Single-cell Gene Expression Profiling Research Articles

Single-cell gene expression profiling reveals functional heterogeneity of undifferentiated human epidermal cells

Human epidermal stem cells express high levels of β1 integrins, delta-like 1 (DLL1) and the EGFR antagonist LRIG1. However, there is cell-to-cell variation in the relative abundance of DLL1 and LRIG1 mRNA transcripts. Single-cell global gene expression profiling showed that undifferentiated cells fell into two clusters delineated by expression of DLL1 and its binding partner syntenin. The DLL1+ cluster had elevated expression of genes associated with endocytosis, integrin-mediated adhesion and receptor tyrosine kinase signalling. Differentially expressed genes were not independently regulated, as overexpression of DLL1 alone or together with LRIG1 led to the upregulation of other genes in the DLL1+ cluster. Overexpression of DLL1 and LRIG1 resulted in enhanced extracellular matrix adhesion and increased caveolin-dependent EGFR endocytosis. Further characterisation of CD46, one of the genes upregulated in the DLL1+ cluster, revealed it to be a novel cell surface marker of human epidermal stem cells. Cells with high endogenous levels of CD46 expressed high levels of β1 integrin and DLL1 and were highly adhesive and clonogenic. Knockdown of CD46 decreased proliferative potential and β1 integrin-mediated adhesion. Thus, the previously unknown heterogeneity revealed by our studies results in differences in the interaction of undifferentiated basal keratinocytes with their environment.

The added value of single-cell gene expression profiling

Cells are the basic unit of life and they have remarkable abilities to respond individually as well as in concert to internal and external stimuli in a specific manner. Studying complex tissues and whole organs requires understanding of cell heterogeneity and responses to stimuli at the single-cell level. In this review, we discuss the potential of single-cell gene expression profiling, focusing on data analysis and biological interpretation. We exemplify several aspects of the added value of single-cell analysis by comparing the same experimental data at both single-cell and cell population level. Data normalization and handling of missing data are two important steps in data analysis that are performed differently at single-cell level compared with cell population level. Furthermore, we discuss how single-cell gene expression data can be viewed and how subpopulations of cells can be identified and characterized.

Expression of Pluripotency and Oocyte-Related Genes in Single Putative Stem Cells from Human Adult Ovarian Surface Epithelium CulturedIn Vitroin the Presence of Follicular Fluid

The aim of this study was to trigger the expression of genes related to oocytes in putative ovarian stem cells scraped from the ovarian surface epithelium of women with premature ovarian failure and cultured in vitro in the presence of follicular fluid, rich in substances for oocyte growth and maturation. Ovarian surface epithelium was scraped and cell cultures were set up by scrapings in five women with nonfunctional ovaries and with no naturally present mature follicles or oocytes. In the presence of donated follicular fluid putative stem cells grew and developed into primitive oocyte-like cells. A detailed single-cell gene expression profiling was performed to elucidate their genetic status in comparison to human embryonic stem cells, oocytes, and somatic fibroblasts. The ovarian cell cultures depleted/converted reproductive hormones from the culture medium. Estradiol alone or together with other substances may be involved in development of these primitive oocyte-like cells. The majority of primitive oocyte-like cells was mononuclear and expressed several genes related to pluripotency and oocytes, including genes related to meiosis, although they did not express some important oocyte-specific genes. Our work reveals the presence of putative stem cells in the ovarian surface epithelium of women with premature ovarian failure.

Single cell gene expression profiling of cortical osteoblast lineage cells

In tissues with complex architectures such as bone, it is often difficult to purify and characterize specific cell types via molecular profiling. Single cell gene expression profiling is an emerging technology useful for characterizing transcriptional profiles of individual cells isolated from heterogeneous populations. In this study we describe a novel procedure for the isolation and characterization of gene expression profiles of single osteoblast lineage cells derived from cortical bone. Mixed populations of different cell types were isolated from adult long bones of C57BL/6J mice by enzymatic digestion, and subsequently subjected to FACS to purify and characterize osteoblast lineage cells via a selection strategy using antibodies against CD31, CD45, and alkaline phosphatase (AP), specific for mature osteoblasts. The purified individual osteoblast lineage cells were then profiled at the single cell level via nanofluidic PCR. This method permits robust gene expression profiling on single osteoblast lineage cells derived from mature bone, potentially from anatomically distinct sites. In conjunction with this technique, we have also shown that it is possible to carry out single cell profiling on cells purified from fixed and frozen bone samples without compromising the gene expression signal. The latter finding means the technique can be extended to biopsies of bone from diseased individuals. Our approach for single cell expression profiling provides a new dimension to the transcriptional profile of the primary osteoblast lineage population in vivo, and has the capacity to greatly expand our understanding of how these cells may function in vivo under normal and diseased states.

