New papers with focus on single-cell gene expression noise:

Method of the year - Methods to watch - Special feature
Single-cell methods - Improved single-cell methods are helping to unravel biological complexity
We present important methods and areas of methodological development worth watching in the coming years.
Nature Methods - VOL.9 NO.1 - JANUARY 2012 - 35

The heterogeneity of cells in culture and in organisms poses a challenge for many experi-mental measurements. Population measure-ments are necessarily averages, masking the behavior of minority subpopulations and effectively blinding researchers to possibly interesting differences between cells.The alternative is to make measure-ments on single cells. Methodologically speaking, this, too, is challenging on sever-al fronts. Molecular analyses, whether on a particular macromolecule or at an ‘omic’ scale, can be difficult (or even impossible) to accomplish on the amount of mate-rial extracted from one cell. Methods with increased sensitivity are therefore in demand. Throughput is also a bottle-neck. Basing firm conclusions on single-cell measurements means that one must be able to quickly and accurately analyze many cells. Finally, it is often necessary to analyze single cells in a mul-tiplexed fash-ion, either because the cells exist in a heteroge-neous pop-ulation or because one wants to measure many parameters at the same time.There continue to be methodologi-cal advances on all of these fronts. Mass cytometry, for instance - in which iso-topes are used as antibody labels instead of fluorescent probes—considerably extends the multiplexing capabilities of flow cytometry (Science 332, 687–695; 2011).   Is the measurement of gene expression,  digital reverse-transcriptase PCR in a microfluidics device makes it possible to simultaneously monitor the expres-sion of hundreds of genes in hundreds of single cells. As demonstrated in a recent study of tumor heterogeneity, this can be combined with single cell sorting and with statistical clustering methods to begin to dissect the cellular subpopulations that constitute a tissue (Nat. Biotechnol. 29, 1120–1127; 2011).

SPECIAL ISSUE -- Single-Cell Biology -- L. Bryan Ray
Cells Go Solo -- Science 6 Dec 2013 Vol. 342 no. 6163 p. 1187

INTRODUCTION - The scientific literature contains an enormous body of work in which large numbers of cells have been broken open and homogenized to prepare samples for biochemical characterization and, certainly, much has been learned from such studies. But more recently, it has become possible to monitor events in single cells, thus allowing investigators to test whether existing “averaged” readings of the state of many cells from traditional large-scale assays accurately represent the behavior of the individual cells being studied. Such single-cell measurements are providing a wealth of information—sometimes unanticipated and often previously obscured—about how cells respond to perturbations or signals. In this special issue, three Reviews provide examples of fundamental insights into cellular regulation that are revealed when it is possible to measure enzymatic activity, transcriptional responses, or the metabolic state in individual cells.

An obvious advantage of single-cell measurements is the ability to measure variations or “noise” in the responses of the individual cells to similar or identical conditions. In many instances, it is possible to monitor the time course of cellular responses. Gene transcription can be particularly noisy, with bursts of RNA synthesis occurring in some cells but not others of the same population. Thus, fundamental questions arise about the nature of these systems. Perhaps variation in response is advantageous in conserving resources or in assuring that some cells survive in a changing environment. Or it may be that biophysical constraints of small numbers of molecules and the characteristics of the enzymes at work dictate such variability as unavoidable. Sanchez and Golding review recent work in model systems, from bacteria to animal cells, that attempts to resolve whether the kinetics of transcription are encoded in the architecture of promoter sequences in DNA—and might therefore vary throughout the genome—or are determined by physical or biophysical properties that would impose more global constraints throughout the cell.

Levine et al. explore another previously hidden phenomenon. Continuous measurements of protein activation show that many undergo asynchronous pulsatile responses, which are obscured in average measurements from a population of cells. They discuss how cellular circuits are wired to produce such responses and what the advantages of such control systems might be.

Zenobi highlights methodological advances, particularly in mass spectrometry, that are enabling quantitation of the abundance of molecular components of single cells. Challenges abound for the goal of making simultaneous measurements to characterize the rapid ly changing metabolic state of individual cells. But the promise of new insights across a broad range of disciplines is sustaining a steady effort to tap into the large store of new knowledge lying hidden within the confines of single cells.

Microfluidics and Single Cells
03/25/2014 Sarah C.P. Williams
Growing evidence suggests that biochemical assays don’t capture the complexity of cell cultures. Now, researchers are turning to microfluidics to assay one cell at a time. Learn more...

Microfluidic probe for single-cell analysis in adherent tissue culture

Sarkar A, Kolitz S, Lauffenburger DA, Han J
Nat Commun. 2014 (5): 3421

Single-cell analysis provides information critical to understanding key disease processes that are characterized by significant cellular heterogeneity. Few current methods allow single-cell measurement without removing cells from the context of interest, which not only destroys contextual information but also may perturb the process under study. Here we present a microfluidic probe that lyses single adherent cells from standard tissue culture and captures the contents to perform single-cell biochemical assays. We use this probe to measure kinase and housekeeping protein activities, separately or simultaneously, from single human hepatocellular carcinoma cells in adherent culture. This tool has the valuable ability to perform measurements that clarify connections between extracellular context, signals and responses, especially in cases where only a few cells exhibit a characteristic of interest.

