Single-cell gene expression profiling using reverse transcription quantitative real-time PCR

Patch-clamp recordings and calcium imaging followed by single-cell PCR reveal the developmental profile of 13 genes in iPSC-derived human neurons

Molecular genetic studies are typically performed on homogenized biological samples, resulting in contamination from non-neuronal cells. To improve expression profiling of neurons we combined patch recordings with single-cell PCR. Two iPSC lines (healthy subject and 22q11.2 deletion) were differentiated into neurons. Patch electrode recordings were performed on 229 human cells from Day-13 to Day-88, followed by capture and single-cell PCR for 13 genes: ACTB, HPRT, vGLUT1, βTUBIII, COMT, DISC1, GAD1, PAX6, DTNBP1, ERBB4, FOXP1, FOXP2, and GIRK2. Neurons derived from both iPSC lines expressed βTUBIII, fired action potentials, and experienced spontaneous depolarizations (UP states) ~2 weeks before vGLUT1, GAD1 and GIRK2 appeared. Multisite calcium imaging revealed that these UP states were not synchronized among hESC-H9-derived neurons. The expression of FOXP1, FOXP2 and vGLUT1 was lost after 50 days in culture, in contrast to other continuously expressed genes. When gene expression was combined with electrophysiology, two subsets of genes were apparent; those irrelevant to spontaneous depolarizations (including vGLUT1, GIRK2, FOXP2 and DISC1) and those associated with spontaneous depolarizations (GAD1 and ERBB4). The results demonstrate that in the earliest stages of neuron development, it is useful to combine genetic analysis with physiological characterizations, on a cell-to-cell basis.

Single cell gene expression analysis of pluripotent stem cells

Analyzing gene expression profiles from cells en masse provides an average profile for the population which may obscure differences in individual cells. Using an optimized workflow for qRT-PCR, gene expression profiles of undifferentiated pluripotent stem cells reveal distinct gene expression profiles for individual cells, and a large expression level range of almost every gene. Importantly, this technique allows for the identification and characterization of small subpopulations.

Heterogeneity of astrocytes: from development to injury - single cell gene expression

Astrocytes perform control and regulatory functions in the central nervous system; heterogeneity among them is still a matter of debate due to limited knowledge of their gene expression profiles and functional diversity. To unravel astrocyte heterogeneity during postnatal development and after focal cerebral ischemia, we employed single-cell gene expression profiling in acutely isolated cortical GFAP/EGFP-positive cells. Using a microfluidic qPCR platform, we profiled 47 genes encoding glial markers and ion channels/transporters/receptors participating in maintaining K⁺ and glutamate homeostasis per cell. Self-organizing maps and principal component analyses revealed three subpopulations within 10–50 days of postnatal development (P10–P50). The first subpopulation, mainly immature glia from P10, was characterized by high transcriptional activity of all studied genes, including polydendrocytic markers. The second subpopulation (mostly from P20) was characterized by low gene transcript levels, while the third subpopulation encompassed mature astrocytes (mainly from P30, P50). Within 14 days after ischemia (D3, D7, D14), additional astrocytic subpopulations were identified: resting glia (mostly from P50 and D3), transcriptionally active early reactive glia (mainly from D7) and permanent reactive glia (solely from D14). Following focal cerebral ischemia, reactive astrocytes underwent pronounced changes in the expression of aquaporins, nonspecific cationic and potassium channels, glutamate receptors and reactive astrocyte markers.

Rapid, quantitative, reverse transcription PCR in a polymer microfluidic chip

Quantitative PCR (qPCR) techniques have become invaluable, high-throughput tools to study gene expression. However, the need to measure gene expression patterns quickly and affordably, useful for applications such as stem cell biomanufacturing requiring real-time observation and control, has not been adequately met by rapid qPCR instrumentation to date. We report a reverse transcription, microfluidic qPCR system and its application to DNA and RNA amplification measurement. In the system, an environmental control fixture provides mechanical and thermal repeatability for an infrared laser to achieve both accurate and precise open-loop temperature control of 1 μl reaction volumes in a low-cost polymer microfluidic chip with concurrent fluorescence imaging. We have used this system to amplify serial dilutions of λ-phage DNA (10(5)-10(7) starting copies) and RNA transcripts from the GAPDH housekeeping gene (5.45 ng total mouse embryonic stem cell RNA) and measured associated standard curves, efficiency (57%), repeatability (~1 cycle threshold), melting curves, and specificity. This microfluidic qRT-PCR system offers a practical approach to rapid analysis (~1 h), combining the cost benefits of small reagent volumes with the simplicity of disposable polymer microchips and easy setup.