IS5-1 - Identification and Characterization of Acute Myeloid Leukemia-Stem Cells by Single-Cell Gene-Expression Profile

ABSTRACT While the identification of cancer stem cells as therapeutic targets is now actively being pursued in a variety of human malignancies, leukemic stem cells (LSCs) in acute myeloid leukemia (AML) are a paradigm of such a strategy. However, significant improvements in outcome based on these insights have not been forthcoming, because the molecular basis to distinguish the properties of LSCs from those of normal hematopoietic stem cells (HSCs) remains largely unknown. Meanwhile, current advances in single-cell gene profiling can provide definitive evidence regarding the conversion of one cell type into another at a high level of resolution. To characterize biological subtypes of LSCs in AML, in this study, we systematically analyzed the cDNA profiles of a large number of single LSCs. We first carried out the comparative DNA microarray analysis with primary leukemic cells and reconstituted cells in xenograft, and extracted 22 intrinsic genes from 5,599 genes, of which expression was significantly up-regulated in reconstituted cells, as the markers of high grade, aggressive AML. Among them, Evi1 and MN1, both previously identified potential poor prognostic factors in AML, were included. Next, we isolated BM CD34 + 38- LSCs from refractory AML patients, randomly picked up single cells, and amplified a total of 96 single-cell cDNA samples from each patient, as well as CD34 + 38- cells derived from a healthy volunteer to obtain information from normal HSCs. By analyzing expression-patterning of the 22 identified genes in each cell, we have identified a set of genes, of which expression pattern was significantly correlated with that of Evi1. This correlation was not observed in their normal counterparts, indicating that it was specific for AML LSCs. Furthermore, in one case, who developed AML from myelodysplastic syndrome (MDS), the hierarchical cluster based on the molecular signatures was identified only in LSCs at AML stage, but not at MDS. These results suggest that single-cell gene-expression profiling would allows us to classify AML-LSCs and provide new insights into functional properties of LSCs. Currently, we are comprehensively evaluating the expression of surface molecules on AML LSCs, and would like to disclose the clinical practicality of this methodology in our presentation.

Simultaneous Coexpression of Memory-related and Effector-related Genes by Individual Human CD8 T Cells Depends on Antigen Specificity and Differentiation

Phenotypic and functional cell properties are usually analyzed at the level of defined cell populations but not single cells. Yet, large differences between individual cells may have important functional consequences. It is likely that T-cell-mediated immunity depends on the polyfunctionality of individual T cells, rather than the sum of functions of responding T-cell subpopulations. We performed highly sensitive single-cell gene expression profiling, allowing the direct ex vivo characterization of individual virus-specific and tumor-specific T cells from healthy donors and melanoma patients. We have previously shown that vaccination with the natural tumor peptide Melan-A-induced T cells with superior effector functions as compared with vaccination with the analog peptide optimized for enhanced HLA-A*0201 binding. Here we found that natural peptide vaccination induced tumor-reactive CD8 T cells with frequent coexpression of both memory/homing-associated genes (CD27, IL7R, EOMES, CXCR3, and CCR5) and effector-related genes (IFNG, KLRD1, PRF1, and GZMB), comparable with protective Epstein-Barr virus-specific and cytomegalovirus-specific T cells. In contrast, memory/homing-associated and effector-associated genes were less frequently coexpressed after vaccination with the analog peptide. Remarkably, these findings reveal a previously unknown level of gene expression diversity among vaccine-specific and virus-specific T cells with the simultaneous coexpression of multiple memory/homing-related and effector-related genes by the same cell. Such broad functional gene expression signatures within antigen-specific T cells may be critical for mounting efficient responses to pathogens or tumors. In summary, direct ex vivo high-resolution molecular characterization of individual T cells provides key insights into the processes shaping the functional properties of tumor-specific and virus-specific T cells.

