Single-cell molecular-biology is a relatively new scientific branch in biology. The first single-cell analysis were involved in the characterization of mitochondrial DNA in 1988. Single-cell DNA analysis, in particular genomic DNA, is important and may be informative in the analysis of genetics of cell clonality, genetic anticipation and single-cell DNA polymorphisms. Nowadays for most scientists the quantitative transcriptomics in a single-cell is much more important, and the analytical method of choice is the quantitative real-time RT-PCR. In single-cell biology the absolute abundance of particular mRNAs or microRNAs and their up- or down-regulation in a single cell, compared to their neighbour cells, is the goal. The need for quantitative single-cell mRNA analysis is evident given the vast cellular heterogeneity of all tissue cells and the inability of conventional RNA methods, like northern blotting, RNAse protection assay or classical block RT-PCR, to distinguish individual cellular contributions to mRNA abundance differences.

The purpose of this single-cell qPCR page is to provide researchers with resources (papers, talks, posters) for single-cell molecular analysis such as qPCR and RT-qPCR:

Single-Cell -omics
in Nature Reviews

Recent technological advances are providing unprecedented opportunities to analyse the complexities of biological systems at the single-cell level. Various crucial biological phenomena are either invisible or only partially characterized when interrogated using standard analyses that average data across a bulk population of cells. However, high-throughput analyses of the genomes, transcriptomes and proteomes of single cells are providing novel and important insights into diverse processes such as development, gene-expression dynamics, tissue heterogeneity and disease pathogenesis.

Sequencing the Single Cell – Adventures in Genomics
by Illumina Inc.

A single cell is the smallest building block in biology. Each and every cell contains an entire genome with all the information to create an entire organism – be it a bacterium or a buffalo cell. Recent advances in sequencing technology are making it possible to extract and sequence the genomes from individual cells. This is advancing our understanding of many biological processes.

Technical aspects and recommendations for single-cell qPCR
Stahlberg A and Kubista M
Mol Aspects Med. 2018 Feb;59:28-35
Single cells are basic physiological and biological units that can function individually as well as in groups in tissues and organs. It is central to identify, characterize and profile single cells at molecular level to be able to distinguish different kinds, to understand their functions and determine how they interact with each other. During the last decade several technologies for single-cell profiling have been developed and used in various applications, revealing many novel findings. Quantitative PCR (qPCR) is one of the most developed methods for single-cell profiling that can be used to interrogate several analytes, including DNA, RNA and protein. Single-cell qPCR has the potential to become routine methodology but the technique is still challenging, as it involves several experimental steps and few molecules are handled. Here, we discuss technical aspects and provide recommendation for single-cell qPCR analysis. The workflow includes experimental design, sample preparation, single-cell collection, direct lysis, reverse transcription, preamplification, qPCR and data analysis. Detailed reporting and sharing of experimental details and data will promote further development and make validation studies possible. Efforts aiming to standardize single-cell qPCR open up means to move single-cell analysis from specialized research settings to standard research laboratories.

RT-qPCR work-flow for single-cell data analysis
Anders Ståhlberg, Vendula Rusnakova, Amin Forootan, Miroslava Anderova, Mikael Kubista
Methods 2013, Vol 59, Issue 1, pages 80-88
Individual cells represent the basic unit in tissues and organisms and are in many aspects unique in their properties. The introduction of new and sensitive techniques to study single-cells opens up new avenues to understand fundamental biological processes. Well established statistical tools and recommendations exist for gene expression data based on traditional cell population measurements. However, these workflows are not suitable, and some steps are even inappropriate, to apply on single-cell data. Here, we present a simple and practical workflow for preprocessing of single-cell data generated by reverse transcription quantitative real-time PCR. The approach is demonstrated on a data set based on profiling of 41 genes in 303 single-cells. For some pre-processing steps we present options and also recommendations. In particular, we demonstrate and discuss different strategies for handling missing data and scaling data for downstream multivariate analysis. The aim of this workflow is provide guide to the rapidly growing community studying single-cells by means of reverse transcription quantitative real-time PCR profiling.

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.

