Name: single-cell gene expression profiling using facs and qpcr with internal standards
Uploaded: 2017-02-25T14:00:00.000+00:00
Duration: 10 min 50 s
Description: Watch this Scientific Journal Video about Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards at JoVE.com

私たちは、このプロトコルの開発中に細胞選別を行うの彼女の援助のためにCCR ETIBフローサイトメトリーコアでV.カプールに感謝したいと思います。また、このプロトコルの開発中に定量PCRを行う際の援助のためにM. RaffeldとCCR LP分子診断ユニットとJ.朱とNHLBI DNA配列決定およびゲノミクスコアに感謝します。この研究は、NIHの学内プログラムによってサポートされていました。

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The authors have nothing to disclose.

我々は、培養で増殖させた接着性細胞の集団から個々の哺乳動物細胞を単離するため、各セル内の約96の遺伝子の発現をアッセイするための方法を提示しています。この方法がうまく機能するために良好な事前準備が重要です。プライマーは、単セル測定の品質を決定するように、特に興味のある転写物（1.2〜1.3ステップ）に特異的な設計およびテストプライマーペアは、時間がかかるが、?...

集団内の個々の細胞は均一な生理的刺激1、2、3、4に大幅に異なる応答を示すことができます。集団中の細胞の遺伝的変異は、応答のこの品種のための1つのメカニズムであるが、それでも細胞のクローン集団で、応答の変動性を向上させることができ、いくつかの非遺伝的要因もあります。例えば、個々のタンパク質および他の重要なシグナル伝達分子のレベルは、下流の遺伝子発現プロファイルの変化を生じる、セル単位で変化させることができます。さらに、遺伝子活性化は、バースト7,8,9あたりの転写物の比較的少数に限定することができる転写5,6の短時間のバーストで発生することができます。そのような遺伝子活性化における偶然性が大幅に生物学的応答の変動に寄与することができ、生理的刺激に応答して、微生物10におよび哺乳動物細胞1に2を選択的利点を提供することができます。変化の遺伝的および非遺伝的供給源の両方に、刺激に応答する任意の細胞の遺伝子発現プロファイルは、バルク応答の測定から得られた平均遺伝子発現プロファイルとは大きく異なっていてもよいです。個々の細胞は、刺激に応答して可変性を示す程度を決定することは、個々の細胞の単離のための技術は、目的の転写物の発現レベルを測定し、得られた発現データのコンピュータ分析を必要とします。 コストの広い範囲をカバーし、単一細胞における遺伝子発現をアッセイするためのいくつかのアプローチがあり、転写産物の数はプローブ、及び定量化の精度。例えば、単一細胞RNA-のSeqは、転写物のカバレッジと、個々の細胞の中で最も高度に発現される遺伝子のための別個の転写産物の数千を定量する能力の広い深さを提供しています。コストが減少し続けるが、しかし、このようなシーケンシングの深さに関連するコストは、法外することができます。逆に、in situハイブリダイゼーション（FISH smRNA） における単一分子RNAの蛍光は、目的の遺伝子につき合理的なコストであっても低発現遺伝子のための転写物の正確な定量を提供しています。しかしながら、標的遺伝子の少数は、このアプローチによって、所定の細胞においてアッセイすることができます。このプロトコールに記載定量的PCRベースのアッセイは、これらの技術の間の妥協点を提供します。これらのアッセイは、最大96個の細胞で一度に関心の96転写物まで定量化するために、マイクロ流体リアルタイムPCR装置を採用しています。前述の方法のそれぞれは、必要なハードウェアのコストを有しているが、任意の個々のqPCRアッセイのコストは比較的です低いです。このプロトコルは、（プロトコルADP 41、フリュー）マイクロ流体リアルタイムPCR装置の製造元が推奨する1から適応されます。 PCRベースのアプローチで各転写産物の絶対数の推定を可能にするために、我々は、複数の実験で使用できる準備標的遺伝子アンプリコンの内部統制を利用するプロトコルを拡大してきました。 この技術の一例として、MCF-7ヒト乳癌細胞において腫瘍抑制因子p53によって調節される遺伝子の発現の定量化は、11に記載されています。細胞は、DNA二本鎖切断を誘発する化学物質でチャレンジされています。以前の研究は、DNA二重鎖切断に対するp53応答は、p53レベル12の観点と異なる標的遺伝子11の活性化の両方で、個々の細胞における異質性を大いに発揮することが示されています。さらに、p53は100以上の発現を調節します細胞周期停止、アポトーシス及び老化13、14を含む多くの下流経路に関与する標的遺伝子を十分に特徴付け。各細胞におけるp53媒介性応答は、複雑かつ可変でもあるので、アプローチからシステムの利点の分析とは、約100の標的遺伝子は、以下に記載されるような個々の細胞、同時にプローブすることができます。 （例えば、単一細胞の単離および溶解のための代替方法として）わずかな変更を加えて、プロトコルは、容易に、哺乳動物の細胞型、転写、および細胞応答の広い範囲を研究するために適合させることができます。 適切な事前準備で、細胞選別および遺伝子発現測定のラウンドは、3日間にわたって、このプロトコルに従って行うことができます。 、事前に関心の転写産物を選択し、それらのtranscrからcDNAを増幅するプライマー対を識別し、検証：以下のタイミングが示唆されていますIPTSは、および標準とそれらのプライマーを用いてプライマーミックスを準備します。細胞治療の後、1日目に、収穫と逆転写および特定の標的増幅を行い、細胞を選別し、取り込まれなかったプライマーを除去するためにエキソヌクレアーゼでサンプルを扱います。 2日目、定量PCRを使用して選別した細胞上の品質管理を行います。最後に、3日目に、マイクロ流体定量PCRを使用して選別した細胞における遺伝子発現を測定します。 図1は、必要な手順をまとめたものです。