Quantitative single-cell ion-channel gene expression profiling through an improved qRT-PCR technique combined with whole cell patch clamp

Cellular excitability originates from a concerted action of different ion channels. The genomic diversity of ion channels (over 100 different genes) underlies the functional diversity of neurons in the central nervous system (CNS) and even within a specific type of neurons large differences in channel expression have been observed. Patch-clamp is a powerful technique to study the electrophysiology of excitability at the single cell level, allowing exploration of cell-to-cell variability. Only a few attempts have been made to link electrophysiological profiling to mRNA transcript levels and most suffered from experimental noise precluding conclusive quantitative correlations. Here we describe a refinement to the technique that combines patch-clamp analysis with quantitative real-time (qRT) PCR at the single cell level. Hereto the expression of a housekeeping gene was used to normalize for cell-to-cell variability in mRNA isolation and the subsequent processing steps for performing qRT-PCR. However, the mRNA yield from a single cell was insufficient for performing a valid qRT-PCR assay; this was resolved by including a RNA amplification step. The technique was validated on a stable Ltk− cell line expressing the Kv2.1 channel and on embryonic dorsal root ganglion (DRG) cells probing for the expression of Kv2.1. Current density and transcript quantity displayed a clear correlation when the qRT-PCR assay was done in twofold and the data normalized to the transcript level of the housekeeping gene GAPD. Without this normalization no significant correlation was obtained. This improved technique should prove very valuable for studying the molecular background of diversity in cellular excitability.

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.

Single Cell Transcriptional Profiling of Adult Mouse Cardiomyocytes

While numerous studies have examined gene expression changes from homogenates of heart tissue, this prevents studying the inherent stochastic variation between cells within a tissue. Isolation of pure cardiomyocyte populations through a collagenase perfusion of mouse hearts facilitates the generation of single cell microarrays for whole transcriptome gene expression, or qPCR of specific targets using nanofluidic arrays. We describe here a procedure to examine single cell gene expression profiles of cardiomyocytes isolated from the heart. This paradigm allows for the evaluation of metrics of interest which are not reliant on the mean (for example variance between cells within a tissue) which is not possible when using conventional whole tissue workflows for the evaluation of gene expression (Figure 1). We have achieved robust amplification of the single cell transcriptome yielding micrograms of double stranded cDNA that facilitates the use of microarrays on individual cells. In the procedure we describe the use of NimbleGen arrays which were selected for their ease of use and ability to customize their design. Alternatively, a reverse transcriptase - specific target amplification (RT-STA) reaction, allows for qPCR of hundreds of targets by nanofluidic PCR. Using either of these approaches, it is possible to examine the variability of expression between cells, as well as examining expression profiles of rare cell types from within a tissue. Overall, the single cell gene expression approach allows for the generation of data that can potentially identify idiosyncratic expression profiles that are typically averaged out when examining expression of millions of cells from typical homogenates generated from whole tissues.

Single Cell Transcriptional Profiling of Adult Mouse Cardiomyocytes

While numerous studies have examined gene expression changes from homogenates of heart tissue, this prevents studying the inherent stochastic variation between cells within a tissue. Isolation of pure cardiomyocyte populations through a collagenase perfusion of mouse hearts facilitates the generation of single cell microarrays for whole transcriptome gene expression, or qPCR of specific targets using nanofluidic arrays. We describe here a procedure to examine single cell gene expression profiles of cardiomyocytes isolated from the heart. This paradigm allows for the evaluation of metrics of interest which are not reliant on the mean (for example variance between cells within a tissue) which is not possible when using conventional whole tissue workflows for the evaluation of gene expression (Figure 1). We have achieved robust amplification of the single cell transcriptome yielding micrograms of double stranded cDNA that facilitates the use of microarrays on individual cells. In the procedure we describe the use of NimbleGen arrays which were selected for their ease of use and ability to customize their design. Alternatively, a reverse transcriptase - specific target amplification (RT-STA) reaction, allows for qPCR of hundreds of targets by nanofluidic PCR. Using either of these approaches, it is possible to examine the variability of expression between cells, as well as examining expression profiles of rare cell types from within a tissue. Overall, the single cell gene expression approach allows for the generation of data that can potentially identify idiosyncratic expression profiles that are typically averaged out when examining expression of millions of cells from typical homogenates generated from whole tissues.