Quantification of mRNA in single cells and modelling of RT-qPCR induced noise
Bengtsson M, Hemberg M, Rorsman P, Stahlberg A.
BMC Mol Biol. 2008 Jul 17;9:63.
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford,
The Churchill Hospital, Oxford, OX3 7LJ, UK.
BACKGROUND: Gene expression has a strong stochastic element resulting in highly variable mRNA levels between individual cells, even in a seemingly homogeneous cell population. Access to fundamental information about cellular mechanisms, such as correlated gene expression, motivates measurements of multiple genes in individual cells. Quantitative reverse transcription PCR (RT-qPCR) is the most accessible method which provides sufficiently accurate measurements of mRNA in single cells.
RESULTS: Low concentration of guanidine thiocyanate was used to fully lyse single pancreatic beta-cells followed by RT-qPCR without the need for
purification. The accuracy of the measurements was determined by a quantitative noise-model of the reverse transcription and PCR. The noise is insignificant for initial copy numbers >100 while at lower copy numbers the noise intrinsic of the PCR increases sharply, eventually obscuring quantitative measurements. Importantly, the model allows us to determine the RT efficiency without using artificial RNA as a standard. The experimental setup was applied on single endocrine cells, where the technical and biological noise levels were determined.
CONCLUSION: Noise in single-cell RT-qPCR is insignificant compared to biological cell-to-cell variation in mRNA levels for medium and high abundance transcripts. To minimize the technical noise in single-cell RT-qPCR, the mRNA should be analyzed with a single RT reaction, and a single qPCR reaction per gene.

Single-cell molecular biology.
Eberwine J. Nat Neurosci. 2001 4 Suppl: 1155-1156 Department of Pharmacology, University of Pennsylvania Medical Center, 36th
Street and Hamilton Walk, Philadelphia, Pennsylvania 19104, USA.

Single-molecule DNA amplification and analysis in an integrated microfluidic device.
Lagally ET, Medintz I, Mathies RA.
Department of Chemistry, University of California, Berkeley 94720, USA.
Anal Chem. 2001 Feb 1;73(3):565-70.

Stochastic PCR amplification of single DNA template molecules followed by capillary electrophoretic (CE) analysis of the products is demonstrated in an integrated microfluidic device. The microdevice consists of submicroliter PCR chambers etched into a glass substrate that are directly connected to a microfabricated CE system. Valves and hydrophobic vents provide controlled and sensorless loading of the 280-nL PCR chambers; the low volume reactor, the low thermal mass, and the use of thin-film heaters permit cycle times as fast as 30 s. The amplified product, labeled with an intercalating fluorescent dye, is directly injected into the gel-filled capillary channel for electrophoretic analysis. Repetitive PCR analyses at the single DNA template molecule level exhibit quantized product peak areas; a histogram of the normalized peak areas reveals clusters of events caused by 0, 1, 2, and 3 viable template copies in the reactor and these event clusters are shown to fit a Poisson distribution. This device demonstrates the most sensitive PCR possible in a microfabricated device. The detection of single DNA molecules will also facilitate single-cell and single-molecule studies to expose the genetic variation underlying ensemble sequence and expression averages.

Expression profiling of single mammalian cells - small is beautiful.
Brady G.
School of Biological Sciences, G.38 Stopford Building, University of Manchester,
Oxford Road, Manchester M13 9PT, UK.
Yeast. 2000 Sep 30;17(3):211-217
Increasingly mRNA expression patterns established using a variety of molecular technologies such as cDNA microarrays, SAGE and cDNA display are being used to identify potential regulatory genes and as a means of providing valuable insights into the biological status of the starting sample. Until recently, the application of these techniques has been limited to mRNA isolated from millions or, at very best, several thousand cells thereby restricting the study of small samples and complex tissues. To overcome this limitation a variety of amplification approaches have been developed which are capable of broadly evaluating mRNA expression patterns in single cells. This review will describe approaches that have been employed to examine global gene expression patterns either in small numbers of cells or, wherever possible, in actual isolated single cells. The first half of the review will summarize the technical aspects of methods developed for single-cell analysis and the latter half of the review will describe the areas of biological research that have benefited from single-cell expression analysis.

Current applications of single-cell PCR.
Hahn S, Zhong XY, Troeger C, Burgemeister R, Gloning K, Holzgreve W.
Department of Obstetrics and Gynaecology, University of Basel, Switzerland
Cell Mol Life Sci. 2000 57(1): 96-105
Plant organs are composed of many different cell types and the analysis of  'bulk' material results in the average of all information in these cells. Therefore, this does not reflect any individuality of the tissues present in plants. This review briefly summarizes different sampling methods which provide tissue- and cell-specific samples, respectively. In addition, gene expression analysis tools that allow the analysis of transcripts in minute samples are discussed in detail. The combination of both approaches results in high resolution gene expression data, which increases understanding of plant physiology in such diverse areas as primary and secondary metabolism, plant defence or stress response.