Quantitative PCR analysis of DNA, RNAs, and proteins in the same single cell

BACKGROUND

The single cell represents the basic unit of all organisms. Most investigations have been performed on large cell populations, but understanding cell dynamics and heterogeneity requires single-cell analysis. Current methods for single-cell analysis generally can detect only one class of analytes.

METHODS

Reverse transcription and the proximity ligation assay were coupled with quantitative PCR and used to quantify any combination of DNA, mRNAs, microRNAs (miRNAs), noncoding RNAs (ncRNAs), and proteins from the same single cell. The method was used on transiently transfected human cells to determine the intracellular concentrations of plasmids, their transcribed mRNAs, translated proteins, and downstream RNA targets.

RESULTS

We developed a whole-cell lysis buffer to release unfractionated DNA, RNA, and proteins that would not degrade any detectable analyte or inhibit the assay. The dynamic range, analytical sensitivity, and specificity for quantifying DNA, mRNAs, miRNAs, ncRNAs, and proteins were shown to be accurate down to the single-cell level. Correlation studies revealed that the intracellular concentrations of plasmids and their transcribed mRNAs were correlated only moderately with translated protein concentrations (Spearman correlation coefficient, 0.37 and 0.31, respectively; P < 0.01). In addition, an ectopically expressed gene affected the correlations between analytes and this gene, which is related to gene regulation.

CONCLUSIONS

This method is compatible with most cell-sampling approaches, and generates output for the same parameter for all measured analytes, a feature facilitating comparative data analysis. This approach should open up new avenues in molecular diagnostics for detailed correlation studies of multiple and different classes of analytes at the single-cell level.

RT-qPCR work-flow for single-cell data analysis

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.

Characterization of the rainbow trout egg microRNA transcriptome

MicroRNAs (miRNAs) are a class of endogenous small non-coding RNA molecules that regulate post-transcriptional expression of target genes and play important roles in animal development. The objectives of this study were to characterize the egg miRNA transcriptome and identify novel egg-predominant miRNAs in rainbow trout. Small RNAs isolated from mature unfertilized rainbow trout eggs were subjected to deep sequencing using an Illumina Genome Analyzer. The massive sequencing produced 24,621,741 quality reads, among which, 266 known miRNAs were identified and 230 putatively novel miRNAs were predicted. The most abundantly known miRNAs are let-7 and miR-21, accounting for 24.06% and 18.71% of the known miRNAs, respectively. Other known miRNAs which are abundantly present in eggs include miR-24, miR-202, miR-148, miR-30, miR-10, miR-146, miR-25, and miR-143. Real time PCR analysis using cDNAs derived from 10 tissues validated 87 out of 90 selected putative miRNAs and identified three novel miRNAs predominantly expressed in rainbow trout eggs. Each of these novel egg-predominant miRNAs is predicted to target a significant number of genes, most of which are significantly down-regulated in naturally ovulated rainbow trout eggs based on analysis of publicly available microarray data sets. Quantitative real time PCR analysis also demonstrated low expression of a selected number of target genes in eggs relative to liver and muscle tissues. This study represents the first complete survey of miRNAs in fish eggs and provides a starting point for future studies aimed at understanding the roles of miRNAs in controlling egg quality and early embryogenesis in rainbow trout.

Distinct gene expression signatures in human embryonic stem cells differentiated towards definitive endoderm at single-cell level

Characterization of directed differentiation of pluripotent stem cells towards therapeutically relevant cell types, including pancreatic beta-cells and hepatocytes, depends on molecular markers and assays that resolve the signature of individual cells. Pancreas and liver both have a common origin of anterior definitive endoderm (DE). Here, we differentiated human embryonic stem cells towards DE using three different activin A based treatments. Differentiation efficiencies were evaluated by gene expression profiling over time at cell population level. A panel of key markers was used to study DE formation. Final DE differentiation was also analyzed with immunocytochemistry and single-cell gene expression profiling. We found that cells treated with activin A in combination with sodium butyrate and B27 serum-free supplement medium generated the most mature DE cells. Cell population studies were useful to monitor the temporal expression of genes involved in primitive streak formation and endoderm formation, while single-cell analysis allowed us to study cell culture heterogeneity and fingerprint individual cells. In addition, single-cell analysis revealed distinct gene expression patterns for the three activin A based protocols applied. Our data provide novel insights in DE gene expression at the cellular level of in vitro differentiated human embryonic stem cells, and illustrate the power of using single-cell gene expression profiling to study differentiation heterogeneity and to characterize cell types and subpopulations.

