitis (SSPE) for measles virus (MV). Methods IgG variable region sequences of single-antibody-secreting CD138+ cells sorted from SSPE CSF were amplified by single-cell PCR and analyzed. Human IgG1 recombinant antibodies (rAbs) were produced from four expanded CD138+ clones and assayed for immunoreactivity against MV proteins. Results Clonal expansion was a prominent feature of the SSPE plasma cell repertoire, and each of the four rAbs assayed was specific for either the MV fusion or the MV nucleocapsid protein. Conclusions Expanded plasma cell clones in the CSF of patients with subacute sclerosing panencephalitis produce disease-relevant antibodies. Recombinant antibodies derived from CSF B cells could provide a tool to identify target antigens in idiopathic inflammatory disorders. PMID:17515543

Proteome reference maps of Medicago truncatula embryogenic cell cultures generated from single protoplasts.

PubMed

Imin, Nijat; De Jong, Femke; Mathesius, Ulrike; van Noorden, Giel; Saeed, Nasir A; Wang, Xin-Ding; Rose, Ray J; Rolfe, Barry G

2004-07-01

Using a combination of two-dimensional gel electrophoresis (2-DE) protein mapping and mass spectrometry (MS) analysis, we have established proteome reference maps of Medicago truncatula embryogenic tissue culture cells. The cultures were generated from single protoplasts, which provided a relatively homogeneous cell population. We used these to analyze protein expression at the globular stages of somatic embryogenesis, which is the earliest morphogenetic embryonic stage. Over 3000 proteins could reproducibly be resolved over a pI range of 4-11. Three hundred and twelve protein spots were extracted from colloidal Coomassie Blue-stained 2-DE gels and analyzed by matrix-assisted laser desorption/ionization-time of flight MS analysis and tandem MS sequencing. This enabled the identification of 169 protein spots representing 128 unique gene products using a publicly available expressed sequence tag database and the MASCOT search engine. These reference maps will be valuable for the investigation of the molecular events which occur during somatic embryogenesis in M. truncatula. The proteome reference maps and supplementary materials will be available and updated for public access at http://semele.anu.edu.au/.

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.

A cDNA from a mouse pancreatic beta cell encoding a putative transcription factor of the insulin gene.

PubMed Central

Walker, M D; Park, C W; Rosen, A; Aronheim, A

1990-01-01

Cell specific expression of the insulin gene is achieved through transcriptional mechanisms operating on multiple DNA sequence elements located in the 5' flanking region of the gene. Of particular importance in the rat insulin I gene are two closely similar 9 bp sequences (IEB1 and IEB2): mutation of either of these leads to 5-10 fold reduction in transcriptional activity. We have screened an expression cDNA library derived from mouse pancreatic endocrine beta cells with a radioactive DNA probe containing multiple copies of the IEB1 sequence. A cDNA clone (A1) isolated by this procedure encodes a protein which shows efficient binding to the IEB1 probe, but much weaker binding to either an unrelated DNA probe or to a probe bearing a single base pair insertion within the recognition sequence. DNA sequence analysis indicates a protein belonging to the helix-loop-helix family of DNA-binding proteins. The ability of the protein encoded by clone A1 to recognize a number of wild type and mutant DNA sequences correlates closely with the ability of each sequence element to support transcription in vivo in the context of the insulin 5' flanking DNA. We conclude that the isolated cDNA may encode a transcription factor that participates in control of insulin gene expression. Images PMID:2181401

Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications.

PubMed

Van den Berge, Koen; Perraudeau, Fanny; Soneson, Charlotte; Love, Michael I; Risso, Davide; Vert, Jean-Philippe; Robinson, Mark D; Dudoit, Sandrine; Clement, Lieven

2018-02-26

Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce a weighting strategy, based on a zero-inflated negative binomial model, that identifies excess zero counts and generates gene- and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq.

Sequencing of Single Pollen Nuclei Reveals Meiotic Recombination Events at Megabase Resolution and Circumvents Segregation Distortion Caused by Postmeiotic Processes

PubMed Central

Dreissig, Steven; Fuchs, Jörg; Himmelbach, Axel; Mascher, Martin; Houben, Andreas

2017-01-01

Meiotic recombination is a fundamental mechanism to generate novel allelic combinations which can be harnessed by breeders to achieve crop improvement. The recombination landscape of many crop species, including the major crop barley, is characterized by a dearth of recombination in 65% of the genome. In addition, segregation distortion caused by selection on genetically linked loci is a frequent and undesirable phenomenon in double haploid populations which hampers genetic mapping and breeding. Here, we present an approach to directly investigate recombination at the DNA sequence level by combining flow-sorting of haploid pollen nuclei of barley with single-cell genome sequencing. We confirm the skewed distribution of recombination events toward distal chromosomal regions at megabase resolution and show that segregation distortion is almost absent if directly measured in pollen. Furthermore, we show a bimodal distribution of inter-crossover distances, which supports the existence of two classes of crossovers which are sensitive or less sensitive to physical interference. We conclude that single pollen nuclei sequencing is an approach capable of revealing recombination patterns in the absence of segregation distortion. PMID:29018459

Complete sequence of the first chimera genome constructed by cloning the whole genome of Synechocystis strain PCC6803 into the Bacillus subtilis 168 genome.

PubMed

Watanabe, Satoru; Shiwa, Yuh; Itaya, Mitsuhiro; Yoshikawa, Hirofumi

2012-12-01

Genome synthesis of existing or designed genomes is made feasible by the first successful cloning of a cyanobacterium, Synechocystis PCC6803, in Gram-positive, endospore-forming Bacillus subtilis. Whole-genome sequence analysis of the isolate and parental B. subtilis strains provides clues for identifying single nucleotide polymorphisms (SNPs) in the 2 complete bacterial genomes in one cell.