Quantification of Multiple Gene Expression in Individual Cells.
Antonio Peixoto, Marta Monteiro, Benedita Rocha,1 and Henrique Veiga-Fernandes
INSERM U591, Institut Necker, Paris, 75015 France
Genome Research 2004, 14: 1938-1947

Quantitative gene expression analysis aims to define the gene expression patterns determining cell behavior. So far, these assessments can only be performed at the population level. Therefore, they determine the average gene expression within a population, overlooking possible cell-to-cell heterogeneity that could lead to different cell behaviors/cell fates. Understanding individual cell behavior requires multiple gene expression analyses of single cells, and may be fundamental for the understanding of all types of biological events and/or differentiation processes. We here describe a new reverse transcription-polymerase chain reaction (RT-PCR) approach allowing the simultaneous quantification of the expression of 20 genes in the same single cell. This method has broad application, in different species and any type of gene combination. RT efficiency is evaluated. Uniform and maximized amplification conditions for all genes are provided. Abundance relationships are maintained, allowing the precise quantification of the absolute number of mRNA molecules per cell, ranging from 2 to 1.28×109 for each individual gene. We evaluated the impact of this approach on functional genetic read-outs by studying an apparently homogeneous  population (monoclonal T cells recovered 4 d after antigen stimulation), using either this method or conventional real-time RT-PCR. Single-cell studies revealed considerable cell-to-cell variation: All T cells did not express all individual genes. Gene coexpression patterns were very heterogeneous. mRNA copy numbers varied between different transcripts and in different cells. As a consequence, this single-cell assay introduces new and fundamental information regarding functional genomic read-outs. By comparison, we also show that conventional quantitative assays determining population averages supply insufficient information, and may even be highly misleading.

New techniques for isolation of single prokaryotic cells.  REVIEW
Frohlich J, Konig H.
Institut fur Mikrobiologie und Weinforschung, Johannes Gutenberg-Universitat, Becherweg 15, 55128, Mainz, Germany.

FEMS Microbiol Rev. 2000 Dec;24(5):567-72.

Since the 1960s, several new attempts have been made to improve the management of single prokaryotic cells using micromanipulator techniques. In order to facilitate the isolation of pure cultures we have recently developed an improved micromanipulation method for routine work. With the aid of this method single prokaryotic cells can be picked out of a mixed community under direct visual control. The isolated aerobic or anaerobic cells can be grown in pure culture or can be subjected to single cell PCR. Other powerful and completely new approaches are the applications of laser micromanipulation systems, such as optical tweezers or laser microdissection techniques. Of the latter two methods only optical tweezers have been successfully applied to cloning prokaryotic cells.

Single cell sorting and cloning
Francis L. Battye, Amanda Light and David M. Tarlinton
The Walter & Eliza Hall Institute of Medical Research, Post Office
Royal Melbourne Hospital, Melbourne, Victoria 3050, Australia,
Journal of Immunological Methods, Volume 243 (1-2) 2000, Pages 25-32

Cell sorters now allow the selection of cells and other bodies according to a range of quite diverse criteria. The additional refinement that allows the sorting of individual cells based on these criteria has seen application in many fields of research. Single cells may be sorted for microscopy, for culture and for genetic analysis by way of single cell PCR. In practical terms, in the setting up of an instrument for single cell sorting, there are additional requirements to ensure that each detected event is indeed a single cell or body, that this cell can be reliably sorted via saline droplet, separate from its fellow travelers, that the aiming of the droplet deflection is sufficiently precise to find the target vessel and that the cell will be undamaged on arrival. Among the diverse reported applications of the technique, two fields which have benefited greatly are lymphocyte development and haemopoiesis. In the former case, the analysis of gene rearrangements in lymphocytes, both in the pre- and post-antigenic phases of development, has been enabled by the combined technologies of single cell sorting and PCR. It is argued that such experiments could not have been done without that partnership. In a similar way, the single cell sorting technique has been found to be the perfect way to demonstrate precursor/progeny relationships between haemopoietic cells and, further, to demonstrate rigorously the effects of particular cytokines on the haemopoietic system.

Current applications of single-cell PCR.
Hahn S, Zhong XY, Troeger C, Burgemeister R, Gloning K, Holzgreve W.
Department of Obstetrics and Gynaecology, University of Basel, Switzerland
Cell Mol Life Sci. 2000 57(1): 96-105
The advent of the polymerase chain reaction (PCR) has revolutionised the way in which molecular biologists view their task at hand, for it is now possible to amplify and examine minute quantities of rare genetic material: the limit of this exploration being the single cell. It is especially in the field of prenatal diagnostics that this ability has been readily seized upon, as it has opened up the prospect of preimplantation genetic analysis and the use of fetal cells enriched from the blood of pregnant women for the assessment of single-gene Mendelian disorders. However, apart from diagnostic applications, single-cell PCR has proven to be of enormous use to basic scientists, addressing diverse immunological, neurological and developmental questions, where both the genome but also messenger RNA expression patterns were examined. Furthermore, recent advances, such as optimised whole genome amplification (WGA) procedures, single-cell complementary DNA arrays and perhaps even single-cell comparative genomic hybridisation will ensure that the genetic analysis of single cells will become common practice, thereby opening up new possibilities for diagnosis and research.