<table><tbody><tr><td>RNeasy Plus Mini Kit</td><td>Qiagen</td><td>74134</td><td></td></tr><tr><td>High Capacity cDNA Reverse Transcription Kit with RNase Inhibitor</td><td>ThermoFisher</td><td>4374966</td><td></td></tr><tr><td>Phusion High-Fidelity DNA Polymerase</td><td>New England BioLabs</td><td>M0530S</td><td></td></tr><tr><td>QIAquick Gel Extraction Kit</td><td>Qiagen</td><td>28704</td><td></td></tr><tr><td>Quant-iT High-Sensitivity dsDNA Assay Kit</td><td>ThermoFisher</td><td>Q33120&amp;nbsp;</td><td></td></tr><tr><td>2.0 ml low adhesion microcentrifuge tubes</td><td>USA Scientific</td><td>1420-2600</td><td></td></tr><tr><td>DNA Suspension Buffer</td><td>Teknova</td><td>T0221</td><td></td></tr><tr><td>Axygen 0.2 ml Maxymum Recovery Thin Wall PCR Tubes</td><td>Corning</td><td>PCR-02-L-C</td><td></td></tr><tr><td>GE 96.96 Dynamic Array DNA Binding Dye Sample &amp;amp; Assay Loading Reagent Kit</td><td>Fluidigm</td><td>100-3415</td><td></td></tr><tr><td>HyClone RPMI 1640 media</td><td>GE Healthcare Life Sciences</td><td>SH30027.01</td><td></td></tr><tr><td>Fetal Bovine Serum, Certified (US)</td><td>ThermoFisher</td><td>16000-044</td><td></td></tr><tr><td>Antibiotic-Antimycotic Solution</td><td>Corning</td><td>30-004-CI</td><td></td></tr><tr><td>Neocarzinostatin</td><td>Sigma</td><td>N9162</td><td></td></tr><tr><td>ELIMINase</td><td>Decon Labs</td><td>1101</td><td></td></tr><tr><td>SUPERase-In</td><td>ThermoFisher</td><td>AM2696</td><td></td></tr><tr><td>CellsDirect One-Step qRT-PCR Kit</td><td>ThermoFisher</td><td>11753500</td><td></td></tr><tr><td>&lt;em&gt;E. coli&lt;/em&gt; DNA</td><td>Affymetrix</td><td>14380 10 MG</td><td></td></tr><tr><td>ThermalSeal Sealing Film, Sterile</td><td>Excel Scientific</td><td>STR-THER-PLT</td><td></td></tr><tr><td>BD FACSAria IIu</td><td>BD Biosciences</td><td></td><td></td></tr><tr><td>HyClone Trypsin 0.05%</td><td>GE Healthcare Life Sciences</td><td>SH30236.01</td><td></td></tr><tr><td>PBS, 1x</td><td>Corning</td><td>21-040-CV</td><td></td></tr><tr><td>Falcon 40 &amp;micro;m Cell Strainer</td><td>Corning</td><td>352340</td><td></td></tr><tr><td>Exonuclease I</td><td>New England BioLabs</td><td>M0293S</td><td></td></tr><tr><td>SsoFast EvaGreen Supermix with Low ROX</td><td>Bio-Rad</td><td>172-5210</td><td></td></tr><tr><td>96.96 Dynamic Array IFC for Gene Expression (microfluidic qPCR chip)</td><td>Fluidigm</td><td>BMK-M-96.96</td><td></td></tr><tr><td>IFC Controller HX (loading machine)</td><td>Fluidigm</td><td></td><td></td></tr><tr><td>BioMark or BioMark HD (microfluidic qPCR machine)</td><td>Fluidigm</td><td></td><td></td></tr><tr><td>Real-Time PCR Analysis software&amp;nbsp;</td><td>Fluidigm</td><td></td><td></td></tr><tr><td>MATLAB software</td><td>MathWorks</td><td></td><td></td></tr></tbody></table>