Rac1b Increases with Progressive Tau Pathology within Cholinergic Nucleus Basalis Neurons in Alzheimer's Disease

Cholinergic basal forebrain (CBF) nucleus basalis (NB) neurons display neurofibrillary tangles (NFTs) during Alzheimer's disease (AD) progression, yet the mechanisms underlying this selective vulnerability are currently unclear. Rac1, a member of the Rho family of GTPases, may interact with the proapoptotic pan-neurotrophin receptor p75(NTR) to induce neuronal cytoskeletal abnormalities in AD NB neurons. Herein, we examined the expression of Rac1b, a constitutively active splice variant of Rac1, in NB cholinergic neurons during AD progression. CBF tissues harvested from people who died with a clinical diagnosis of no cognitive impairment (NCI), mild cognitive impairment, or AD were immunolabeled for both p75(NTR) and Rac1b. Rac1b appeared as cytoplasmic diffuse granules, loosely aggregated filaments, or compact spheres in p75(NTR)-positive NB neurons. Although Rac1b colocalized with tau cytoskeletal markers, the percentage of p75(NTR)-immunoreactive neurons expressing Rac1b was significantly increased only in AD compared with both mild cognitive impairment and NCI. Furthermore, single-cell gene expression profiling with custom-designed microarrays showed down-regulation of caveolin 2, GNB4, and lipase A in AD Rac1b-positive/p75(NTR)-labeled NB neurons compared with Rac1b-negative/p75(NTR)-positive perikarya in NCI. These proteins are involved in Rac1 pathway/cell cycle progression and lipid metabolism. These data suggest that Rac1b expression acts as a modulator or transducer of various signaling pathways that lead to NFT formation and membrane dysfunction in a subgroup of CBF NB neurons in AD.

Blimp1 Expression Predicts Embryonic Stem Cell Development In Vitro

Despite recent critical insights into the pluripotent state of embryonic stem cells (ESCs), there is little agreement over the inaugural and subsequent steps leading to its generation [1-4]. Here we show that inner cell mass (ICM)-generated cells expressing Blimp1, a key transcriptional repressor of the somatic program during germ cell specification [5, 6], emerge on day 2 of blastocyst culture. Single-cell gene expression profiling indicated that many of these Blimp1-positive cells coexpress other genes typically associated with early germ cell specification. When genetically traced in vitro, these cells acquired properties normally associated with primordial germ cells. Importantly, fate-mapping experiments revealed that ESCs commonly arise from Blimp1-positive precursors; indeed, prospective sorting of such cells from ICM outgrowths increased the rate of ESC derivation more than 9-fold. Finally, using genetic ablation or distinct small molecules [7, 8], we show that epiblast cells can become ESCs without first acquiring Blimp1 positivity. Our findings suggest that the germ cell-like state is facultative for the stabilization of pluripotency in vitro. Thus, the association of Blimp1 expression with ESC development furthers understanding of how the pluripotent state of these cells is established in vitro and suggests a means to enhance the generation of new stem cell lines from blastocysts.

Single-cell gene-expression profiling and its potential diagnostic applications

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

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.

Single Cell Gene Expression Profiling of Adult Murine Colon Provides Novel Insight Into Both the Origin of Stem Cells and Their Supportive Cell Type

Single Cell Gene Expression Profiling of Adult Murine Colon Provides Novel Insight Into Both the Origin of Stem Cells and Their Supportive Cell Type

Single-cell gene-expression profiling reveals qualitatively distinct CD8 T cells elicited by different gene-based vaccines

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

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 gene profiling analysis of human regulatory T cell subsets

Negative regulation of the immune system is of critical importance to prevent pathology. This level of regulation is compromised in autoimmunity and graft-versus-host disease, a life-threatening complication of hematopoietic stem cell transplantation. CD4+CD25+FOXP3+ regulatory T cells (Treg) are potent suppressors of these adverse immune reactions. Treg also play critical roles in the maintenance self-tolerance and the control of immune homeostasis. Recent reports have suggested that human Treg cells may not be a homogenous cell population. The aim of this study was to identify and characterize human Treg sub-populations. Treg subpopulations were isolated by cell sorting and characterized by immuno-phenotyping, functional assays and gene expression profiling. Single-cell gene expression profiling was performed by qRT-PCR using BioMark technology. We have identified three different subsets of Treg in human peripheral blood: CD25hiFOXP3hiCD127-CD45RA-HLADR+ (“activated” Treg), CD25hiFOXP3intCD45RA-HLADR- (“memory” Treg) and CD25hiFOXP3intCD127-CD45RA+HLADR- (“naive” Treg). We noted substantial differences in the expression of several Treg markers, such as FOXP3 and CTLA4, in the three subsets. Gene expression profiling combined with global pathway analysis revealed clearly distinct immune signatures. In particular, we found that memory Treg, but not naive or activated Treg, expressed transcripts encoding cytokines such as IL-17A, IL-22, IFN-γ, IL-10, and IL-4. Despite their heterogeneity, all three human Treg subsets suppressed the proliferation of effector cells in vitro and are already present at birth, although in different proportions. Single-cell gene expression profiling revealed substantial heterogeneity within the three Treg subsets, in particular within the memory Treg population. Of note, cytokine-expressing memory Treg did not downregulate FOXP3 and other Treg marker molecules. Current work addresses a potential “plasticity” and the ontogeny of this cell population. In conclusion, our data revealed a striking heterogeneity of the human Treg compartment, indicating that Treg may use multiple mechanisms to exert their immunoregulatory functions.