Microfluidic single-cell real-time PCR for comparative analysis of gene expression patterns

Single-cell quantitative real-time PCR (qRT-PCR) combined with high-throughput arrays allows the analysis of gene expression profiles at a molecular level in approximately 11 h after cell sample collection. We present here a high-content microfluidic real-time platform as a powerful tool for comparatively investigating the regulation of developmental processes in single cells. This approach overcomes the limitations involving heterogeneous cell populations and sample amounts, and may shed light on differential regulation of gene expression in normal versus disease-related contexts. Furthermore, high-throughput single-cell qRT-PCR provides a standardized, comparative assay for in-depth analysis of the mechanisms underlying human pluripotent stem cell self-renewal and differentiation.

Highly parallel genome-wide expression analysis of single mammalian cells

BACKGROUND

We have developed a high-throughput amplification method for generating robust gene expression profiles using single cell or low RNA inputs.

METHODOLOGY/PRINCIPAL FINDINGS

The method uses tagged priming and template-switching, resulting in the incorporation of universal PCR priming sites at both ends of the synthesized cDNA for global PCR amplification. Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates. Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80). Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.

CONCLUSIONS/SIGNIFICANCE

In summary, our method facilitates whole-genome gene expression profiling in contexts where starting material is extremely limiting, particularly in areas such as the study of progenitor cells in early development and tumor stem cell biology.

Single-cell and regional gene expression analysis in Alzheimer's disease

The clinical manifestations of Alzheimer's disease (AD) are secondary to the substantial loss of cortical neurons. To be effective, neuroprotective strategies will need to target the primary pathogenic mechanisms of AD prior to cell loss. The differences between neurons are largely determined by their specific repertoire of mRNAs. Thus, transcriptomic analyses that do not assume a priori etiological hypotheses are potentially powerful tools that can be used to understand the pathogenesis of complex diseases, including AD. The human brain comprises thousands of different cell types of both neuronal and non-neuronal origins. Information about individual cell-type-specific gene expression patterns will allow for a better understanding of the mechanisms that govern the progression of AD, which may lead to new therapeutic targets for prevention and treatment of the disease. This review provides an overview of the current technologies in use and the developments for single-cell extraction and transcriptome analysis. Recent transcriptome profiling studies on individual AD-afflicted brain cells are also discussed.

Analytical technologies for integrated single-cell analysis of human immune responses

The immune system is a network of cells in which the constitutive members interact through dense and sometimes overlapping connections. The extreme complexity of this network poses a significant challenge for monitoring pathological conditions (e.g., food allergies, autoimmunity, and other chronic inflammatory diseases) and for discovering robust signatures of immunological responses that correlate with or predict the efficacy of interventions. The diversity among immune cells found in clinical samples (variations in cellular functions, lineages, and clonotypic breadth) requires approaches for monitoring immune responses with single-cell resolution.In this chapter, we present an engineering approach for integrated single-cell analysis that uses interchangeable modular operations to provide a comprehensive characterization of the phenotypic, functional, and genetic variations for individual cells. We focus on the use of microfabricated devices to isolate and interrogate single cells, and on the analytical components that enable subsequent detection, correlation, and interpretation of multidimensional sets of data. We discuss specific challenges and opportunities in the realization of this concept, and review two examples where it has been implemented. The presented approach should provide a basis for the design and implementation of nonconventional bioanalytical processes for studying specific responses of an immune system.

Multiplexed quantification of nucleic acids with large dynamic range using multivolume digital RT-PCR on a rotational SlipChip tested with HIV and hepatitis C viral load