single-cell gene expression profiling using facs and qpcr with internal standards

Gene expression measurements from bulk populations of cells can obscure the considerable transcriptomic variation of individual cells within those populations. Single-cell gene expression measurements can help assess the role of noise in gene expression, identify correlations in the expression of pairs of genes, and reveal subpopulations of cells that respond differently to a stimulus. Here, we describe a procedure to measure the expression of up to 96 genes in single mammalian cells isolated from a population growing in tissue culture. Cells are sorted into lysis buffer by fluorescence-activated cell sorting (FACS), and the mRNA species of interest are reverse-transcribed and amplified. Gene expression is then measured using a microfluidic real-time PCR machine, which performs up to 96 qPCR assays on up to 96 samples at a time. We also describe the generation and use of PCR amplicon standards to enable the estimation of the absolute number of each transcript. Compared with other methods of measuring gene expression in single cells, this approach allows for the quantification of more distinct transcripts than RNA FISH at a lower cost than RNA-Seq.

プロトコルの一般的な概要は、細胞治療、FACSによる単一細胞の単離、単一細胞溶解物からのcDNAライブラリーの生成および前増幅、単一細胞cDNAライブラリーを確認するステップを含む、 図1に示されていますソートされたウェル、および定量PCRにより遺伝子発現を測定します。 単一細胞の単離および遺伝子発?...

Watch this Scientific Journal Video about Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards at JoVE.com

内部標準を使用した FACS および qPCR を使用した単一細胞遺伝子発現プロファイリング |遺伝学 |ビデオ

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

We describe a method to sort single mammalian cells and to quantify the expression of up to 96 target genes of interest in each cell. This method includes the use of internal qPCR standards to enable the estimation of absolute transcript counts.

内部標準でFACSおよび定量PCRを用いた単一細胞遺伝子発現プロファイリング

Gene expression measurements from bulk populations of cells can obscure the considerable transcriptomic variation of individual cells within those ...

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Gene Expression

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16.4K ビュー.  National Cancer Institute. We describe a method to sort single mammalian cells and to quantify the expression of up to 96 target genes of interest in each cell. This method includes the use of internal qPCR standards to enable the estimation of absolute transcript counts.

ビデオ: Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Gene expression heterogeneity is an interesting feature to investigate in lymphoid populations. Gene expression in these cells varies during cell activation, stress, or stimulation. Single-cell multiplex gene expression enables the simultaneous assessment of tens of genes1,2,3. At the single-cell level, multiplex gene expression determines population heterogeneity4,5. It allows for the distinction of population heterogeneity by determining both the probable mix of diverse precursor stages among mature cells and also the diversity of cell responses to stimuli.
Innate lymphoid cells (ILC) have been recently described as a population of innate effectors of the immune response6,7. In this protocol, cell heterogeneity of the ILC hepatic compartment is investigated during homeostasis.
Currently, the most widely used technique to assess gene expression is RT-qPCR. This method measures gene expression only one gene at a time. Additionally, this method cannot estimate heterogeneity of gene expression, since multiple cells are needed for one test. This leads to the measurement of the average gene expression of the population. When assessing large numbers of genes, RT-qPCR becomes a time-, reagent-, and sample-consuming method. Hence, the trade-offs limit the number of genes or cell populations that can be evaluated, increasing the risk of missing the global picture.
This manuscript describes how single-cell multiplex RT-qPCR can be used to overcome these limitations. This technique has benefited from recent microfluidics technological advances1,2. Reactions occurring in multiplex RT-qPCR chips do not exceed the nanoliter-level. Hence, single-cell gene expression, as well as simultaneous multiple gene expression, can be performed in a reagent-, sample-, and cost-effective manner. It is possible to test cell gene signature heterogeneity at the clonal level between cell subsets within a population at different developmental stages or under different conditions4,5. Working on rare populations with large numbers of conditions at the single-cell level is no longer a restriction.