Simultaneous quantification of alternatively spliced transcripts in a single droplet digital PCR reaction
Bing Sun, Lian Tao, and Yun-Ling Zheng
BioTechniques, Vol. 56, No. 6, June 2014, pp. 319–325

Humans synthesize ~150,000 different proteins from 25,000–30,000 genes by alternative splicing. It is estimated that more than 70% of human protein-coding genes produce multiple alternatively spliced mRNA transcripts (1). When these mRNAs are translated, they produce an array of proteins with diverse and even antagonistic functions. A large proportion of human genetic disorders are the result of abnormal splicing, with abnormal splicing variants thought to even contribute to the development of cancer (2, 3). Given the importance of alternative splicing in regulating cellular function, accurate quantification of multiple alternatively spliced transcripts could facilitate the discovery of new biomarkers for clinical applications and thus enhance our understanding of the role of alternative splicing in health and disease.

Validation of high-throughput single cell analysis methodology
Devonshire AS1, Baradez MO2, Morley G2, Marshall D2, Foy CA2.
Anal Biochem. 2014 (1) 452: 103-113

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

Block-Cell-Printing for live single-cell printing
Zhang K1, Chou CK, Xia X, Hung MC, Qin L.
Proc Natl Acad Sci U S A. 2014 111(8): 2948-2953

A unique live-cell printing technique, termed "Block-Cell-Printing" (BloC-Printing), allows for convenient, precise, multiplexed, and high-throughput printing of functional single-cell arrays. Adapted from woodblock printing techniques, the approach employs microfluidic arrays of hook-shaped traps to hold cells at designated positions and directly transfer the anchored cells onto various substrates. BloC-Printing has a minimum turnaround time of 0.5 h, a maximum resolution of 5 µm, close to 100% cell viability, the ability to handle multiple cell types, and efficiently construct protrusion-connected single-cell arrays. The approach enables the large-scale formation of heterotypic cell pairs with controlled morphology and allows for material transport through gap junction intercellular communication. When six types of breast cancer cells are allowed to extend membrane protrusions in the BloC-Printing device for 3 h, multiple biophysical characteristics of cells--including the protrusion percentage, extension rate, and cell length--are easily quantified and found to correlate well with their migration levels. In light of this discovery, BloC-Printing may serve as a rapid and high-throughput cell protrusion characterization tool to measure the invasion and migration capability of cancer cells. Furthermore, primary neurons are also compatible with BloC-Printing.

Quantitative assessment of single-cell RNA-sequencing methods
Wu AR, Neff NF, Kalisky T, Dalerba P, Treutlein B, Rothenberg ME, Mburu FM, Mantalas GL, Sim S, Clarke MF, Quake SR
Nat Methods. 2014 Jan;11(1):41-46

Interest in single-cell whole-transcriptome analysis is growing rapidly, especially for profiling rare or heterogeneous populations of cells. We compared commercially available single-cell RNA amplification methods with both microliter and nanoliter volumes, using sequence from bulk total RNA and multiplexed quantitative PCR as benchmarks to systematically evaluate the sensitivity and accuracy of various single-cell RNA-seq approaches. We show that single-cell RNA-seq can be used to perform accurate quantitative transcriptome measurement in individual cells with a relatively small number of sequencing reads and that sequencing large numbers of single cells can recapitulate bulk transcriptome complexity.

The workflow of single-cell expression profiling using quantitative real-time PCR
Ståhlberg A1, Kubista M.
Expert Rev Mol Diagn. 2014 (3):3323-331

Biological material is heterogeneous and when exposed to stimuli the various cells present respond differently. Much of the complexity can be eliminated by disintegrating the sample, studying the cells one by one. Single-cell profiling reveals responses that go unnoticed when classical samples are studied. New cell types and cell subtypes may be found and relevant pathways and expression networks can be identified. The most powerful technique for single-cell expression profiling is currently quantitative reverse transcription real-time PCR (RT-qPCR). A robust RT-qPCR workflow for highly sensitive and specific measurements in high-throughput and a reasonable degree of multiplexing has been developed for targeting mRNAs, but also microRNAs, non-coding RNAs and most recently also proteins. We review the current state of the art of single-cell expression profiling and present also the improvements and developments expected in the next 5 years.

Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro E, Biezuner T, Linnarsson S.
Nat Rev Genet. 2013 (9): 618-630

The unabated progress in next-generation sequencing technologies is fostering a wave of new genomics, epigenomics, transcriptomics and proteomics technologies. These sequencing-based technologies are increasingly being targeted to individual cells, which will allow many new and longstanding questions to be addressed. For example, single-cell genomics will help to uncover cell lineage relationships; single-cell transcriptomics will supplant the coarse notion of marker-based cell types; and single-cell epigenomics and proteomics will allow the functional states of individual cells to be analysed. These technologies will become integrated within a decade or so, enabling high-throughput, multi-dimensional analyses of individual cells that will produce detailed knowledge of the cell lineage trees of higher organisms, including humans. Such studies will have important implications for both basic biological research and medicine.

Genetic determinants and cellular constraints in noisy gene expression
Sanchez A, Golding I
Science. 2013 342(6163): 1188-1193

In individual cells, transcription is a random process obeying single-molecule kinetics. Often, it occurs in a bursty, intermittent manner. The frequency and size of these bursts affect the magnitude of temporal fluctuations in messenger RNA and protein content within a cell, creating variation or "noise" in gene expression. It is still unclear to what degree transcriptional kinetics are specific to each gene and determined by its promoter sequence. Alternative scenarios have been proposed, in which the kinetics of transcription are governed by cellular constraints and follow universal rules across the genome. Evidence from genome-wide noise studies and from systematic perturbations of promoter sequences suggest that both scenarios-namely gene-specific versus genome-wide regulation of transcription kinetics-may be present to different degrees in bacteria, yeast, and animal cells.