Research Highlight  -  Gene expression: Which mean do you mean?
Patrick Goymer
Nature Reviews Genetics 6, 877 (December 2005)

There is considerable variation in gene-expression levels between individual cells. Bengtsson et al. show that these levels are distributed log-normally rather than normally, which implies that the arithmetic mean does not represent the situation in a typical cell. They also show that the levels of expression of different genes in the same cell do not generally correlate, and suggest that mechanistic conclusions can be drawn when they do. Using reverse transcriptase quantitative real-time PCR, they measured the transcript levels of 5 genes in 169 mouse pancreatic cells. For each gene the results were distributed log-normally across the sample cells, making the geometric mean a more appropriate representation of the data than the more commonly quoted arithmetic mean. For the insulin genes, Ins1 and Ins2, up to 9-fold differences were found between the arithmetic and geometric means. Of the five genes studied, only Ins1 and Ins2 expression levels correlated at the level of the individual cell. Levels of ActB, the beta -actin gene, correlated with these two only at the overall population level, whereas levels of the final two genes did not correlate with any of the others. This indicates that expression-level differences in individual genes are not due to cells having different levels of overall transcription. The authors suggest that genes that correlate at the individual cell level are co-ordinately regulated, whereas those that correlate at the population level merely respond to the same environmental stimuli. The importance of these findings is demonstrated by the fact that we might have underestimated the effect of glucose on insulin expression by almost 4-fold, which could be important in the administration of therapeutic insulin.

References (see below)
Bengtsson, M. et al. Gene-expression profiling in single cells from the pancreatic islets of Langerhans reveals lognormal distribution of mRNA levels. Genome Res. 15, 1388–1392 (2005)
Gene expression profiling in single cells from the pancreatic islets of
Langerhans reveals lognormal distribution of mRNA levels.
Bengtsson M, Stahlberg A, Rorsman P, Kubista M.
Department of Experimental Medical Science, Lund University, 221 84 Lund, Sweden
TATAA Biocenter, Lundberg Laboratory,405 30 Goeteborg, Sweden
Genome Res. 2005 15(10):1388-92
The transcriptional machinery in individual cells is controlled by a relatively small number of molecules, which may result in stochastic behavior in gene activity. Because of technical limitations in current collection and recording methods, most gene expression measurements are carried out on populations of cells and therefore reflect average mRNA levels. The variability of the transcript levels between different cells remains undefined, although it may have profound effects on cellular activities. Here we have measured gene expression levels of the five genes ActB, Ins1, Ins2, Abcc8, and Kcnj11 in individual cells from mouse pancreatic islets. Whereas Ins1 and Ins2 expression show a strong cell-cell correlation, this is not the case for the other genes. We further found that the transcript levels of the different genes are lognormally distributed. Hence, the geometric mean of expression levels provides a better estimate of gene activity of the typical cell than does the arithmetic mean measured on a cell population.

Distribution of mRNA transcripts in single cells determined by quantitative RT-PCR.
Martin Bengtsson1, Anders Ståhlberg2, Patrik Rorsman(1, 3), Mikael Kubista2
1: Department of Experimental Medical Science, Lund University, Lund, Sweden. 2: Department of Chemistry and Biosciences - Molecular Biotechnology, Chalmers University of Technology and TATAA Biocenter, Göteborg, Sweden.
3: The Oxford Centre for Diabetes, Endocrinology and Metabolism, The Churchill Hospital, Oxford, England.
Poster at the qPCR meeting qPCR 2005 in Freising Weihenstephan
A cell contains approximately 20 pg of RNA, of which <5% is mRNA. That corresponds to a few hundred thousand transcripts, representing some 10,000 genes expressed at one timepoint. The constitution of this expression palette, or transcriptome, determines the fate of the cell and is a record of its recent history. Gene expression is ultimately controlled at the single cell level, but still, most gene expression analysis studies of today are carried out using thousands or millions of cells, for practical reasons. The measurements become a representation of the average cell, and individual differences in transcript levels remain undisclosed. Differences in a small proportion of the cell population are not likely to be revealed when looking at whole cultures or tissues.
When a small number of molecules determine the fate of a chemical equilibrium, a certain randomness and stochasticity is observed. As the number of molecules increase as do the predictability of the reaction. The number of enhancer and transcription activator molecules in a cell is low, and a stochastic element is thus seen in gene expression analysis at the single cell level. It has been suggested that some genes are expressed in a binary, on or off, behavior, resulting in a binomial population distribution of the transcript levels.
We have studied the gene expression of single cells in the pancreatic islets of Langerhans in mice using quantitative RT-PCR. The pancreatic islets are heterogeneous clusters of cells releasing major metabolic hormones, such as insulin. Precise quantification at this level has never before been carried out in tissues and data reveal intricate correlation between related genes while simultaneously showing a large spread between cells of the same type. Furthermore, we see a lognormal distribution of transcript levels in the single cell.

