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A single cell is the very fundamental element in an organism; however, it contains the most complicated and stochastic information, such as DNA, RNA, and protein expression. Thus, it is a necessity to study stochastic gene expression in order to

A single cell is the very fundamental element in an organism; however, it contains the most complicated and stochastic information, such as DNA, RNA, and protein expression. Thus, it is a necessity to study stochastic gene expression in order to discover the biosignatures at the single-cell level. The heterogeneous gene expression of single cells from an isogenic cell population has already been studied for years. Yet to date, single-cell studies have been confined in a fashion of analyzing isolated single cells or a dilution of cells from the bulk-cell populations. These techniques or devices are limited by either the mechanism of cell lysis or the difficulties to target specific cells without harming neighboring cells.

This dissertation presents the development of a laser lysis chip combined with a two-photon laser system to perform single-cell lysis of single cells in situ from three-dimensional (3D) cell spheroids followed by analysis of the cell lysate with two-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The 3D spheroids were trapped in a well in the custom-designed laser lysis chip. Next, each single cell of interest in the 3D spheroid was identified and lysed one at a time utilizing a two-photon excited laser. After each cell lysis, the contents inside the target cell were released to the surrounding media and carried out to the lysate collector. Finally, the gene expression of each individual cell was measured by two-step RT-qPCR then spatially mapped back to its original location in the spheroids to construct a 3D gene expression map.

This novel technology and approach enables multiple gene expression measurements in single cells of multicellular organisms as well as cell-to-cell heterogeneous responses to the environment with spatial recognition. Furthermore, this method can be applied to study precancerous tissues for a better understanding of cancer progression and for identifying early tumor development.
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    Title
    • Single cell RT-qPCR on 3D cell spheroids
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    Date Created
    2016
    Resource Type
  • Text
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    Note
    • Partial requirement for: Ph.D., Arizona State University, 2016
      Note type
      thesis
    • Includes bibliographical references (pages 83-93)
      Note type
      bibliography
    • Field of study: Electrical engineering

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    by Kuo-Chen Wang

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