Transcriptional profiling of cells sorted by RNA abundance
Klemm S, Semrau S, Wiebrands K, Mooijman D, Faddah DA, Jaenisch R, van Oudenaarden A
Nat Methods. 2014 May;11(5): 549-551

We have developed a quantitative technique for sorting cells on the basis of endogenous RNA abundance, with a molecular resolution of 10-20 transcripts. We demonstrate efficient and unbiased RNA extraction from transcriptionally sorted cells and report a high-fidelity transcriptome measurement of mouse induced pluripotent stem cells (iPSCs) isolated from a heterogeneous reprogramming culture. This method is broadly applicable to profiling transcriptionally distinct cellular states without requiring antibodies or transgenic fluorescent proteins.

Validation of noise models for single-cell transcriptomics
Grün D, Kester L, van Oudenaarden A
Nat Methods. 2014 (6): 637-640

Single-cell transcriptomics has recently emerged as a powerful technology to explore gene expression heterogeneity among single cells. Here we identify two major sources of technical variability: sampling noise and global cell-to-cell variation in sequencing efficiency. We propose noise models to correct for this, which we validate using single-molecule FISH. We demonstrate that gene expression variability in mouse embryonic stem cells depends on the culture condition.

Image-based transcriptomics in thousands of single human cells at single-molecule resolution
Battich N, Stoeger T, Pelkmans L.
Nat Methods. 2013 (11): 11127-11133

Fluorescence in situ hybridization (FISH) is widely used to obtain information about transcript copy number and subcellular localization in single cells. However, current approaches do not readily scale to the analysis of whole transcriptomes. Here we show that branched DNA technology combined with automated liquid handling, high-content imaging and quantitative image analysis allows highly reproducible quantification of transcript abundance in thousands of single cells at single-molecule resolution. In addition, it allows extraction of a multivariate feature set quantifying subcellular patterning and spatial properties of transcripts and their cell-to-cell variability. This has multiple implications for the functional interpretation of cell-to-cell variability in gene expression and enables the unbiased identification of functionally relevant in situ signatures of the transcriptome without the need for perturbations. Because this method can be incorporated in a wide variety of high-throughput image-based approaches, we expect it to be broadly applicable.

Cell Biology. Using cell-to-cell variability - a new era in molecular biology
Pelkmans L.
Institute of Molecular Life Sciences, University of Zurich, Zürich, Switzerland
Science. 2012 Apr 27;336(6080): 425-426

Genomic analysis at the single-cell level
Kalisky T, Blainey P, Quake SR.
Department of Bioengineering, Stanford University and Howard Hughes Medical Institute, Stanford, California 94305, USA
Annu Rev Genet. 2011;45: 431-445

Studying complex biological systems such as a developing embryo, a tumor, or a microbial ecosystem often involves understanding the behavior and heterogeneity of the individual cells that constitute the system and their interactions. In this review, we discuss a variety of approaches to single-cell genomic analysis.

A single molecule view of gene expression
Larson DR, Singer RH, Zenklusen D.
Department of Anatomy and Structural Biology and The Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, New York 10461, USA.
Trends Cell Biol. 2009 Nov;19(11):630-637

Analyzing the expression of single genes in single cells appears minimalistic in comparison to gene expression studies based on more global approaches. However, stimulated by advances in imaging technologies, single-cell studies have become an essential tool in understanding the rules that govern gene expression. This quantitative view of single-cell gene expression is based on counting mRNAs in single cells, monitoring transcription in real time, and visualizing single proteins. Parallel advances in mathematical models based on stochastic, discrete descriptions of biochemical processes have provided crucial insights into the underlying cellular mechanisms that control expression. The view that has emerged is rooted in a probabilistic understanding of cellular processes that quantitatively explains both the mean and the variation observed in gene-expression patterns among single cells. Thus, the close coupling between imaging and mathematical theory has established single-cell analysis as an essential branch of systems biology.

Single-cell gene-expression profiling and its potential diagnostic applications
Ståhlberg A, Kubista M, Aman P.
Sahlgrenska Cancer Center, Department of Pathology, Sahlgrenska Academy at University of Gothenburg, Box 425, 40530 Gothenburg, Sweden
Expert Rev Mol Diagn. 2011 (7): 735-740

Gene-expression profiling has been successfully applied in various diagnostic applications, but its full capacity is yet to be realized. Samples are generally prepared from a mixture of different cells that are present in unknown proportions. Cells are, in many aspects, unique in their characteristics and this heterogeneity confounds the expression profile. The development of new and robust techniques to measure gene expression in single cells opens new avenues in molecular medicine. Today, gene-expression profiles of individual cells can be measured with high precision and accuracy, identifying different cell types as well as revealing heterogeneity among cells of the same kind. Here, we review practical aspects of single-cell gene-expression profiling using reverse transcription quantitative real-time PCR and its potential use in diagnostics.

