Nature Methods
Supplement issue: April 2011 Volume 8, No 4
Summary of the supplement on single-cell analysis
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In a series of commissioned pieces, authors discuss methods for the analysis of single cells and consider technical developments still needed. Three Reviews describe methods to study single-cell gene expression, peptide, and small-molecule metabolite profiles. Two Perspectives describe live-cell imaging and clonal analysis applied to single stem cells. A Commentary provides an overview of the technological developments underlying single-cell analysis and discusses applications of genome analysis in single cells.

Single-cell analysis - Methods to study single cell genomics
Since the beginning of research on cell biology, say Stephen Quake and Tomer Kalisky in a Commentary, technological advances have driven biological understanding of the single cell. Early microscopes that permitted biologists to observe single cells have led, via molecular marking techniques and flow cytometry, to the ability to rapidly monitor dozens of markers on thousands of individual cells. But the scale of single-cell analysis has not stopped there. The authors discuss methodologies, such as microfluidics, that are enabling highly parallel genome-scale analysis at single-cell resolution. They consider new applications—including haplotyping of human cells and the analysis of complex bacterial populations—for whole-genome sequencing of single cells. (Nat. Methods 8, 311–314, 2011)

Transcriptomes - Methods for single-cell transcriptome profiling
Strategies for single-cell transcriptome analysis

Cells, even when derived from a common tissue source or progenitor, vary in their gene expression, and this in turn influences their behavior and fate. It is thus important to analyze transcriptomes at single-cell resolution. In a Review, Azim Surani and colleagues take the reader through the steps of single-cell transcriptome analysis, from the isolation of single cells to the release and reverse transcription of mRNA and the amplification of the resulting cDNA, followed by DNA microarray analysis or high-throughput sequencing. The authors present available software tools for bioinformatic analysis of sequence data and discuss current limitations of single-cell transcriptome analyses such as the lack of discrimination between sense and antisense strands and the exclusion of non-polyadenylated transcripts. Finally, they describe up-and-coming areas such as single-molecule sequencing for full-length RNAs and the ability to sequence RNA that is actively being translated. (Nat. Methods 8, S6–S11, 2011)

Transcript imaging - Validating transcripts in single cells
Schematic of a branched probe for transcript imaging

High-throughput sequencing of transcripts in a single cell yields bulk information on what is being transcribed; to follow up on single transcripts in more detail, one needs to visualize the transcripts. In a Review, Alexander van Oudenaarden and Shalev Itzkovitz discuss methods for single-molecule transcript imaging in living and fixed cells. For transcript imaging in fixed cells, they describe fluorescence in situ hybridization (FISH) and derivative approaches based on labeled probes. For live cells, the authors compare methods based on gene fusion to the MS2 bacteriophage coat protein and molecular beacons. They discuss imaging technology and data analysis needed to extract information from single-molecule FISH experiments. In an outlook section they provide a glimpse into what is still required to make these methods more sensitive and to combine them with quantitative measurements of DNA and protein for a more complete picture of the expression networks that underlie tissue function. (Nat. Methods 8, S12–S19, 2011)

Relevance of circulating tumor cells, extracellular nucleic acids, and exosomes in breast cancer.
Friel AM, Corcoran C, Crown J, O'Driscoll L.
Breast Cancer Res Treat. 2010 Oct;123(3): 613-625
School of Pharmacy and Pharmaceutical Sciences & Molecular Therapeutics for Cancer Ireland, Trinity College Dublin, Dublin 2, Ireland.
Early detection of cancer is vital to improved overall survival rates. At present, evidence is accumulating for the clinical value of detecting occult tumor cells in peripheral blood, plasma, and serum specimens from cancer patients. Both molecular and cellular approaches, which differ in sensitivity and specificity, have been used for such means. Circulating tumor cells and extracellular nucleic acids have been detected within blood, plasma, and sera of cancer patients. As the presence of malignant tumors are clinically determined and/or confirmed upon biopsy procurement-which in itself may have detrimental effects in terms of stimulating cancer progression/metastases-minimally invasive methods would be highly advantageous to the diagnosis and prognosis of breast cancer and the subsequent tailoring of targeted treatments for individuals, if reliable panels of biomarkers suitable for such an approach exist. Herein, we review the current advances made in the detection of such circulating tumor cells and nucleic acids, with particular emphasis on extracellular nucleic acids, specifically extracellular mRNAs and discuss their clinical relevance.