Global cDNA amplification combined with real-time RT-PCR: 
accurate quantification of multiple human potassium channel genes at the single cell level.

Al-Taher A, Bashein A, Nolan T, Hollingsworth M, Brady G. (2000)

Yeast. 2000 Sep 30;17(3): 201-210

We have developed a sensitive quantitative RT-PCR procedure suitable for the analysis of small samples, including single cells, and have used it to measure levels of potassium channel mRNAs in a panel of human tissues and small numbers of cells grown in culture. The method involves an initial global amplification of cDNA derived from all added polyadenylated mRNA followed by quantitativeRT-PCR of individual genes using specific primers. In order to facilitate rapid and accurate processing of samples, we have adapted the approach to allow use of TaqMan real-time quantitative PCR. We demonstrate that the approach represents a major improvement over existing conventional and real-time quantitative PCR approaches, since it can be applied to samples equivalent to a single cell, isable to accurately measure expression levels equivalent to less than 1/100th copy/cell (one specific cDNA molecule present amongst 10(8) total cDNA molecules). Furthermore, since the initial step involves a global amplification of all expressed genes, a permanent cDNA archive is generated from each sample, which can be regenerated indefinitely for further expression analysis.

Correlating function and gene expression of individual basal ganglia neurons.
 Liss B, Roeper J.

Molecular Neurobiology, Institute for Physiology, Philipps-University Marburg, Deutschhausstrasse 2, 35033 Marburg, Germany.
Trends Neurosci. 2004 Aug;27(8):475-81
Functional studies at the level of individual neurons have greatly contributed to our current understanding of basal ganglia function and dysfunction. However, identification of the expressed genes responsible for these distinct neuronal phenotypes is less advanced. Qualitative and quantitative single-cell gene-expression profiling, combined with electrophysiological analysis, allows phenotype-genotype correlations to be made for individual neurons. In this review, progress on gene-expression profiling of individual, functionally characterized basal ganglia neurons is discussed, focusing on ion channels and receptors. In addition, methodological issues are discussed and emerging novel techniques are introduced that will enable a genome-wide comparison of function and gene expression for individual neurons.

Improved quantitative real-time RT-PCR for expression profiling of individual cells.
Liss B.

Nucleic Acids Res  2002 Sep 1;30(17):e89

University Laboratory of Physiology and MRC Anatomical Neuropharmacology Unit,
Department of Pharmacology, Oxford University, Parks Road, Oxford OX1 3PT, UK.

The real-time quantitative polymerase chain reaction (rtqPCR) has overcome the limitations of conventional, time-consuming quantitative PCR strategies and is maturing into a routine tool to quantify gene expression levels, following reverse transcription (RT) of mRNA into complementary DNA (cDNA). Expression profiling with single-cell resolution is highly desirable, in particular for complex tissues like the brain that contain a large variety of different cell types in close proximity. The patch-clamp technique allows selective harvesting of single-cell cytoplasm after recording of cellular activity. However, components of the cDNA reaction, in particular the reverse transcriptase itself, significantly inhibit subsequent rtqPCR amplification. Using undiluted single-cell cDNA reaction mix directly as template for rtqPCR, I observed that  the amplification kinetics of rtqPCRs were dramatically altered in a  non-systematic fashion. Here, I describe a simple and robust precipitation  protocol suitable for purification of single-cell cDNA that completely removes  inhibitory RT components without detectable loss of cDNA. This improved  single-cell real-time RT-PCR protocol provides a powerful tool to quantify  differential gene expression of individual cells and thus could complement  global microarray-based expression profiling strategies.

Rapid, single-tube method for quantitative preparation and analysis of RNA and DNA in samples as small as one cell.
Hartshorn C, Anshelevich A, Wangh LJ.
BMC Biotechnol. 2005 5(1): 2.

Current methods for accurate quantification of nucleic acids typically begin with a template preparation step in which DNA and/or RNA are freed of bound proteins and are then purified. Isolation of RNA is particularly challenging because this molecule is sensitive to elevated temperatures and is degraded by RNases, which therefore have to be immediately inactivated upon cell lysis. Many protocols for nucleic acids purification, reverse transcription of RNA and/or amplification of DNA require repeated transfers from tube to tube and other manipulations during which materials may be lost. This paper introduces a novel and highly reliable single-tube method for rapid cell lysis, followed by quantitative preparation and analysis of both RNA and/or DNA molecules in small samples. In contrast to previous approaches, this procedure allows all steps to be carried out by sequential dilution in a single tube, without chemical extraction or binding to a matrix. We demonstrate the utility of this method by quantification of four genes, Xist, Sry and the two heat-inducible hsp70i (hsp70.1 and hsp70.3), as well as their RNA transcripts in single mouse embryos and in isolated blastomeres. This method virtually eliminates losses of nucleic acids and is sensitive and accurate down to single molecules.