Multimarker gene analysis of circulating tumor cells in pancreatic cancer patients: a feasibility study
de Albuquerque A, Kubisch I, Breier G, Stamminger G, Fersis N, Eichler A, Kaul S, Stölzel U.
Department of Pathology, Technische Universität Dresden, Dresden, Germany
Oncology. 2012;82(1): 3-10

OBJECTIVE: The aim of this study was to develop an immunomagnetic/real-time reverse transcriptase polymerase chain reaction (RT-PCR) assay and assess its clinical value for the molecular detection of circulating tumor cells (CTCs) in peripheral blood of pancreatic cancer patients.
METHODS: The presence of CTCs was evaluated in 34 pancreatic cancer patients before systemic therapy and in 40 healthy controls, through immunomagnetic enrichment, using the antibodies BM7 and VU1D9 [targeting mucin 1 and epithelial cell adhesion molecule (EpCAM), respectively], followed by real-time RT-PCR analysis of the genes KRT19, MUC1, EPCAM, CEACAM5 and BIRC5.
RESULTS: The developed assay showed high specificity, as none of the healthy controls were found to be positive for the multimarker gene panel. CTCs were detected in 47.1% of the pancreatic cancer patients before the beginning of systemic treatment. Shorter median progression-free survival (PFS) was observed for patients who had at least one detectable tumor-associated transcript, compared with patients who were CTC negative. Median PFS time was 66.0 days [95% confidence interval (CI) 44.8-87.2] for patients with baseline CTC positivity and 138.0 days (95% CI 124.1-151.9) for CTC-negative patients (p = 0.01, log-rank test).
CONCLUSION: Our results suggest that in addition to the current prognostic methods, CTC analysis represents a potential complementary tool for prediction of outcome in pancreatic cancer patients.

Mammalian genes are transcribed with widely different bursting kinetics
Suter DM, Molina N, Gatfield D, Schneider K, Schibler U, Naef F.
Department of Molecular Biology, Sciences III, University of Geneva, 30 Quai Ernest Ansermet, 1211 Geneva, Switzerland.
Science. 2011 332(6028): 472-474

In prokaryotes and eukaryotes, most genes appear to be transcribed during short periods called transcriptional bursts, interspersed by silent intervals. We describe how such bursts generate gene-specific temporal patterns of messenger RNA (mRNA) synthesis in mammalian cells. To monitor transcription at high temporal resolution, we established various gene trap cell lines and transgenic cell lines expressing a short-lived luciferase protein from an unstable mRNA, and recorded bioluminescence in real time in single cells. Mathematical modeling identified gene-specific on- and off-switching rates in transcriptional activity and mean numbers of mRNAs produced during the bursts. Transcriptional kinetics were markedly altered by cis-regulatory DNA elements. Our analysis demonstrated that bursting kinetics are highly gene-specific, reflecting refractory periods during which genes stay inactive for a certain time before switching on again.

Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy
Young JW, Locke JC, Altinok A, Rosenfeld N, Bacarian T, Swain PS, Mjolsness E, Elowitz MB.
Division of Biology, California Institute of Technology, Pasadena, USA.
Nat Protoc. 2011 7(1): 80-88

Quantitative single-cell time-lapse microscopy is a powerful method for analyzing gene circuit dynamics and heterogeneous cell behavior. We describe the application of this method to imaging bacteria by using an automated microscopy system. This protocol has been used to analyze sporulation and competence differentiation in Bacillus subtilis, and to quantify gene regulation and its fluctuations in individual Escherichia coli cells. The protocol involves seeding and growing bacteria on small agarose pads and imaging the resulting microcolonies. Images are then reviewed and analyzed using our laboratory's custom MATLAB analysis code, which segments and tracks cells in a frame-to-frame method. This process yields quantitative expression data on cell lineages, which can illustrate dynamic expression profiles and facilitate mathematical models of gene circuits. With fast-growing bacteria, such as E. coli or B. subtilis, image acquisition can be completed in 1 d, with an additional 1-2 d for progressing through the analysis procedure.

Quantification noise in single cell experiments
Reiter M, Kirchner B, Müller H, Holzhauer C, Mann W, Pfaffl MW.
Nucleic Acids Res. 2011 Oct;39(18):e124
In quantitative single-cell studies, the critical part is the low amount of nucleic acids present and the resulting experimental variations. In addition biological data obtained from heterogeneous tissue are not reflecting the expression behaviour of every single-cell. These variations can be derived from natural biological variance or can be introduced externally. Both have negative effects on the quantification result. The aim of this study is to make quantitative single-cell studies more transparent and reliable in order to fulfil the MIQE guidelines at the single-cell level. The technical variability introduced by RT, pre-amplification, evaporation, biological material and qPCR itself was evaluated by using RNA or DNA standards. Secondly, the biological expression variances of GAPDH, TNFα, IL-1β, TLR4 were measured by mRNA profiling experiment in single lymphocytes. The used quantification setup was sensitive enough to detect single standard copies and transcripts out of one solitary cell. Most variability was introduced by RT, followed by evaporation, and pre-amplification. The qPCR analysis and the biological matrix introduced only minor variability. Both conducted studies impressively demonstrate the heterogeneity of expression patterns in individual cells and showed clearly today's limitation in quantitative single-cell expression analysis.

Identifying single-cell molecular programs by stochastic profiling
Janes KA, Wang CC, Holmberg KJ, Cabral K, Brugge JS.
Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, USA
Nat Methods. 2010 Apr;7(4): 311-317

Cells in tissues can be morphologically indistinguishable yet show molecular expression patterns that are remarkably heterogeneous. Here we describe an approach to comprehensively identify co-regulated, heterogeneously expressed genes among cells that otherwise appear identical. The technique, called stochastic profiling, involves repeated, random selection of very small cell populations via laser-capture microdissection followed by a customized single-cell amplification procedure and transcriptional profiling. Fluctuations in the resulting gene-expression measurements are then analyzed statistically to identify transcripts that are heterogeneously coexpressed. We stochastically profiled matrix-attached human epithelial cells in a three-dimensional culture model of mammary-acinar morphogenesis. Of 4,557 transcripts, we identified 547 genes with strong cell-to-cell expression differences. Clustering of this heterogeneous subset revealed several molecular 'programs' implicated in protein biosynthesis, oxidative-stress responses and NF-kappaB signaling, which we independently confirmed by RNA fluorescence in situ hybridization. Thus, stochastic profiling can reveal single-cell heterogeneities without the need to measure expression in individual cells.

