Literature DB >> 18094763

A microfluidic processor for gene expression profiling of single human embryonic stem cells.

Jiang F Zhong1, Yan Chen, Joshua S Marcus, Axel Scherer, Stephen R Quake, Clive R Taylor, Leslie P Weiner.   

Abstract

The gene expression of human embryonic stem cells (hESC) is a critical aspect for understanding the normal and pathological development of human cells and tissues. Current bulk gene expression assays rely on RNA extracted from cell and tissue samples with various degree of cellular heterogeneity. These 'cell population averaging' data are difficult to interpret, especially for the purpose of understanding the regulatory relationship of genes in the earliest phases of development and differentiation of individual cells. Here, we report a microfluidic approach that can extract total mRNA from individual single-cells and synthesize cDNA on the same device with high mRNA-to-cDNA efficiency. This feature makes large-scale single-cell gene expression profiling possible. Using this microfluidic device, we measured the absolute numbers of mRNA molecules of three genes (B2M, Nodal and Fzd4) in a single hESC. Our results indicate that gene expression data measured from cDNA of a cell population is not a good representation of the expression levels in individual single cells. Within the G0/G1 phase pluripotent hESC population, some individual cells did not express all of the 3 interrogated genes in detectable levels. Consequently, the relative expression levels, which are broadly used in gene expression studies, are very different between measurements from population cDNA and single-cell cDNA. The results underscore the importance of discrete single-cell analysis, and the advantages of a microfluidic approach in stem cell gene expression studies.

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Year:  2007        PMID: 18094763      PMCID: PMC4110104          DOI: 10.1039/b712116d

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  33 in total

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2.  Noise in genetic and neural networks.

Authors:  Peter S Swain; André Longtin
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3.  Gene regulation at the single-cell level.

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4.  Transcription factor profiling in individual hematopoietic progenitors by digital RT-PCR.

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5.  Tunability and noise dependence in differentiation dynamics.

Authors:  Gürol M Süel; Rajan P Kulkarni; Jonathan Dworkin; Jordi Garcia-Ojalvo; Michael B Elowitz
Journal:  Science       Date:  2007-03-23       Impact factor: 47.728

6.  Laser capture microdissection.

Authors:  M R Emmert-Buck; R F Bonner; P D Smith; R F Chuaqui; Z Zhuang; S R Goldstein; R A Weiss; L A Liotta
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7.  Analysis of gene expression in a complex differentiation hierarchy by global amplification of cDNA from single cells.

Authors:  G Brady; F Billia; J Knox; T Hoang; I R Kirsch; E B Voura; R G Hawley; R Cumming; M Buchwald; K Siminovitch
Journal:  Curr Biol       Date:  1995-08-01       Impact factor: 10.834

8.  Analysis of G protein alpha subunit mRNA abundance in preimplantation mouse embryos using a rapid, quantitative RT-PCR approach.

Authors:  L Rambhatla; B Patel; N Dhanasekaran; K E Latham
Journal:  Mol Reprod Dev       Date:  1995-07       Impact factor: 2.609

9.  Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise.

Authors:  John R S Newman; Sina Ghaemmaghami; Jan Ihmels; David K Breslow; Matthew Noble; Joseph L DeRisi; Jonathan S Weissman
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10.  Microfluidics device for single cell gene expression analysis in Saccharomyces cerevisiae.

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Journal:  Yeast       Date:  2006 Oct-Nov       Impact factor: 3.239

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  73 in total

1.  Single cell transcriptional profiling of adult mouse cardiomyocytes.

Authors:  James M Flynn; Luis F Santana; Simon Melov
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2.  Variability in G-protein-coupled signaling studied with microfluidic devices.

Authors:  Xiaoyan Robert Bao; Iain D C Fraser; Estelle A Wall; Stephen R Quake; Melvin I Simon
Journal:  Biophys J       Date:  2010-10-20       Impact factor: 4.033

Review 3.  Microfluidic single-cell analysis of intracellular compounds.

Authors:  Tzu-Chiao Chao; Alexandra Ros
Journal:  J R Soc Interface       Date:  2008-10-06       Impact factor: 4.118

4.  Single-cell detection of mRNA expression using nanofountain-probe electroporated molecular beacons.

Authors:  Juan P Giraldo-Vela; Wonmo Kang; Rebecca L McNaughton; Xuemei Zhang; Brian M Wile; Andrew Tsourkas; Gang Bao; Horacio D Espinosa
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5.  Microfluidic confinement of single cells of bacteria in small volumes initiates high-density behavior of quorum sensing and growth and reveals its variability.

Authors:  James Q Boedicker; Meghan E Vincent; Rustem F Ismagilov
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6.  Stem cells in microfluidics.

Authors:  Huei-Wen Wu; Chun-Che Lin; Gwo-Bin Lee
Journal:  Biomicrofluidics       Date:  2011-03-30       Impact factor: 2.800

7.  Single cell digital polymerase chain reaction on self-priming compartmentalization chip.

Authors:  Qiangyuan Zhu; Lin Qiu; Yanan Xu; Guang Li; Ying Mu
Journal:  Biomicrofluidics       Date:  2017-01-31       Impact factor: 2.800

Review 8.  Stem cells technology: a powerful tool behind new brain treatments.

Authors:  Lucienne N Duru; Zhenzhen Quan; Talal Jamil Qazi; Hong Qing
Journal:  Drug Deliv Transl Res       Date:  2018-10       Impact factor: 4.617

9.  T7-based linear amplification of low concentration mRNA samples using beads and microfluidics for global gene expression measurements.

Authors:  Jason G Kralj; Audrey Player; Hope Sedrick; Matthew S Munson; David Petersen; Samuel P Forry; Paul Meltzer; Ernest Kawasaki; Laurie E Locascio
Journal:  Lab Chip       Date:  2008-12-15       Impact factor: 6.799

10.  A microfluidic platform for electrical detection of DNA hybridization.

Authors:  M Javanmard; R W Davis
Journal:  Sens Actuators B Chem       Date:  2010-03-30       Impact factor: 7.460

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