Real-time PCR with molecular beacons provides a highly accurate assay for detection of Tay-Sachs alleles in single cells.
Rice JE, Sanchez JA, Pierce KE, Wangh LJ.
Department of Biology, Brandeis University, Waltham, MA 02454-9110, USA.
Prenat Diagn. 2002 Dec;22(12): 1130-1134
The results presented here provide the first single-cell genetic assay for Tay-Sachs disease based on real-time PCR. Individual lymphoblasts were lysed with an optimized lysis buffer and assayed using one pair of primers that amplifies both the wild type  and 1278 + TATC Tay-Sachs alleles. The resulting amplicons were detected in real time with two molecular beacons each with a different colored fluorochrome. The kinetics of amplicon accumulation generate objective criteria by which to evaluate the validity of each reaction. The assay had an overall utility of 95%, based on the detection of at least one signal in 235 of the 248 attempted tests and an efficiency of 97%, as 7 of the 235 samples were excluded from further analysis for objective quantitative reasons. The accuracy of the assay was 99.1%, because 228 of 230 samples gave signals consistent with the genotype  of the cells. Only two of the 135 heterozygous samples were allele drop-outs, a rate far lower than previously reported for single-cell Tay-Sachs assays  using conventional methods of PCR.

Laser-Capture Microdissection  and  qRT-PCR

One-Step RT-PCR without Initial RNA Isolation Step for Laser-Microdissected Tissue Sample

Kiyoshi KOBAYASHI, Hiroyuki UTSUMI, Miyoko OKADA, Tetsuya SAKAIRI,
Itsuko IKEDA, Manami KUSAKABE and Shirou TAKAGI
Discovery Technology Laboratory, Mitsubishi Pharma Co., Toxicology Laboratory, Mitsubishi Pharma Co.
Journal of Veterinary Medical Science Vol. 65 (2003), No. 8 : 917-919

One-step RT-PCR procedure without initial RNA extraction step is tested for laser microdissected tissue sample. Unfixed cryosections of liver and kidney tissue of male SD rats were cut using laser microdissection system and directly used as templates for RT-PCR study. To check the sensitivity, 5, 25, 125, and 625 hepatocytes were cut and put in PCR-tube. After DNase treatment and cDNA synthesis with pd(N)6 random primer, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) cDNAs were amplified by 60 thermal cycles. GAPDH-specific bands were observed at as few as 25 hepatocytes. Specificity of this procedure was tested for hepatocytes, renal tubular epithelium and glomerular tissue using albumin PCR primers. Approximately 250 cells were cut and albumin cDNA was amplified as described above. Albumin specific band was observed only in hepatocytes sample. To apply this approach to quantitative PCR, various numbers of hepatocytes were cut and put in 0.2 mL PCR tube. After reverse transcription and 10 cycles of GAPDH cDNA amplification by regular thermal-cycler, PCR solution was transferred to 96-well plate designed for real-time PCR system, and further 40 cycles were performed. As a result, GAPDH cDNAs were successfully amplified with a good correlation between the number of template hepatocytes and the intensity of PCR signal. From these results, we concluded this approach would be very useful for the expression analysis of microdissected pathology samples.

Real-time quantitative RT-PCR after laser-assisted cell picking
Fink L, Seeger W, Ermert L, Hanze J, Stahl U, Grimminger F, Kummer W, Bohle RM.
Department of Pathology, Justus-Liebig-Universitat Giessen, Germany.
Nat Med. 1998 4(11): 1329-1333.
The present study describes a technique for quantitation of mRNA in a few isotypic cells obtained from an intact organ structure by combining laser-assisted cell picking and real-time PCR. The microscopically controlled lasering of selected cells in stained tissue sections was applied to lung alveolar macrophages, which are unique in that they can alternatively be gathered as a pure cell population from intact lungs by bronchoalveolar lavage as a reference technique. TNF-alpha was chosen as the transcriptionally inducible target gene to be quantified in alveolar macrophages of control rat lung, as well as low- and high-challenge lungs stimulated by endotoxin and IFN-gamma nebulization. Online fluorescence detection for quantitation of the number of amplified copies was based on 5' nuclease activity of Taq polymerase cleaving a sequence-specific dual-labeled fluorogenic hybridization probe. A pseudogene-free sequence of PBGD served as an internal calibrator for comparative quantitation of target. A quick procedure and minimized loss of template were achieved by avoiding RNA extraction, DNase digestion and nested-PCR. Using this approach, we demonstrated dose-dependent manifoldupregulation of the ratio of TNF-alpha mRNA copies per one copy of PBGD mRNA in alveolar macrophages of the challenged lungs. The quantitative data obtained from laser-picked alveolar macrophages were well matched with those of lavaged alveolar macrophages carried out in parallel. We suggest that this new combination of laser-assisted cell picking and real-time PCR has great promise for quantifying mRNA expression in a few single cells or oligocellular clusters in intact organs, allowing assessment of transcriptional regulation in defined cell populations.