High-throughput microfluidic single-cell RT-qPCR
White AK, VanInsberghe M, Petriv OI, Hamidi M, Sikorski D, Marra MA, Piret J, Aparicio S, Hansen CL.
Centre for High-Throughput Biology, University of British Columbia, Vancouver, BC, Canada V6T 1Z4.
Proc Natl Acad Sci U S A. 2011 Aug 23;108(34): 13999-134004

A long-sought milestone in microfluidics research has been the development of integrated technology for scalable analysis of transcription in single cells. Here we present a fully integrated microfluidic device capable of performing high-precision RT-qPCR measurements of gene expression from hundreds of single cells per run. Our device executes all steps of single-cell processing, including cell capture, cell lysis, reverse transcription, and quantitative PCR. In addition to higher throughput and reduced cost, we show that nanoliter volume processing reduced measurement noise, increased sensitivity, and provided single nucleotide specificity. We apply this technology to 3,300 single-cell measurements of (i) miRNA expression in K562 cells, (ii) coregulation of a miRNA and one of its target transcripts during differentiation in embryonic stem cells, and (iii) single nucleotide variant detection in primary lobular breast cancer cells. The core functionality established here provides the foundation from which a variety of on-chip single-cell transcription analyses will be developed.

RNA-Seq analysis to capture the transcriptome landscape of a single cell
Tang F, Barbacioru C, Nordman E, Li B, Xu N, Bashkirov VI, Lao K, Surani MA.
Wellcome Trust/Cancer Research UK Gurdon Institute of Cancer and Developmental Biology, University of Cambridge, Cambridge, UK.
Nat Protoc. 2010 Mar;5(3): 516-535

We describe here a protocol for digital transcriptome analysis in a single mouse oocyte and blastomere using a deep-sequencing approach. In this method, individual cells are isolated and transferred into lysate buffer by mouth pipette, followed by reverse transcription carried out directly on the whole cell lysate. Free primers are removed by exonuclease I and a poly(A) tail is added to the 3' end of the first-strand cDNAs by terminal deoxynucleotidyl transferase. Single-cell cDNAs are then amplified by 20 + 9 cycles of PCR. The resulting 100-200 ng of amplified cDNAs are used to construct a sequencing library, which can be used for deep sequencing using the SOLiD system. Compared with cDNA microarray techniques, our assay can capture up to 75% more genes expressed in early embryos. This protocol can generate deep-sequencing libraries for 16 single-cell samples within 6 d.

Development and applications of single-cell transcriptome analysis
Tang F, Lao K, Surani MA.
Wellcome Trust/Cancer Research UK Gurdon Institute of Cancer and Developmental Biology, University of Cambridge, Cambridge, UK.
Nat Methods. 2011 8(4 Suppl): S6-11

Dissecting the relationship between genotype and phenotype is one of the central goals in developmental biology and medicine. Transcriptome analysis is a powerful strategy to connect genotype to phenotype of a cell. Here we review the history, progress, potential applications and future developments of single-cell transcriptome analysis. In combination with live cell imaging and lineage tracing, it will be possible to decipher the full gene expression network underlying physiological functions of individual cells in embryos and adults, and to study diseases.

Quantitative RT-PCR gene expression analysis of laser microdissected tissue samples
Erickson HS, Albert PS, Gillespie JW, Rodriguez-Canales J, Marston Linehan W, Pinto PA, Chuaqui RF, Emmert-Buck MR.
Pathogenetics Unit, Laboratory of Pathology and Urologic Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Nat Protoc. 2009; 4(6): 902-922

Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is a valuable tool for measuring gene expression in biological samples. However, unique challenges are encountered when studies are performed on cells microdissected from tissues derived from animal models or the clinic, including specimen-related issues, variability of RNA template quality and quantity, and normalization. qRT-PCR using small amounts of mRNA derived from dissected cell populations requires adaptation of standard methods to allow meaningful comparisons across sample sets. The protocol described here presents the rationale, technical steps, normalization strategy and data analysis necessary to generate reliable gene expression measurements of transcripts from dissected samples. The entire protocol from tissue microdissection through qRT-PCR analysis requires approximately 16 h.

mRNA and microRNA expression profiles in circulating tumor cells and primary tumors of metastatic breast cancer patients
Sieuwerts AM, Mostert B, Bolt-de Vries J, Peeters D, de Jongh FE, Stouthard JM, Dirix LY, van Dam PA, Van Galen A, de Weerd V, Kraan J, van der Spoel P, Ramírez-Moreno R, van Deurzen CH, Smid M, Yu JX, Jiang J, Wang Y, Gratama JW, Sleijfer S, Foekens JA, Martens JW.
Department of Medical Oncology, Josephine Nefkens Institute and Cancer Genomics Centre, Rotterdam, The Netherlands.
Clin Cancer Res. 2011 Jun 1;17(11): 3600-3618