In this paper, we are working toward a problem of great importance to global health: determination of viral HIV and hepatitis C (HCV) loads under point-of-care and resource limited settings. While antiretroviral treatments are becoming widely available, viral load must be evaluated at regular intervals to prevent the spread of drug resistance and requires a quantitative measurement of RNA concentration over a wide dynamic range (from 50 up to 10(6) molecules/mL for HIV and up to 10(8) molecules/mL for HCV). "Digital" single molecule measurements are attractive for quantification, but the dynamic range of such systems is typically limited or requires excessive numbers of compartments. Here we designed and tested two microfluidic rotational SlipChips to perform multivolume digital RT-PCR (MV digital RT-PCR) experiments with large and tunable dynamic range. These designs were characterized using synthetic control RNA and validated with HIV viral RNA and HCV control viral RNA. The first design contained 160 wells of each of four volumes (125 nL, 25 nL, 5 nL, and 1 nL) to achieve a dynamic range of 5.2 × 10(2) to 4.0 × 10(6) molecules/mL at 3-fold resolution. The second design tested the flexibility of this approach, and further expanded it to allow for multiplexing while maintaining a large dynamic range by adding additional wells with volumes of 0.2 nL and 625 nL and dividing the SlipChip into five regions to analyze five samples each at a dynamic range of 1.8 × 10(3) to 1.2 × 10(7) molecules/mL at 3-fold resolution. No evidence of cross-contamination was observed. The multiplexed SlipChip can be used to analyze a single sample at a dynamic range of 1.7 × 10(2) to 2.0 × 10(7) molecules/mL at 3-fold resolution with limit of detection of 40 molecules/mL. HIV viral RNA purified from clinical samples were tested on the SlipChip, and viral load results were self-consistent and in good agreement with results determined using the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test. With further validation, this SlipChip should become useful to precisely quantify viral HIV and HCV RNA for high-performance diagnostics in resource-limited settings. These microfluidic designs should also be valuable for other diagnostic and research applications, including detecting rare cells and rare mutations, prenatal diagnostics, monitoring residual disease, and quantifying copy number variation and gene expression patterns. The theory for the design and analysis of multivolume digital PCR experiments is presented in other work by Kreutz et al.

Metabolic differentiation of neuronal phenotypes by single-cell capillary electrophoresis-electrospray ionization-mass spectrometry

Single-cell mass spectrometry (MS) is a rapidly emerging field in metabolic investigations. The inherent chemical complexity of most biological samples poses analytical challenges when using MS platforms to measure sample content without prior chemical separation. Here, a single-cell capillary electrophoresis (CE) system was coupled with electrospray ionization (ESI) MS to enable the simultaneous measurement of a vast array of endogenous compounds in over 50 identified and isolated large neurons from the Aplysia californica central nervous system. More than 300 distinct ion signals (m/z values) were detected from a single neuron in the positive ion mode, 140 of which were selected for chemometric data analysis. Metabolic features were evaluated among six different neuron types (B1, B2, left pleural 1 (LPl1), metacerebral cell (MCC), R2, and R15) chosen for their various physiological functions. The results indicated chemical similarities among some neuron types (B1 to B2 and LPl1 to R2) and distinctive features for others (MCC and R15 cells). The quantitative nature of the MS platform allowed the comparison of metabolite levels for specific neurons. The CE-ESI-MS approach for examination of individual nanoliter-volume cells as described herein is readily adaptable to other volume-limited samples.

Acoustic microstreaming increases the efficiency of reverse transcription reactions comprising single-cell quantities of RNA

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.

Quantification noise in single cell experiments

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.

Differentially expressed micoRNAs in human oocytes

PURPOSE

To identify differentially expressed microRNAs (miRNAs) and expression patterns of specific miRNAs during meiosis in human oocytes.

MATERIALS AND METHODS

To identify differentially expressed miRNAs, GV oocytes and MII oocytes matured at conventional FSH levels (5.5 ng/ml) were analyzed by miRNA microarray. Real-time RT-PCR was used to confirm the changed miRNAs. To validate the dynamic changes of miRNAs from GV to MII stages, oocytes were divided into four groups (#1-4), corresponding to GV oocytes, MI oocytes, MII oocytes matured in conventional FSH level and MII oocytes matured in high FSH level (2,000 ng/ml) respectively.

RESULTS

Compared with GV oocytes, MII oocytes exhibited up-regulation of 4 miRNAs (hsa-miR-193a-5p, hsa-miR-297, hsa-miR-625 and hsa-miR-602), and down-regulation of 11 miRNAs (hsa-miR-888*, hsa-miR-212, hsa-miR-662, hsa-miR-299-5p, hsa-miR-339-5p, hsa-miR-20a, hsa-miR-486-5p, hsa-miR-141*, hsa-miR-768-5p, hsa-miR-376a and hsa-miR-15a). RT-PCR analysis of hsa-miR-15a and hsa-miR-20a expression revealed concordant dynamic changes in oocytes from group 1 to group 4.

CONCLUSION(S)

Specific miRNAs in human oocytes had dynamic changes during meiosis. High-concentration FSH in IVM medium led to reverse effect on the expression of hsa-miR-15a and hsa-miR-20a.

Establishment of real-time quantitative reverse transcription polymerase chain reaction assay for transcriptional analysis of duck enteritis virus UL55 gene

BACKGROUND

Real-time quantitative reverse transcription polymerase chain reaction assay (qRT-PCR) has become the benchmark for detection and quantification of target gene expression level and been utilized increasingly in detection of viral load and therapy monitoring. The dynamic transcription variation of duck enteritis virus UL55 gene during the life cycle of duck enteritis virus in infected cells has not been reported yet.