This protocol describes how to assess the expression of a large array of genes at the clonal level. Single-cell RT-qPCR produces highly reliable results with a strong sensitivity for hundreds of samples and genes.

レアリンパ集団の不均一性を特徴づけるためにマルチプレックスRT-qPCRのを使用した単一細胞の遺伝子発現

Gene expression heterogeneity is an interesting feature to investigate in lymphoid populations. Gene expression in these cells varies during cell ...

遺伝学

Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR

Real Time Polymerase Chain Reaction also known as quantitative PCR (q-PCR) is a widely used tool in microbial ecology to quantify gene abundances of taxonomic and functional groups in environmental samples. Used in combination with a reverse transcriptase reaction (RT-q-PCR), it can also be employed to quantify gene transcripts. q-PCR makes use of highly sensitive fluorescent detection chemistries that allow quantification of PCR amplicons during the exponential phase of the reaction. Therefore, the biases associated with &#39;end-point&#39; PCR detected in the plateau phase of the PCR reaction are avoided. A protocol to quantify bacterial 16S rRNA genes and transcripts from coastal sediments via real-time PCR is provided. First, a method for the co-extraction of DNA and RNA from coastal sediments, including the additional steps required for the preparation of DNA-free RNA, is outlined. Second, a step-by-step guide for the quantification of 16S rRNA genes and transcripts from the extracted nucleic acids via q-PCR and RT-q-PCR is outlined. This includes details for the construction of DNA and RNA standard curves. Key considerations for the use of RT-q-PCR assays in microbial ecology are included.

A protocol to quantify bacterial 16S rRNA genes and transcripts from coastal sediments via real-time PCR is provided. The methodology includes the co-extraction of DNA and RNA; preparation of DNA-free RNA; and 16S rRNA gene and transcript quantification via RT-q-PCR, including standard curve construction.

リアルタイムPCRによる沿岸堆積物および定量16SのrRNA遺伝子と転写物からの同時DNA-RNA抽出

Real Time Polymerase Chain Reaction also known as quantitative PCR (q-PCR) is a widely used tool in microbial ecology to quantify gene abundances of ...

環境学

Isolation and Characterization of Single Cells from Zebrafish Embryos

The zebrafish (Danio rerio) is a powerful model organism to study vertebrate development. Though many aspects of zebrafish embryonic development have been described at the morphological level, little is known about the molecular basis of cellular changes that occur as the organism develops. With recent advancements in microfluidics and multiplexing technologies, it is now possible to characterize gene expression in single cells. This allows for investigation of heterogeneity between individual cells of specific cell populations to identify and classify cell subtypes, characterize intermediate states that occur during cell differentiation, and explore differential cellular responses to stimuli. This study describes a protocol to isolate viable, single cells from zebrafish embryos for high throughput multiplexing assays. This method may be rapidly applied to any zebrafish embryonic cell type with fluorescent markers. An extension of this method may also be used in combination with high throughput sequencing technologies to fully characterize the transcriptome of single cells. As proof of principle, the relative abundance of cardiac differentiation markers was assessed in isolated, single cells derived from nkx2.5 positive cardiac progenitors. By evaluation of gene expression at the single cell level and at a single time point, the data support a model in which cardiac progenitors coexist with differentiating progeny. The method and work flow described here is broadly applicable to the zebrafish research community, requiring only a labeled transgenic fish line and access to microfluidics technologies.

This protocol describes a method for isolating single cells from zebrafish embryos, enriching for cells of interest, capturing zebrafish cells in microfluidic based single cell multiplex systems, and assessing gene expression from single cells.

ゼブラフィッシュ胚からの単一細胞の単離とキャラクタリゼーション

The zebrafish (Danio rerio) is a powerful model organism to study vertebrate development. Though many aspects of zebrafish embryonic development have been ...