PURPOSE: Molecular characterization of circulating tumor cells (CTC) holds great promise. Unfortunately, routinely isolated CTC fractions currently still contain contaminating leukocytes, which makes CTC-specific molecular characterization extremely challenging. In this study, we determined mRNA and microRNA (miRNA) expression of potentially CTC-specific genes that are considered to be clinically relevant in breast cancer.
EXPERIMENTAL DESIGN: CTCs were isolated with the epithelial cell adhesion molecule-based CellSearch Profile Kit. Selected genes were measured by real-time reverse transcriptase PCR in CTCs of 50 metastatic breast cancer patients collected before starting first-line systemic therapy in blood from 53 healthy blood donors (HBD) and in primary tumors of 8 of the patients. The molecular profiles were associated with CTC counts and clinical parameters and compared with the profiles generated from the corresponding primary tumors.
RESULTS: We identified 55 mRNAs and 10 miRNAs more abundantly expressed in samples from 32 patients with at least 5 CTCs in 7.5 mL of blood compared with samples from 9 patients without detectable CTCs and HBDs. Clustering analysis resulted in 4 different patient clusters characterized by 5 distinct gene clusters. Twice the number of patients from cluster 2 to 4 had developed both visceral and nonvisceral metastases. Comparing transcript levels in CTCs with those measured in corresponding primary tumors showed clinically relevant discrepancies in estrogen receptor and HER2 levels.
CONCLUSIONS: Our study shows that molecular profiling of low numbers of CTCs in a high background of leukocytes is feasible and shows promise for further studies on the clinical relevance of molecular characterization of CTCs.

Comprehensive qPCR profiling of gene expression in single neuronal cells
Citri A, Pang ZP, Südhof TC, Wernig M, Malenka RC.
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, California, USA
Nat Protoc. 2011 Dec 22;7(1): 118-127

A major challenge in neuronal stem cell biology lies in characterization of lineage-specific reprogrammed human neuronal cells, a process that necessitates the use of an assay sensitive to the single-cell level. Single-cell gene profiling can provide definitive evidence regarding the conversion of one cell type into another at a high level of resolution. The protocol we describe uses Fluidigm Biomark dynamic arrays for high-throughput expression profiling from single neuronal cells, assaying up to 96 independent samples with up to 96 quantitative PCR (qPCR) probes (equivalent to 9,216 reactions) in a single experiment, which can be completed within 2-3 d. The protocol enables simple and cost-effective profiling of several hundred transcripts from a single cell, and it could have numerous utilities.

Single cell transcriptomics of neighboring hyphae of Aspergillus niger
de Bekker C, Bruning O, Jonker MJ, Breit TM, Wösten HA.
Microbiology and Kluyver Centre for Genomics of Industrial Fermentations, Institute of Biomembranes, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands.
Genome Biol. 2011 12(8): R71

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

RT-qPCR based quantitative analysis of gene expression in single bacterial cells
Gao W, Zhang W, Meldrum DR.
Center for Ecogenomics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287-6501, United States.
J Microbiol Methods. 2011 Jun;85(3): 221-227

Recent evidence suggests that cell-to-cell difference at the gene expression level is an order of magnitude greater than previously thought even for isogenic bacterial populations. Such gene expression heterogeneity determines the fate of individual bacterial cells in populations and could also affect the ultimate fate of populations themselves. To quantify the heterogeneity and its biological significance, quantitative methods to measure gene expression in single bacterial cells are needed. In this work, we developed two SYBR Green-based RT-qPCR methods to determine gene expression directly in single bacterial cells. The first method involves a single-tube operation that can analyze one gene from each bacterial cell. The second method is featured by a two-stage protocol that consists of RNA isolation from a single bacterial cell and cDNA synthesis in the first stage, and qPCR in the second stage, which allows determination of expression level of multiple genes simultaneously for single bacterial cells of both gram-positive and negative. We applied the methods to stress-treated (i.e. low pH and high temperature) Escherichia coli populations. The reproducible results demonstrated that the method is sensitive enough not only for measuring cellular responses at the single-cell level, but also for revealing gene expression heterogeneity among the bacterial cells. Furthermore, our results showed that the two-stage method can reproducibly measure multiple highly expressed genes from a single E. coli cell, which exhibits important foundation for future development of a high throughput and lab-on-chips whole-genome RT-qPCR methodology for single bacterial cells.

Circulating tumor cells in breast cancer: detection systems, molecular characterization, and future challenges
Lianidou ES, Markou A.
Laboratory of Analytical Chemistry, Department of Chemistry, University of Athens, Athens, Greece
Clin Chem. 2011 Sep;57(9): 1242-1255

BACKGROUND: Circulating tumor cell (CTC) analysis is a promising new diagnostic field for estimating the risk for metastatic relapse and metastatic progression in patients with cancer.
CONTENT: Different analytical systems for CTC isolation and detection have been developed as immunocytochemical and molecular assays, most including separation steps by size or biological characteristics, such as expression of epithelial- or cancer-specific markers. Recent technical advancements in CTC detection and characterization include methods based on multiplex reverse-transcription quantitative PCR and approaches based on imaging and microfilter and microchip devices. New areas of research are directed toward developing novel assays for CTC molecular characterization. QC is an important issue for CTC analysis, and standardization of micrometastatic cell detection and characterization methodologies is important for the incorporation of CTCs into prospective clinical trials to test their clinical utility. The molecular characterization of CTCs can provide important information on the molecular and biological nature of these cells, such as the status of hormone receptors and epidermal and other growth factor receptor family members, and indications of stem-cell characteristics. This information is important for the identification of therapeutic targets and resistance mechanisms in CTCs as well as for the stratification of patients and real-time monitoring of systemic therapies.
SUMMARY: CTC analysis can be used as a liquid biopsy approach for prognostic and predictive purposes in breast and other cancers. In this review we focus on state-of-the-art technology platforms for CTC isolation, imaging, and detection; QC of CTC analysis; and ongoing challenges for the molecular characterization of CTCs.