Visualizing high error levels during gene expression in living bacterial cells.
Meyerovich M, Mamou G, Ben-Yehuda S.
Proc Natl Acad Sci U S A. 2010 Jun 22;107(25): 11543-11548
Department of Microbiology and Molecular Genetics, Institute for Medical Research, Israel-Canada, Hebrew University-Hadassah Medical School, Hebrew University of Jerusalem, 91120 Jerusalem, Israel.
To monitor inaccuracy in gene expression in living cells, we designed an experimental system in the bacterium Bacillus subtilis whereby spontaneous errors can be visualized and quantified at a single-cell level. Our strategy was to introduce mutations into a chromosomally encoded gfp allele, such that errors in protein production are reported in real time by the formation of fluorescent GFP molecules. The data reveal that the amount of errors can greatly exceed previous estimates, and that the error rate increases dramatically at lower temperatures and during stationary phase. Furthermore, we demonstrate that when facing an antibiotic threat, an increase in error level is sufficient to allow survival of bacteria carrying a mutated antibiotic-resistance gene. We propose that bacterial gene expression is error prone, frequently yielding protein molecules that differ slightly from the sequence specified by their DNA, thus generating a cellular reservoir of nonidentical protein molecules. This variation may be a key factor in increasing bacterial fitness, expanding the capability of an isogenic population to face environmental challenges.

A multimarker QPCR-based platform for the detection of circulating tumour cells in patients with early-stage breast cancer.
Molloy TJ, Devriese LA, Helgason HH, Bosma AJ, Hauptmann M, Voest EE, Schellens JH, Van't Veer LJ.
Br J Cancer. 2011 May 17. [Epub ahead of print]
Division of Experimental Therapy, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.
Background: The detection of circulating tumour cells (CTCs) has been linked with poor prognosis in advanced breast cancer. Relatively few studies have been undertaken to study the clinical relevance of CTCs in early-stage breast cancer.Methods:In a prospective study, we evaluated CTCs in the peripheral blood of 82 early-stage breast cancer patients. Control groups consisted of 16 advanced breast cancer patients and 45 healthy volunteers. The CTC detection was performed using ErbB2/EpCAM immunomagnetic tumour cell enrichment followed by multimarker quantitative PCR (QPCR). The CTC status and common clinicopathological factors were correlated to relapse-free, breast cancer-related and overall survival.
Results: Circulating tumour cells were detected in 16 of 82 (20%) patients with early-stage breast cancer and in 13 out of 16 (81%) with advanced breast cancer. The specificity was 100%. The median follow-up time was 51 months (range: 17-60). The CTC positivity in early-stage breast cancer patients resulted in significantly poorer relapse-free survival (log rank test: P=0.003) and was an independent predictor of relapse-free survival (multivariate hazard ratio=5.13, P=0.006, 95% CI: 1.62-16.31).
Conclusion: The detection of CTCs in peripheral blood of early-stage breast cancer patients provided prognostic information for relapse-free survival.

