Related Experiment Video
Updated: May 20, 2026

Assessing Neural Stem Cell Motility Using an Agarose Gel-based Microfluidic Device
Published on: February 11, 2008
An automated microfluidic device for assessment of mammalian cell genetic stability
Yan Chen1, Baoyue Zhang, Hongtao Feng
1Department of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. yan.chen@siat.ac.cn
Abstract:
Single-cell transcriptome contains reliable gene regulatory relationships because gene-gene interactions only happen within a mammalian cell. While the study of gene-gene interactions enables us to understand the molecular mechanism of cellular events and evaluate molecular characteristics of a mammalian cell population, its complexity requires an analysis of a large number of single-cells at various stages. However, many existing microfluidic platforms cannot process single-cells effectively for routine molecular analysis. To address these challenges, we develop an integrated system with individual controller for effective single-cell transcriptome analysis. In this paper, we report an integrated microfluidic approach to rapidly measure gene expression in individual cells for genetic stability assessment of a cell population. Inside this integrated microfluidic device, the cells are individually manipulated and isolated in an array using micro sieve structures, then transferred into different nanoliter reaction chambers for parallel processing of single-cell transcriptome analysis. This device enables us to manipulate individual single-cells into nanoliter reactor with high recovery rate. We have performed gene expression analysis for a large number of HeLa cells and 293T cells expanded from a single-cell. Our data shows that even the house-keeping genes are expressed at heterogeneous levels within a clone of cells. The heterogeneity of actin expression reflects the genetic stability, and the expression distribution is different between cancer cells (HeLa) and immortalized 293T cells. The result demonstrates that this platform has the potential for assessment of genetic stability in cancer diagnosis.