Molecular characterization of circulating tumor cells in breast cancer: challenges and promises for individualized cancer treatment
Lianidou ES, Markou A, Strati A.
Analysis of Circulating Tumor Cells Lab, Laboratory of Analytical Chemistry, Department of Chemistry, University of Athens, 15771, Athens, Greece
Cancer Metastasis Rev. 2012 Jun 13

Blood testing using Circulating Tumor Cells (CTCs) has emerged as one of the hottest fields in cancer diagnosis. Research on CTCs present nowadays a challenge, as these cells are well defined targets for understanding tumour biology and improving cancer treatment. The presence of tumor cells in patient's bone marrow or peripheral blood is an early indicator of metastasis and may signal tumor spread sooner than clinical symptoms appear and imaging results confirm a poor prognosis. CTC enumeration can serve as a "liquid biopsy" and an early marker to assess response to systemic therapy. Definition of biomarkers based on comprehensive characterization of CTCs has a strong potential to be translated to individualized targeted treatments and spare breast cancer patients unnecessary and ineffective therapies but also to reduce the costs for the health system and to downsize the extent and length of clinical studies. In this review, we briefly summarize recent studies on the molecular characterization of circulating tumor cells in breast cancer and discuss challenges and promises of CTCs for individualized cancer treatment.

Gene expression profile of circulating tumor cells in breast cancer by RT-qPCR
Strati A, Markou A, Parisi C, Politaki E, Mavroudis D, Georgoulias V, Lianidou E.
Department of Chemistry, University of Athens, University Campus, 15771 Athens, Greece.
BMC Cancer. 2011 11:422.

BACKGROUND: Circulating tumor cells (CTCs) have been associated with prognosis especially in breast cancer and have been proposed as a liquid biopsy for repeated follow up examinations. Molecular characterization of CTCs is difficult to address since they are very rare and the amount of available sample is very limited.
METHODS: We quantified by RT-qPCR CK-19, MAGE-A3, HER-2, TWIST1, hTERT α+β+, and mammaglobin gene transcripts in immunomagnetically positively selected CTCs from 92 breast cancer patients, and 28 healthy individuals. We also compared our results with the CellSearch system in 33 of these patients with early breast cancer.
RESULTS: RT-qPCR is highly sensitive and specific and can detect the expression of each individual gene at the one cell level. None of the genes tested was detected in the group of healthy donors. In 66 operable breast cancer patients, CK-19 was detected in 42.4%, HER-2 in 13.6%, MAGE-A3 in 21.2%, hMAM in 13.6%, TWIST-1 in 42.4%, and hTERT α+β+ in 10.2%. In 26 patients with verified metastasis, CK-19 was detected in 53.8%, HER-2 in 19.2%, MAGE-A3 in 15.4%, hMAM in 30.8%, TWIST-1 in 38.5% and hTERT α+β+in 19.2%. Our preliminary data on the comparison between RT-qPCR and CellSearch in 33 early breast cancer patients showed that RT-qPCR gives more positive results in respect to CellSearch.
CONCLUSIONS: Molecular characterization of CTCs has revealed a remarkable heterogeneity of gene expression between breast cancer patients. In a small percentage of patients, CTCs were positive for all six genes tested, while in some patients only one of these genes was expressed. The clinical significance of these findings in early breast cancer remains to be elucidated when the clinical outcome for these patients is known.

Single-cell gene-expression profiling reveals qualitatively distinct CD8 T cells elicited by different gene-based vaccines
Flatz L, Roychoudhuri R, Honda M, Filali-Mouhim A, Goulet JP, Kettaf N, Lin M, Roederer M, Haddad EK, Sékaly RP, Nabel GJ.
Vaccine Research Center, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892-3005, USA.
Proc Natl Acad Sci U S A. 2011 108(14): 5724-5729

CD8 T cells play a key role in mediating protective immunity against selected pathogens after vaccination. Understanding the mechanism of this protection is dependent upon definition of the heterogeneity and complexity of cellular immune responses generated by different vaccines. Here, we identify previously unrecognized subsets of CD8 T cells based upon analysis of gene-expression patterns within single cells and show that they are differentially induced by different vaccines. Three prime-boost vector combinations encoding HIV Env stimulated antigen-specific CD8 T-cell populations of similar magnitude, phenotype, and functionality. Remarkably, however, analysis of single-cell gene-expression profiles enabled discrimination of a majority of central memory (CM) and effector memory (EM) CD8 T cells elicited by the three vaccines. Subsets of T cells could be defined based on their expression of Eomes, Cxcr3, and Ccr7, or Klrk1, Klrg1, and Ccr5 in CM and EM cells, respectively. Of CM cells elicited by DNA prime-recombinant adenoviral (rAd) boost vectors, 67% were Eomes(-) Ccr7(+) Cxcr3(-), in contrast to only 7% and 2% stimulated by rAd5-rAd5 or rAd-LCMV, respectively. Of EM cells elicited by DNA-rAd, 74% were Klrk1(-) Klrg1(-)Ccr5(-) compared with only 26% and 20% for rAd5-rAd5 or rAd5-LCMV. Definition by single-cell gene profiling of specific CM and EM CD8 T-cell subsets that are differentially induced by different gene-based vaccines will facilitate the design and evaluation of vaccines, as well as enable our understanding of mechanisms of protective immunity.