RESULTS

The newly identified duck enteritis virus UL55 gene was amplified and cloned into pMD18-T vector after digestion to generate a recombinant plasmid pMD18-T/UL55 for the establishment of qRT-PCR as standard DNA. The results of agarose gel electrophoresis and melting curve analysis demonstrated the primers we designed for qRT-PCR were specific and available. We used β-actin as a reference gene for normalization and established two standard curves based on pMD18-T/UL55 and pMD18-T/β-actin successfully. Based on that, the transcriptional analysis of DEV UL55 gene was performed, and the result suggested the expression of UL55 mRNA was at a low level from 0 to 8 h post-infection(p.i.), then accumulated quickly since 12 h p.i. and peaked at 36 h p.i., it can be detected till 60 h p.i.. Nucleic acid inhibition test was carried out for analyzing a temporal regulation condition of DEV UL55 gene, result revealed that it was sensitive to ganciclovir. Synthesis procedures of DEV UL55 gene can be inhibited by ganciclovir.

CONCLUSIONS

The method we established in this paper can provide quantitative values reflecting the amounts of measured mRNA in samples. It's available for detection and quantification, also can be used in DEV diagnosis. The DEV UL55 gene was produced most abundantly during the late phase of replication in DEV-infected cells and the transcription of it depended on the synthesized DNA. DEV UL55 gene is a γ2 gene which occurs last and have a strict requirement for viral DNA synthesis.

Quantitative single-cell gene expression measurements of multiple genes in response to hypoxia treatment

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.

Development and applications of single-cell transcriptome analysis

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.

A quantitative comparison of cell-type-specific microarray gene expression profiling methods in the mouse brain

Expression profiling of restricted neural populations using microarrays can facilitate neuronal classification and provide insight into the molecular bases of cellular phenotypes. Due to the formidable heterogeneity of intermixed cell types that make up the brain, isolating cell types prior to microarray processing poses steep technical challenges that have been met in various ways. These methodological differences have the potential to distort cell-type-specific gene expression profiles insofar as they may insufficiently filter out contaminating mRNAs or induce aberrant cellular responses not normally present in vivo. Thus we have compared the repeatability, susceptibility to contamination from off-target cell-types, and evidence for stress-responsive gene expression of five different purification methods - Laser Capture Microdissection (LCM), Translating Ribosome Affinity Purification (TRAP), Immunopanning (PAN), Fluorescence Activated Cell Sorting (FACS), and manual sorting of fluorescently labeled cells (Manual). We found that all methods obtained comparably high levels of repeatability, however, data from LCM and TRAP showed significantly higher levels of contamination than the other methods. While PAN samples showed higher activation of apoptosis-related, stress-related and immediate early genes, samples from FACS and Manual studies, which also require dissociated cells, did not. Given that TRAP targets actively translated mRNAs, whereas other methods target all transcribed mRNAs, observed differences may also reflect translational regulation.

Defining cell populations with single-cell gene expression profiling: correlations and identification of astrocyte subpopulations

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

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.

Metabolic cycling in single yeast cells from unsynchronized steady-state populations limited on glucose or phosphate

Oscillations in patterns of expression of a large fraction of yeast genes are associated with the "metabolic cycle," usually seen only in prestarved, continuous cultures of yeast. We used FISH of mRNA in individual cells to test the hypothesis that these oscillations happen in single cells drawn from unsynchronized cultures growing exponentially in chemostats. Gene-expression data from synchronized cultures were used to predict coincident appearance of mRNAs from pairs of genes in the unsynchronized cells. Quantitative analysis of the FISH results shows that individual unsynchronized cells growing slowly because of glucose limitation or phosphate limitation show the predicted oscillations. We conclude that the yeast metabolic cycle is an intrinsic property of yeast metabolism and does not depend on either synchronization or external limitation of growth by the carbon source.

Single cell analytics: an overview

The research field of single cell analysis is rapidly expanding, driven by developments in flow cytometry, microscopy, lab-on-a-chip devices, and many other fields. The promises of these developments include deciphering cellular mechanisms and the quantification of cell-to-cell differences, ideally with spatio-temporal resolution. However, these promises are challenging as the analytical techniques have to cope with minute analyte amounts and concentrations. We formulate first these challenges and then present state-of-the-art analytical techniques available to investigate the different cellular hierarchies--from the genome to the phenome, i.e., the sum of all phenotypes.