Small-Sample Total RNA Purification: Laser Capture Microdissection and Cultured Cell Applications.
Karen E. Dolter and Jeffrey C. Braman Stratagene, La Jolla, CA, USA
BioTechniques 30:1358-1361 (June 2001)

Gene expression studies require analysis of RNA, but isolation of total RNA from very small samples by traditional methods can be difficult and inefficient. The Absolutely RNA‘ microprep kit provides a convenient method for isolating total RNA from small numbers of cells such as those harvested by laser capture microdissection (LCM). The protocol includes binding of RNA to a solid support, thus eliminating the need for organic extraction and alcohol precipitation. DNase digestion on the solid support reduces or eliminates DNA contamination and minimizes RNA handling. Efficient washing removes contaminants, and elution in a small volume of buffer results in high-purity RNA at a concentration appropriate for demanding applications such as RT-PCR. RNA isolated from as few as 200 laser capture microdissected brain tumor cells resulted in detection of low, medium, and highly expressed genes by conventional and real-time RT-PCR.

Laser-Capture Microdissection: Refining Estimates of the Quantity and
Distribution of Latent Herpes Simplex Virus 1 and Varicella-Zoster
Virus DNA in Human Trigeminal Ganglia at the Single-Cell Level

Kening Wang,* Tsz Y. Lau, Melissa Morales, Erik K. Mont,† and Stephen E. Straus
Medical Virology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and
Infectious Diseases, Bethesda, Maryland
There remains uncertainty and some controversy about the percentages and types of cells in human sensory nerve ganglia that harbor latent herpes simplex virus 1 (HSV-1) and varicella-zoster virus (VZV) DNA. We developed and validated laser-capture microdissection and real-time PCR (LCM/PCR) assays for the presence and copy numbers of HSV-1 gG and VZV gene 62 sequences in single cells recovered from sections of human trigeminal ganglia (TG) obtained at autopsy. Among 970 individual sensory neurons from five subjects, 2.0 to 10.5% were positive for HSV-1 DNA, with a median of 11.3 copies/positive cell, compared with 0.2 to 1.5% of neurons found to be positive by in situ hybridization (ISH) for HSV-1 latency-associated transcripts (LAT), the classical surrogate marker for HSV latency. This indicates a more pervasive latent HSV-1 infection of human TG neurons than originally thought. Combined ISH/LCM/PCR assays revealed that the majority of the latently infected neurons do not accumulate LAT to detectable levels. We detected VZV DNA in 1.0 to 6.9% of individual neurons from 10 subjects. Of the total 1,722 neurons tested, 4.1% were VZV DNA positive, with a median of 6.9 viral genomes/positive cell. After removal by LCM of all visible neurons on a slide, all surrounding nonneuronal cells were harvested and assayed: 21 copies of HSV-1 DNA were detected in 5,200 nonneuronal cells, while nine VZV genomes were detected in 14,200 nonneuronal cells. These data indicate that both HSV-1 and VZV DNAs persist in human TG primarily, if not exclusively, in a moderate percentage of neuronal cells.

Analysis of connective tissues by laser capture microdissection
and reverse transcriptase-polymerase chain reaction

Robin Jacquet, Jennifer Hillyer, William J. Landis*
Department of Biochemistry and Molecular Pathology
Northeastern Ohio Universities College of Medicine, Rootstown, OH, USA

Studies of gene expression from bone, cartilage, and other tissues are complicated by the fact that their RNA, collected and pooled for analysis, often represents a wide variety of composite cells distinct in individual phenotype, age, and state of maturation. Laser capture microdissection (LCM) is a technique that allows specific cells to be isolated according to their phenotype, condition, or other marker from within such heterogeneity. As a result, this approach can yield RNA that is particular to a subset of cells comprising the total cell population of the tissue. This study reports the application of LCM to the gene expression analysis of the cartilaginous epiphyseal growth plate of normal newborn mice. The methodology utilized for this purpose has been coupled with real-time quantitative reverse transcriptase-polymerase chain reaction (QRT-PCR) to quantitate the expression of certain genes involved in growth plate development and calcification. In this paper, the approaches used for isolating and purifying RNA from phenotypically specific chondrocyte populations of the murine growth plate are detailed and illustrate and compare both qualitative and quantitative RT-PCR results. The technique will hopefully serve as a guide for the further analysis of this and other connective tissues by LCM and RT-PCR.