An improved one-tube RT-PCR protocol for analyzing single-cell gene expression in individual mammalian cells.
Li Y, Thompson H, Hemphill C, Hong F, Forrester J, Johnson RH, Zhang W, Meldrum DR.
Anal Bioanal Chem. 2010 Jul;397(5): 1853-1859
Center for Ecogenomics, The Biodesign Institute, Arizona State University, P.O. Box 876501, Tempe, AZ 85287-6501, USA
It is well known that gene expression is regulated at the level of individual cells, and more evidence is now emerging that heterogeneity of cell regulation is orders of magnitude greater than previously thought. In order to detect meaningful variations in transcription levels, it is necessary to measure gene expression at single cell levels rather than in bulk cells, where individual differences or heterogeneity could be lost. In this work, we report an improved reverse-transcriptase polymerase chain reaction (RT-PCR) protocol which allows the direct measurement of gene expression in one tube (5-25 microl of total PCR mixture) at the single mammalian cell level. The protocol employs a new cell lysis buffer, and involves no RNA isolation or nested PCR steps, significantly reducing the possibility of contamination and errors. We successfully applied this protocol in qRT-PCR and linear-after-the-exponential (LATE)-PCR to analyze selected genes of various expression levels from three cell lines. Although further characterization of RNA stability is important, the preliminary results showed that gene expression heterogeneity could be common among members of genetically identical cell populations. The protocol illustrated can be utilized for a wide array of applications without much modification, such as cancer cell analysis and preimplantation genetic diagnostics. In addition, the protocol is based on intercalator-based (SYBR Green PCR) chemistry, which is less expensive and suitable for high-throughput platforms.

Defining cell populations with single-cell gene expression profiling: correlations and identification of astrocyte subpopulations.
Stahlberg A, Andersson D, Aurelius J, Faiz M, Pekna M, Kubista M, Pekny M.
Nucleic Acids Res. 2011 Mar;39(4): e24
Center for Brain Repair and Rehabilitation, Department of Clinical Neuroscience and Rehabilitation, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Medicinaregatan 9A, 413 90 Gothenburg, Sweden
Single-cell gene expression levels show substantial variations among cells in seemingly homogenous populations. Astrocytes perform many control and regulatory functions in the central nervous system. In contrast to neurons, we have limited knowledge about functional diversity of astrocytes and its molecular basis. To study astrocyte heterogeneity and stem/progenitor cell properties of astrocytes, we used single-cell gene expression profiling in primary mouse astrocytes and dissociated mouse neurosphere cells. The transcript number variability for astrocytes showed lognormal features and revealed that cells in primary cultures to a large extent co-express markers of astrocytes and neural stem/progenitor cells. We show how subpopulations of cells can be identified at single-cell level using unsupervised algorithms and that gene correlations can be used to identify differences in activity of important transcriptional pathways. We identified two subpopulations of astrocytes with distinct gene expression profiles. One had an expression profile very similar to that of neurosphere cells, whereas the other showed characteristics of activated astrocytes in vivo.

Single-cell qPCR on dispersed primary pituitary cells - an optimized protocol.
Hodne K, Haug TM, Weltzien FA.
BMC Mol Biol. 2010 Nov 12;11:82.
Norwegian School of Veterinary Science, Department of Basic Sciences and Aquatic Medicine, Oslo, Norway.
BACKGROUND: The incidence of false positives is a potential problem in single-cell PCR experiments. This paper describes an optimized protocol for single-cell qPCR measurements in primary pituitary cell cultures following patch-clamp recordings. Two different cell harvesting methods were assessed using both the GH₄ prolactin producing cell line from rat, and primary cell culture from fish pituitaries.
RESULTS: Harvesting whole cells followed by cell lysis and qPCR performed satisfactory on the GH₄ cell line. However, harvesting of whole cells from primary pituitary cultures regularly produced false positives, probably due to RNA leakage from cells ruptured during the dispersion of the pituitary cells. To reduce RNA contamination affecting the results, we optimized the conditions by harvesting only the cytosol through a patch pipette, subsequent to electrophysiological experiments. Two important factors proved crucial for reliable harvesting. First, silanizing the patch pipette glass prevented foreign extracellular RNA from attaching to charged residues on the glass surface. Second, substituting the commonly used perforating antibiotic amphotericin B with β-escin allowed efficient cytosol harvest without loosing the giga seal. Importantly, the two harvesting protocols revealed no difference in RNA isolation efficiency.
CONCLUSION: Depending on the cell type and preparation, validation of the harvesting technique is extremely important as contaminations may give false positives. Here we present an optimized protocol allowing secure harvesting of RNA from single cells in primary pituitary cell culture following perforated whole cell patch clamp experiments.

