The living microarray: a high-throughput platform for measuring transcription dynamics in single cells
- Equal contributors
1 Department of Human Genetics, McGill University, Montréal, Québec, Canada
2 Department of Medicine, McGill University, Montréal, Québec, Canada
3 McGill University and Genome Quebec Innovation Centre, Montréal, Québec, Canada
4 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
5 Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
6 Ontario Institute for Cancer Research, Toronto, Ontario, Canada
BMC Genomics 2011, 12:115 doi:10.1186/1471-2164-12-115Published: 16 February 2011
Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional regulation and Systems Biology. However, endpoint measurements obtained from methods that pool populations of cells are not amenable to studying time-dependent processes that show cell heterogeneity.
Here we describe a high-throughput platform for measuring transcriptional changes in real time in single mammalian cells. By using reverse transfection microarrays we are able to transfect fluorescent reporter plasmids into 600 independent clusters of cells plated on a single microscope slide and image these clusters every 20 minutes. We use a fast-maturing, destabilized and nuclear-localized reporter that is suitable for automated segmentation to accurately measure promoter activity in single cells. We tested this platform with synthetic drug-inducible promoters that showed robust induction over 24 hours. Automated segmentation and tracking of over 11 million cell images during this period revealed that cells display substantial heterogeneity in their responses to the applied treatment, including a large proportion of transfected cells that do not respond at all.
The results from our single-cell analysis suggest that methods that measure average cellular responses, such as DNA microarrays, RT-PCR and chromatin immunoprecipitation, characterize a response skewed by a subset of cells in the population. Our method is scalable and readily adaptable to studying complex systems, including cell proliferation, differentiation and apoptosis.