Single-cell analysis techniques reveal a striking heterogeneity of human CD4+ T cell subsets

Distinct CD4+ T cell subsets are necessary for efficient immune responses against various pathogens. Among these, Th17 cells play a critical role in mucosal immunity. On the other hand, Th17 cells are pathogenic in several autoimmune disease models. In addition to IL-17A, Th17 cells also produce the IL-10-related cytokine IL-22. However, recent reports have suggested that human IL-22-producing CD4+ T cells may represent a distinct T helper cell subset indicating an unexpected level of heterogeneity of CD4+ T cell “lineages”. The goal of this study was determine the heterogeneity of inflammatory human CD4+ T cell subsets using single-cell techniques. Individual IL-17 or IFN-g-producing cells were isolated using cytokine secretion assays (CSA) and single-cell sorting. Single-cell gene expression profiling was performed by qRT-PCR using BioMark technology. We first determined which human CD4+ T cell populations secrete IL-17, IL-22, and IFN-g. Analysis of cytokine production at the single cell level revealed that only a small proportion of IL-22-producing cells also produced IL-17, whereas the major IL-22-secreting cell populations were a subset of Th1 cells and “Th22” cells that produce neither IL-17 nor IFN-γ. Finally, we identified a small population of CD4+ T cell producing the 3 cytokines. To define the molecular basis for the observed heterogeneity of inflammatory T cell subsets, we isolated individual IL-17A and IFN-g-producing CD4+ T cells using CSA and analyzed the expression of 48 “marker” genes for Th1, Th2, and Th17 subsets. Hierarchical clustering revealed that the gene expression profiles of Th1 and Th17 cells are distinct at the single-cell level. However, we observed large differences in the expression levels and a remarkable heterogeneity of the expression of marker genes for individual Th1 and Th17 cells. Our data reveal a striking heterogeneity of gene expression within inflammatory T cell populations, which may provide an explanation for the diverse functions of CD4+ T cell subsets in orchestrating immune responses.

P119. Properties of neocortical progenitor cells along developmental stages as revealed by single cell gene expression profiles

In mammalian cerebral cortex, neural progenitor cells change their cytogenetic behavior dynamically as development proceeds: while progenitors in early embryonic days mainly generate two progenitor cells in a symmetric manner, those in the middle stage give rise to two different types of daughters in an asymmetric manner (i.e., a stem-like daughter cell and a daughter cell to soon proceed to differentiation). To understand how this stage-dependent cytogenesis is achieved, we sought to identify genes that are expressed by cortical progenitor cells in a temporally regulated manner. We first compared the gene expression profiles of progenitor cells isolated from mouse cortex at E11, E14 and E16 using the single-cell cDNA amplification method followed by microarray analysis. Single-cell gene expression profiles could classify the neocortical progenitor cells into the apical (stem-like) progenitors and the basal (non-stem-like) progenitors at all developmental stages examined. Next, we performed the unsupervised principal component analysis (PCA) of all stages apical progenitor cells, found that the expression pattern of E11 apical progenitors is distinct from that of E14 apical progenitors. This result suggests that apical progenitors may change their property between E11 and E14. Based on these results, we identified a set of genes whose expression increases or decreases during this E11–E14 period. To ask whether these genes are involved in the stage-dependent change of cytogenesis pattern (from symmetric or purely proliferative to asymmetric or more differentiating), we are now doing “heterochronic” in utero erectroporation experiments. For example, a gene that is normally expressed strongly by E14 apical progenitors but not by E11 apical progenitors is artificially expressed in the cortical wall at E10–E11.