New quick method for isolating RNA from laser captured cells stained by
immunofluorescent immunohistochemistry; RNA suitable for direct use in
fluorogenic TaqMan one-step real-time RT-PCR

Jack M. Gallup, Kenji Kawashima, Ginger Lucero and Mark R. Ackermann
Biol. Proced. Online 2005; 7(1): 70-92.

We describe a new approach for reliably isolating one-step real-time quantitative RT-PCR-quality RNA from laser captured cells retrieved from frozen sections previously subjected to immunofluorescent immunohistochemistry (IFIHC) and subsequently subjected to fluorogenic one-step real-time RT-PCR analysis without the need for costly, timeconsuming linear amplification. One cell’s worth of RNA can now be interrogated with confidence. This approach represents an amalgam of technologies already offered commercially by Applied Biosystems, Arcturus and Invitrogen. It is the primary focus of this communication to expose the details and execution of an important new LCM RNA isolation technique, but also provide a detailed account of the IF-IHC procedure preceding RNA isolation, and provide information regarding our approach to fluorogenic one-step real-time RT-PCR in general. Experimental results shown here are meant to supplement the primary aim and are not intended to represent a complete scientific study. It is important to mention, that since LCM-RT-PCR is still far less expensive than micro-array analysis, we feel this approach to isolating RNA from LCM samples will be of continuing use to many researchers with limited budgets in the years ahead.

Quanti-Lyse:  Reliable DNA Amplification from Single Cells
Kenneth E. Pierce, John E. Rice, J. Aquiles Sanchez, and Lawrence J. Wangh
Brandeis University, Waltham, MA, USA
BioTechniques 32:1106-1111 (May 2002)

Amplification of DNA sequences from single cells via PCR is increasingly used in basic research and clinical diagnostics but remains technically difficult. We have developed a cell lysis protocol that uses an optimized proteinase K solution, named QuantiLyse, and permits reliable amplification from individual cells. This protocol was compared to other published methods by means of real-time PCR with molecular beacons. The results demonstrate that Quanti-Lyse treatment of single lymphocytes renders gene targets more available for amplification than other published proteinase K methods or lysis in water. QuantiLyse and an optimized alkaline lysis were equally effective in terms of target availability, although QuantiLyse offers greater flexibility, as it does not require neutralization and can comprise a higher percentage of the final PCR volume. Maximum gene target availability is also obtained following QuantiLyse treatment of samples containing up to 10000 cells (the largest number tested). Thus, QuantiLyse maximizes the chances that targeted DNA sequences will be available for amplification during the first cycle of PCR, thereby reducing the variability among replicate reactions as well as the likelihood of amplification failure or allele drop-out. QuantiLyse will be useful in a range of investigations aimed at gene detection in small numbers of cells.

Linear-After-The-Exponential PCR (LATE-PCR)

Talk at the 2nd Nucleic Acid Quantification Meeting in London 2003:  
by Larry Wangh

Paper:  Primer design criteria for high yields of specific single-stranded

DNA and improved real-time detection.

Kenneth E. Pierce, J. Aquiles Sanchez, John E. Rice, and Lawrence J. Wangh
PNAS, 2005, 102 (24):  8609–8614

Traditional asymmetric PCR uses conventional PCR primers at unequal concentrations to generate single-stranded DNA. Thismethod, however, is difficult to optimize, often inefficient, and tends to promote nonspecific amplification. An alternative approach,Linear-After-The-Exponential (LATE)-PCR, solves these problems by using primer pairs deliberately designed for use at unequal concentrations. The present report systematically examines the primer design parameters that affect the exponential and linear phases of LATE-PCR amplification. In particular, we investigated how altering the concentration-adjusted melting temperature (Tm) of the limiting primer (Tm L) relative to that of the excess primer (Tm X) affects both amplification efficiency and specificity during the exponential phase of LATE-PCR. The highest reaction efficiency and specificity were observed when Tm LTm X>5°C. We also investigated how altering Tm X relative to the higher Tm of the double-stranded amplicon (Tm A) affects the rate and extent of linear amplification. Excess primers with Tm X closer to Tm A yielded higher rates of linear amplification and stronger signals from a hybridization probe. These design criteria maximize the yield of specific single-stranded DNA products and make LATE-PCR more robust and easier to implement. The conclusions were validated by using primer pairs that amplify sequences within the cystic fibrosis transmembrane regulator (CFTR) gene, mutations of which are responsible for cystic fibrosis.