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Anal Biochem. 2016 Sep 01;508:1-8. doi: 10.1016/j.ab.2016.05.021. Epub 2016 May 31.

A multi-layer microchip for high-throughput single-cell gene expression profiling.

Analytical biochemistry

Hao Sun

Affiliations

  1. School of Mechanical Engineering, Fuzhou University, Fuzhou, Fujian, 350001, China. Electronic address: [email protected].

PMID: 27255567 DOI: 10.1016/j.ab.2016.05.021

Abstract

Microfluidics or Bio-MEMS technology offers significant advantages for performing high-throughput screens and sensitive assays. The ability to correlate single-cell genetic information with cellular phenotypes is of great importance to biology and medicine because it holds the potential to gain insight into disease pathways that is unavailable from ensemble measurements. Previously, we reported two kinds of prototypes for integrated on-chip gene expression profiling at the single-cell level, and the throughput was designed to be 6. In this work, we present a five-layer microfluidic system for parallelized, rapid, quantitative analysis of RNA templates with low abundance at the single-cell level. The microchip contains two multiplexors and one partitioning valve group, and it leverages a matrix (6 × 8) of quantitative reverse transcription polymerase chain reaction (RT-qPCR) units formed by a set of parallel microchannels concurrently controlled by elastomeric pneumatic valves, thereby enabling parallelized handling and processing of biomolecules in a simplified operation procedure. A comprehensive metallic nanofilm with passivation layer is used to run polymerase chain reaction (PCR) temperature cycles. To demonstrate the utility of the approach, artificial synthesized RNA templates (XenoRNA) and mRNA templates from single cells are employed to perform the 48-readout RT-qPCRs. The PCR products are imaged on a fluorescence microscope using a hydrolysis probe/primer set (TaqMan). Fluorescent intensities of passive reference dye and a fluorescein amidite reporter dye are acquired and measured at the end of PCR cycles.

Copyright © 2016 Elsevier Inc. All rights reserved.

Keywords: Bio-MEMS; High-throughput single-cell analysis; Integrated RT–qPCR

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