RT-qPCR based quantitative analysis of gene expression in single bacterial cells.
Gao W, Zhang W, Meldrum DR.
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.

Real-time PCR of single bacterial cells on an array of adhering droplets.
Shi X, Lin LI, Chen SY, Chao SH, Zhang W, Meldrum DR.
Lab Chip. 2011 May 23
Center for Biosignatures Discovery Automation, Arizona State University, PO Box 876501. Tempe, AZ, USA
Real-time PCR at the single bacterial cell level is an indispensable tool to quantitatively reveal the heterogeneity of isogenetic cells. Conventional PCR platforms that utilize microtiter plates or PCR tubes have been widely used, but their large reaction volumes are not suited for sensitive single-cell analysis. Microfluidic devices provide high density, low volume PCR chambers, but they are usually expensive and require dedicated equipment to manipulate liquid and perform detection. To address these limitations, we developed an inexpensive chip-level device that is compatible with a commercial real-time PCR thermal cycler to perform quantitative PCR for single bacterial cells. The chip contains twelve surface-adhering droplets, defined by hydrophilic patterning, that serve as real-time PCR reaction chambers when they are immersed in oil. A one-step process that premixed reagents with cell medium before loading was applied, so no on-chip liquid manipulation and DNA purification were needed. To validate its application for genetic analysis, Synechocystis PCC 6803 cells were loaded on the chip from 1000 cells to one cell per droplet, and their 16S rRNA gene (two copies per cell) was analyzed on a commercially available ABI StepOne real-time PCR thermal cycler. The result showed that the device is capable of genetic analysis at single bacterial cell level with C(q) standard deviation less than 1.05 cycles. The successful rate of this chip-based operation is more than 85% at the single bacterial cell level.

Paired analysis of TCRα and TCRβ chains at the single-cell level in mice.
Dash P, McClaren JL, Oguin TH 3rd, Rothwell W, Todd B, Morris MY, Becksfort J, Reynolds C, Brown SA, Doherty PC, Thomas PG.
J Clin Invest. 2011 Jan 4;121(1): 288-295
St Jude Children’s Research Hospital, Memphis, Tennessee 38105-3678, USA.
Characterizing the TCRα and TCRβ chains expressed by T cells responding to a given pathogen or underlying autoimmunity helps in the development of vaccines and immunotherapies, respectively. However, our understanding of complementary TCRα and TCRβ chain utilization is very limited for pathogen- and autoantigen-induced immunity. To address this problem, we have developed a multiplex nested RT-PCR method for the simultaneous amplification of transcripts encoding the TCRα and TCRβ chains from single cells. This multiplex method circumvented the lack of antibodies specific for variable regions of mouse TCRα chains and the need for prior knowledge of variable region usage in the TCRβ chain, resulting in a comprehensive, unbiased TCR repertoire analysis with paired coexpression of TCRα and TCRβ chains with single-cell resolution. Using CD8+ CTLs specific for an influenza epitope recovered directly from the pneumonic lungs of mice, this technique determined that 25% of such effectors expressed a dominant, nonproductively rearranged Tcra transcript. T cells with these out-of-frame Tcra mRNAs also expressed an alternate, in-frame Tcra, whereas approximately 10% of T cells had 2 productive Tcra transcripts. The proportion of cells with biallelic transcription increased over the course of a response, a finding that has implications for immune memory and autoimmunity. This technique may have broad applications in mouse models of human disease.