発生生物学

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is inherently a single-cell assay, however prior to molecular analysis, the target cells are often prospectively isolated in bulk, thereby losing single-cell resolution. Single-cell gene expression analysis provides a means to understand molecular differences between individual cells in heterogeneous cell populations. In bulk cell analysis an overrepresentation of a distinct cell type results in biases and occlusions of signals from rare cells with biological importance. By utilizing FACS index sorting coupled to single-cell gene expression analysis, populations can be investigated without the loss of single-cell resolution while cells with intermediate cell surface marker expression are also captured, enabling evaluation of the relevance of continuous surface marker expression. Here, we describe an approach that combines single-cell reverse transcription quantitative PCR (RT-qPCR) and FACS index sorting to simultaneously characterize the molecular and immunophenotypic heterogeneity within cell populations.
In contrast to single-cell RNA sequencing methods, the use of qPCR with specific target amplification allows for robust measurements of low-abundance transcripts with fewer dropouts, while it is not confounded by issues related to cell-to-cell variations in read depth. Moreover, by directly index-sorting single-cells into lysis buffer this method, allows for cDNA synthesis and specific target pre-amplification to be performed in one step as well as for correlation of subsequently derived molecular signatures with cell surface marker expression. The described approach has been developed to investigate hematopoietic single-cells, but have also been used successfully on other cell types.
In conclusion, the approach described herein allows for sensitive measurement of mRNA expression for a panel of pre-selected genes with the possibility to develop protocols for subsequent prospective isolation of molecularly distinct subpopulations.

Bulk gene expression measurements cloud individual cell differences in heterogeneous cell populations. Here, we describe a protocol for how single-cell gene expression analysis and index sorting by Florescence Activated Cell Sorting (FACS) can be combined to delineate heterogeneity and immunophenotypically characterize molecularly distinct cell populations.

組合せの単一セルは分子を特徴付ける方法・肺浸潤異質性ひと幹と前駆細胞集団

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is ...

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding of the basis of various diseases as well as resistance and/or susceptibility mechanisms. However, FFPE tissues, which represent the most common method for preserving tissue morphology in clinical specimens, are not the best sources for gene expression profiling analysis. The RNA obtained from such samples is often degraded, fragmented, and chemically modified, which leads to suboptimal sequencing libraries. In turn, these generate poor quality sequence data that may not be reliable for gene expression analysis and mutation discovery. In order to make the most of FFPE samples and obtain the best possible data from low quality samples, it is important to take certain precautions while planning experimental design, preparing sequencing libraries, and during data analysis. This includes the use of appropriate metrics for precise sample quality control (QC), identifying the best methods for various steps during the sequencing library generation, and careful library QC. In addition, applying correct software tools and parameters for sequence data analysis is critical in order to identify artifacts in RNA-seq data, filter out contamination and low quality reads, assess uniformity of gene coverage, and measure the reproducibility of gene expression profiles among biological replicates. These steps can ensure high accuracy and reproducibility for profiling of very heterogeneous RNA samples. Here we describe the various steps for sample QC, library preparation and QC, sequencing, and data analysis that can help to increase the amount of useful data obtained from low quality RNA, such as that obtained from FFPE-RNA tissues.

This method describes the steps to improve the quality and quantity of sequence data that can be obtained from formalin-fixed paraffin-embedded (FFPE) RNA samples. We describe the methodology to more accurately assess the quality of FFPE-RNA samples, prepare sequencing libraries, and analyze the data from FFPE-RNA samples.

分解されたFFPE-RNAサンプルのシーケンシングと分析の最適化

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding ...

Single Cell Analysis Of Transcriptionally Active Alleles By Single Molecule FISH

Gene transcription is an essential process in cell biology, and allows cells to interpret and respond to internal and external cues. Traditional bulk population methods (Northern blot, PCR, and RNAseq) that measure mRNA levels lack the ability to provide information on cell-to-cell variation in responses. Precise single cell and allelic visualization and quantification is possible via single molecule RNA fluorescence in situ hybridization (smFISH). RNA-FISH is performed by hybridizing target RNAs with labeled oligonucleotide probes. These can be imaged in medium/high throughput modalities, and, through image analysis pipelines, provide quantitative data on both mature and nascent RNAs, all at the single cell level. The fixation, permeabilization, hybridization and imaging steps have been optimized in the lab over many years using the model system described herein, which results in successful and robust single cell analysis of smFISH labeling. The main goal with sample preparation and processing is to produce high quality images characterized by a high signal-to-noise ratio to reduce false positives and provide data that are more accurate. Here, we present a protocol describing the pipeline from sample preparation to data analysis in conjunction with suggestions and optimization steps to tailor to specific samples.&#160;

Single molecule RNA fluorescence in situ hybridization (smFISH) is a method to accurately quantify levels and localization of specific RNAs at the single cell level. Here, we report our validated lab protocols for wet-bench processing, imaging and image analysis for single cell quantification of specific RNAs.

