17. A MICROFLUIDIC DEVICE FOR SINGLE-CELL GENE EXPRESSION PROFILING

Department: Bioengineering
Faculty Advisor(s): Xiaohua Huang

Primary Student
Name: Alexander Philip Hsiao
Email: a2hsiao@ucsd.edu
Phone: 858-822-4702
Grad Year: 2012

Student Collaborators
Matthew Walsh, mtwalsh@ucsd.edu

Abstract
It is now evident that gene expression varies greatly amongst individual cells, even within a population of the same cell type. Unfortunately, most common molecular analysis techniques require a multitude of cells and produce only an averaged result. Therefore, it is essential that technologies capable of isolating and comprehensively analyzing many single cells in parallel be developed. Such technologies will enable a better understanding of rare and specialized cells with implications in areas such as cancer development, stem cell differentiation, and drug discovery. Microfluidic devices are well suited for such applications because fluidic channels with dimensions in the same range as those of mammalian cells allow for rapid and more controlled manipulation of single cells. In addition, they can be integrated into complete systems where single cells can be captured, lysed, and analyzed within the same chip. Current microfluidic approaches towards single-cell gene expression analysis often require off-chip analysis by qPCR or microarray of the captured mRNA transcripts and often are capable of only interrogating a single cell at a time. Carrying out downstream analysis off-chip often leads to sample loss. Additionally, it is well known that amplification often introduces bias by disproportionately favoring transcripts with higher starting copy number. As such, it is difficult to quantify rare transcripts accurately. Here we present an integrated device for trapping and isolating single cells in parallel, with subsequent on-chip identification and digital counting of mRNA transcripts. Our technology will enable the comprehensive digital quantification of the gene expression profile of single cells with increased efficiency and minimal sample loss.

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