Single Cell RT-PCR on Mouse Embryos: A General  Approach for Developmental Biology
Wolfgang Mann and Thomas Haaf
Nicola King (ed.), RT-PCR Protocols: Second Edition, Methods in Molecular Biology, vol. 630
Springer Science
Preimplantation development is a complicated process, which involves many genes. We have investigated the expression patterns of 17 developmentally important genes and isoforms in early mouse embryos as well as in single cells of the mouse embryo. The comparison is an excellent example for showing the importance of studying heterogeneity among cell populations on the RNA level, which is being increasingly addressed in basic research and medical sciences, particularly with a link to diagnostics (e.g. the analysis of circulating tumor cells and their progenitors). The ubiquitously expressed histone variant H3f3a and the transcription factor Pou5f1 generated mRNA-derived products in all analyzed preimplantation embryos (up to the morula stage) and in all analyzed blastomeres from 16-cell embryos, indicating a rather uniform reactivation of pluripotency gene expression during mouse preimplantation development. In contrast, genes that have been implicated in epigenetic genome reprogramming, such as DNA methyltransferases, methylcytosine-binding proteins, or base excision repair genes revealed considerable variation between individual cells from the same embryo and even higher variability between cells from different embryos. We conclude that at a given point of time, the transcriptome encoding the reprogramming machinery and, by extrapolation, genome reprogramming differs between blastomeres. It is tempting to speculate that cells expressing the reprogramming machinery have a higher developmental potential.

High throughput single cell expression profiling: Taking a closer look on biological response
Mikael Kubista, Linda Strömbom, David Svec, Vendula Rusnakova & Anders Stahlberg
TATAA Biocenter, Gothenburg, Sweden and the Institute of Biotechnology, CAS
European Pharmaceutical Review, Volume 16, Issue 2, 2011
Molecular analysis of tissue and in most cases also of bodily fluids is complicated because of tissue heterogeneity and the presence of many different cell types. Even cells of apparently the same type show substantial variation in gene expression under virtually identical conditions. When analysing classical samples based on tens of thousands of cells, this natural variability among cells is lost. With the advent of real-time quantitative polymerase chain reaction (qPCR), we have a most powerful tool to study diversity on the single cell level and can detect rare cells that are critical to treatment or survival.

Why Single Cells Matter
Fluidigm Corporation

A Whole New World:  Expression Profi ling of Single Cells  -  Who Wants to be Average?   versus   Actual Averaged
Within a population of seemingly identical cells, it is possible that variations in gene expression differ dramatically on a cell-to-cell level. These differences will be masked by the averaging effect of studying pooled samples. The solution is to examine multiple individual cells to identify those bearing unique transcriptomes. “There are very few people who pay attention to the advantages and importance of studying single cells,” said Ron McKay, Chief of the Laboratory of Molecular Biology at the National Institute of Neurological Disorders and Stroke in Bethesda, Maryland, in an article entitled A closer look at the single cell, Nature Reports stem cells, May 7, 2009. “They talk as if they do. They use a FACS machine and act as if they have single-cell data. But they don’t. They have data on a population, and that’s a completely different thing.”

Detection and quantification of mRNA in single human polar bodies: a minimally invasive test of gene expression during oogenesis.
Klatsky PC, Wessel GM, Carson SA.
Mol Hum Reprod. 2010 Dec;16(12): 938-943
Division of Reproductive Endocrinology and Infertility, Women and Infants Hospital, Alpert School of Medicine, Brown University, 101 Dudley Street, Providence, RI 02905, USA