High throughput single cell expression profiling: Taking a closerlook on biological response
Mikael Kubista, Linda Strömbom, David Svec,Vendula Rusnakova & Anders Ståhlberg
TATAA Biocenter, Gothenburg, Sweden and the Institute of Biotechnology, CAS
European Pharmaceutical ReviewVolume 16, Issue 2, 2011

Molecular analysis of tissue and in most cases also of bodily fluids is complicatedbecause of tissue heterogeneity and the presence of many different cell types.Even cells of apparently the same type show substantial variation in geneexpression under virtually identical conditions. When analysing classical samplesbased on tens of thousands of cells, this natural variability among cells is lost.With the advent of real-time quantitative polymerase chain reaction (qPCR), wehave a most powerful tool to study diversity on the single cell level and candetect rare cells that are critical to treatment or survival.

Quantification of circulating endothelial and progenitor cells: comparison of quantitative PCR and four-channel flow cytometry
Steurer M, Kern J, Zitt M, Amberger A, Bauer M, Gastl G, Untergasser G, Gunsilius E.
Tumor Biology and Angiogenesis Laboratory, Division of Hematology and Oncology, Innrain 66, Innsbruck Medical University, 6020 Innsbruck, Austria
BMC Res Notes. 2008 Aug 28;1:71.

BACKGROUND: Circulating endothelial cells (CEC) and endothelial precursor cells (CEP) have been suggested as markers for angiogenesis in cancer. However, CEC/CEP represent a tiny and heterogeneous cell population, rendering a standardized monitoring in peripheral blood difficult. Thus, we investigated whether a PCR-based detection method of CEC/CEP might overcome the limitations of rare-event flow cytometry.
FINDINGS: To test the sensitivity of both assays endothelial colony forming cell clones (ECFC) and cord blood derived CD45- CD34+ progenitor cells were spiked into peripheral blood mononuclear cells (PBMNC) of healthy volunteers. Samples were analyzed for the expression of CD45, CD31, CD34, KDR or CD133 by 4-color flow cytometry and for the expression of CD34, CD133, KDR and CD144 by qPCR. Applying flow cytometry, spiked ECFC and progenitor cells were detectable at frequencies >/= 0.01%, whereas by qPCR a detection limit of 0.001% was achievable. Furthermore, PBMNC from healthy controls (n = 30), patients with locally advanced rectal cancer (n = 20) and metastatic non-small cell lung cancer (NSCLC, n = 25) were analyzed. No increase of CEC/CEP was detectable by flow cytometry. Furthermore, only CD34 and KDR gene expression was significantly elevated in patients with metastatic NSCLC. However, both markers are not specific for endothelial cells.
CONCLUSION: QPCR is more sensitive, but less specific than 4-channel flow cytometry for the detection of CEC/CEP cell types. However, both methods failed to reliably detect an increase of CEC/CEP in tumor patients. Thus, more specific CEC/CEP markers are needed to validate and improve the detection of these rare cell types by PCR-based assays.

Parthenogenic blastocysts derived from cumulus-free in vitro matured human oocytes
McElroy SL, Byrne JA, Chavez SL, Behr B, Hsueh AJ, Westphal LM, Pera RA.
Center for Human Embryonic Stem Cell Research and Education, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Palo Alto, California, United States of America.
PLoS One. 2010 Jun 7;5(6):e10979.

BACKGROUND: Approximately 20% of oocytes are classified as immature and discarded following intracytoplasmic sperm injection (ICSI) procedures. These oocytes are obtained from gonadotropin-stimulated patients, and are routinely removed from the cumulus cells which normally would mature the oocytes. Given the ready access to these human oocytes, they represent a potential resource for both clinical and basic science application. However culture conditions for the maturation of cumulus-free oocytes have not been optimized. We aimed to improve maturation conditions for cumulus-free oocytes via culture with ovarian paracrine/autocrine factors identified by single cell analysis.
METHODOLOGY/PRINCIPAL FINDING: Immature human oocytes were matured in vitro via supplementation with ovarian paracrine/autocrine factors that were selected based on expression of ligands in the cumulus cells and their corresponding receptors in oocytes. Matured oocytes were artificially activated to assess developmental competence. Gene expression profiles of parthenotes were compared to IVF/ICSI embryos at morula and blastocyst stages. Following incubation in medium supplemented with ovarian factors (BDNF, IGF-I, estradiol, GDNF, FGF2 and leptin), a greater percentage of oocytes demonstrated nuclear maturation and subsequently, underwent parthenogenesis relative to control. Similarly, cytoplasmic maturation was also improved as indicated by development to blastocyst stage. Parthenogenic blastocysts exhibited mRNA expression profiles similar to those of blastocysts obtained after IVF/ICSI with the exception for MKLP2 and PEG1.
CONCLUSIONS/SIGNIFICANCE: Human cumulus-free oocytes from hormone-stimulated cycles are capable of developing to blastocysts when cultured with ovarian factor supplementation. Our improved IVM culture conditions may be used for obtaining mature oocytes for clinical purposes and/or for derivation of embryonic stem cells following parthenogenesis or nuclear transfer.