単一分子FISHによる転写活性アレスの単一細胞解析

Gene transcription is an essential process in cell biology, and allows cells to interpret and respond to internal and external cues. Traditional bulk ...

生化学

Cerebrospinal Fluid MicroRNA Profiling Using Quantitative Real Time PCR

MicroRNAs (miRNAs) constitute a potent layer of gene regulation by guiding RISC to target sites located on mRNAs and, consequently, by modulating their translational repression. Changes in miRNA expression have been shown to be involved in the development of all major complex diseases. Furthermore, recent findings showed that miRNAs can be secreted to the extracellular environment and enter the bloodstream and other body fluids where they can circulate with high stability. The function of such circulating miRNAs remains largely elusive, but systematic high throughput approaches, such as miRNA profiling arrays, have lead to the identification of miRNA signatures in several pathological conditions, including neurodegenerative disorders and several types of cancers. In this context, the identification of miRNA expression profile in the cerebrospinal fluid, as reported in our recent study, makes miRNAs attractive candidates for biomarker analysis.
There are several tools available for profiling microRNAs, such as microarrays, quantitative real-time PCR (qPCR), and deep sequencing. Here, we describe a sensitive method to profile microRNAs in cerebrospinal fluids by quantitative real-time PCR. We used the Exiqon microRNA ready-to-use PCR human panels I and II V2.R, which allows detection of 742 unique human microRNAs. We performed the arrays in triplicate runs and we processed and analyzed data using the GenEx Professional 5 software.
Using this protocol, we have successfully profiled microRNAs in various types of cell lines and primary cells, CSF, plasma, and formalin-fixed paraffin-embedded tissues.

We describe a protocol of real time PCR to profile microRNAs in the cerebrospinal fluid (CSF). With the exception of RNA extraction protocols, the procedure can be extended to RNA extracted from other body fluids, cultured cells, or tissue specimens.

定量リアルタイムPCRを用いて脳脊髄液マイクロRNAプロファイリング

MicroRNAs (miRNAs) constitute a potent layer of gene regulation by guiding RISC to target sites located on mRNAs and, consequently, by modulating their ...

医学

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

For most mammalian pathogens, gene expression profiling studies have been limited by technical difficulties to accurately quantify pathogen gene transcripts from infected tissues. Pathogen RNA constitutes a tiny portion of the total RNA isolated from infected tissue samples. Both microarray and RNAseq technologies have difficulties in generating reliable reads for weakly expressed pathogen genes. Mutant pathogen strains with reduced in vivo proliferation pose an even bigger challenge. Here we describe an in vivo gene expression profiling protocol that is very fast, extremely sensitive and highly reproducible. We developed this protocol during our investigation of the fungal pathogen Candida albicans in a murine model of hematogenously disseminated candidiasis. Using this protocol, we have documented time courses of dynamically regulated C. albicans gene expression during kidney infection, and discovered unexpected features of gene expression responses to antifungal drug treatment in vivo.

We developed a protocol that is fast, sensitive and reproducible for pathogen gene expression profiling during an infection.

デジタルバーコードプラットフォームを使用して感染する微生物の遺伝子発現プロファイリング

For most mammalian pathogens, gene expression profiling studies have been limited by technical difficulties to accurately quantify pathogen gene ...

免疫・感染学

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 expression profiling allows the detailed gene expression analysis of individual cells. We describe methods for the isolation of cardiomyocytes, and preparing the resulting lysates for either whole transcriptome microarray or qPCR of specific targets.

成体マウスの心筋細胞の単一細胞転写プロファイリング

While numerous studies have examined gene expression changes from homogenates of heart tissue, this prevents studying the inherent stochastic variation ...

生物学

Profiling Individual Human Embryonic Stem Cells by Quantitative RT-PCR

Heterogeneity of stem cell population hampers detailed understanding of stem cell biology, such as their differentiation propensity toward different lineages. A single cell transcriptome assay can be a new approach for dissecting individual variation. We have developed the single cell qRT-PCR method, and confirmed that this method works well in several gene expression profiles. In single cell level, each human embryonic stem cell, sorted by OCT4::EGFP positive cells, has high expression in OCT4, but a different level of NANOG expression. Our single cell gene expression assay should be useful to interrogate population heterogeneities.

Single cell gene expression assay is needed for understanding stem cell heterogeneities.

定量的RT-PCRによって個々のヒト胚性幹細胞のプロファイリング

Heterogeneity of stem cell population hampers detailed understanding of stem cell biology, such as their differentiation propensity toward different ...