Proteins and mRNA produced in oogenesis support embryonic development until the zygotic transition, 3 days after fertilization. Since polar bodies can be biopsied with little if any harm to the oocyte, we tested the hypothesis that mRNA originating from expression in the meiotic oocyte is present and detectable in a single polar body prior to insemination. Human oocytes were obtained from patients undergoing controlled ovarian hyperstimulation and intracytoplasmic sperm injection. Immature oocytes were cultured overnight and inspected the following day for maturation. Metaphase II oocytes underwent polar body biopsy followed by reverse transcription without RNA isolation. Sibling oocytes were similarly prepared. Complementary DNA from all samples were pre-amplified over 15 cycles for candidate genes using selective primers. Real-time PCR was performed to detect and quantify relative single-cell gene expression. Polar body mRNA was detected in 11 of 12 candidate genes. Transcripts that were present in greater abundance in the oocyte were more likely to be detected in qPCR replicates from single polar bodies. Pre-amplification of cDNA synthesized without RNA isolation can facilitate the quantitative detection of mRNA in single human polar bodies.

Modelling and measuring single cell RNA expression levels find considerable transcriptional differences among phenotypically identical cells.
Subkhankulova T, Gilchrist MJ, Livesey FJ.
BMC Genomics. 2008 Jun 3;9: 268.
Gurdon Institute and Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1 QN, UK

BACKGROUND: Phenotypically identical cells demonstrate predictable, robust behaviours. However, there is uncertainty as to whether phenotypically identical cells are equally similar at the underlying transcriptional level or if cellular systems are inherently noisy. To answer this question, it is essential to distinguish between technical noise and true variation in transcript levels. A critical issue is the contribution of sampling effects, introduced by the requirement to globally amplify the single cell mRNA population, to observed measurements of relative transcript abundance.
RESULTS: We used single cell microarray data to develop simple mathematical models, ran Monte Carlo simulations of the impact of technical and sampling effects on single cell expression data, and compared these with experimental microarray data generated from single embryonic neural stem cells in vivo. We show that the actual distribution of measured gene expression ratios for pairs of neural stem cells is much broader than that predicted from our sampling effect model.
CONCLUSION: Our results confirm that significant differences in gene expression levels exist between phenotypically identical cells in vivo, and that these differences exceed any noise contribution from global mRNA amplification.

Single-cell NF-kappaB dynamics reveal digital activation and analogue information processing.
Tay S, Hughey JJ, Lee TK, Lipniacki T, Quake SR, Covert MW.
Nature. 2010 Jul 8;466(7303): 267-271
Department of Bioengineering, Stanford University, Stanford, California 94305, USA

Cells operate in dynamic environments using extraordinary communication capabilities that emerge from the interactions of genetic circuitry. The mammalian immune response is a striking example of the coordination of different cell types. Cell-to-cell communication is primarily mediated by signalling molecules that form spatiotemporal concentration gradients, requiring cells to respond to a wide range of signal intensities. Here we use high-throughput microfluidic cell culture and fluorescence microscopy, quantitative gene expression analysis and mathematical modelling to investigate how single mammalian cells respond to different concentrations of the signalling molecule tumour-necrosis factor (TNF)-alpha, and relay information to the gene expression programs by means of the transcription factor nuclear factor (NF)-kappaB. We measured NF-kappaB activity in thousands of live cells under TNF-alpha doses covering four orders of magnitude. We find, in contrast to population-level studies with bulk assays, that the activation is heterogeneous and is a digital process at the single-cell level with fewer cells responding at lower doses. Cells also encode a subtle set of analogue parameters to modulate the outcome; these parameters include NF-kappaB peak intensity, response time and number of oscillations. We developed a stochastic mathematical model that reproduces both the digital and analogue dynamics as well as most gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-alpha-induced NF-kappaB signalling in various types of cells. These results highlight the value of high-throughput quantitative measurements with single-cell resolution in understanding how biological systems operate.

Single-allele analysis of transcription kinetics in living mammalian cells.
Yunger S, Rosenfeld L, Garini Y, Shav-Tal Y.
Nat Methods. 2010 Aug;7(8): 631-633
The Mina and Everard Goodman Faculty of Life Sciences and Institute of Nanotechnology, Bar-Ilan University, Ramat Gan, Israel.

We generated a system for in vivo visualization and analysis of mammalian mRNA transcriptional kinetics of single alleles in real time, using single-gene integrations. We obtained high-resolution transcription measurements of a single cyclin D1 allele under endogenous or viral promoter control, including quantification of temporal kinetics of transcriptional bursting, promoter firing, nascent mRNA numbers and transcription rates during the cell cycle, and in relation to DNA replication.

Acoustic microstreaming increases the efficiency of reverse transcription reactions comprising single-cell quantities of RNA.
Boon WC, Petkovic-Duran K, White K, Tucker E, Albiston A, Manasseh R, Horne MK, Aumann TD.
Biotechniques. 2011 Feb;50(2):116-169
Florey Neuroscience Institutes, The University of Melbourne, Parkville, Victoria, Australia; Centre of Neuroscience, The University of Melbourne, Parkville, Victoria, Australia

Correlating gene expression with behavior at the single-cell level is difficult, largely because the small amount of available mRNA (<1 pg) degrades before it can be reverse transcribed into a more stable cDNA copy. This study tested the capacity for a novel acoustic microstreaming method ("micromixing"), which stirs fluid at microliter scales, to improve cDNA yields from reverse transcription (RT) reactions comprising single-cell quantities of RNA. Micromixing significantly decreased the number of qPCR cycles to detect cDNA representing mRNA for hypoxanthine phosphoribosyl-transferase (Hprt) and nuclear receptor-related 1 (Nurr1) by ~9 and ~15 cycles, respectively. The improvement was equivalent to performing RT with 10- to 100-fold more cDNA in the absence of micromixing. Micromixing enabled reliable detection of the otherwise undetectable, low-abundance transcript, Nurr1. It was most effective when RNA concentrations were low (0.1-1 pg/µL, a "single-cell equivalent") but had lesser effects at higher RNA concentrations (~1 ng/µL). This was supported by imaging experiments showing that micromixing improved mixing of a low concentration (20 pg/µL) of fluorescence-labeled RNA but not a higher concentration (1 ng/µL). We conclude that micromixing significantly increases RT yields obtainable from single-cell quantities of RNA.

Quantitative single-cell gene expression measurements of multiple genes in response to hypoxia treatment
Jia Zeng, Jiangxin Wang, Weimin Gao, Aida Mohammadreza, Laimonas Kelbauskas, Weiwen Zhang, Roger H. Johnson and Deirdre R. Meldrum
Anal Bioanal Chem 2011

Cell-to-cell heterogeneity in gene transcription plays a central role in a variety of vital cell processes. To quantify gene expression heterogeneity patterns among cells and to determine their biological significance, methods to measure gene expression levels at the single-cell level are highly needed. We report an experimental technique based on the DNA-intercalating fluorescent dye SYBR green for quantitative expression level analysis of up to ten selected genes in single mammalian cells. The method features a two-step procedure consisting of a step to isolate RNA from a single mammalian cell, synthesize cDNA from it, and a qPCR step. We applied the method to cell populations exposed to hypoxia, quantifying expression levels of seven different genes spanning a wide dynamic range of expression in randomly picked single cells. In the experiment, 72 single Barrett’s esophageal epithelial (CP-A) cells, 36 grown under normal physiological conditions (controls) and 36 exposed to hypoxia for 30 min, were randomly collected and used for measuring the expression levels of 28S rRNA, PRKAA1, GAPDH, Angptl4, MT3, PTGES, and VEGFA genes. The results demonstrate that the method is sensitive enough to measure alterations in gene expression at the single-cell level, clearly showing heterogeneity within a cell population. We present technical details of the method development and implementation, and experimental results obtained by use of the procedure. We expect the advantages of this technique will facilitate further developments and advances in the field of single-cell gene expression profiling on a nanotechnological scale, and eventually as a tool for future point-of-care medical applications.