The living microarray: a high-throughput platform for measuring transcription dynamics in single cells
Background 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-depe...
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| Published in | BMC genomics Vol. 12; no. 1; p. 115 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
16.02.2011
BioMed Central Ltd Springer Nature B.V BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1471-2164 1471-2164 |
| DOI | 10.1186/1471-2164-12-115 |
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| Abstract | Background
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.
Results
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.
Conclusions
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. |
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| AbstractList | 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. Abstract Background 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. Results 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. Conclusions 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. 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.BACKGROUNDCurrent 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.RESULTSHere 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.CONCLUSIONSThe 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. 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. Background 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. Results 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. Conclusions 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. Background 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. Results 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. Conclusions 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. |
| ArticleNumber | 115 |
| Audience | Academic |
| Author | Djambazian, Haig Sladek, Rob Hudson, Thomas J Rajan, Saravanan Dang, Huan Chu Pham |
| AuthorAffiliation | 6 Ontario Institute for Cancer Research, Toronto, Ontario, Canada 5 Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada 1 Department of Human Genetics, McGill University, Montréal, Québec, Canada 4 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada 2 Department of Medicine, McGill University, Montréal, Québec, Canada 3 McGill University and Genome Quebec Innovation Centre, Montréal, Québec, Canada |
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| Author_xml | – sequence: 1 givenname: Saravanan surname: Rajan fullname: Rajan, Saravanan organization: Department of Human Genetics, McGill University – sequence: 2 givenname: Haig surname: Djambazian fullname: Djambazian, Haig organization: McGill University and Genome Quebec Innovation Centre – sequence: 3 givenname: Huan Chu Pham surname: Dang fullname: Dang, Huan Chu Pham organization: Department of Medicine, McGill University – sequence: 4 givenname: Rob surname: Sladek fullname: Sladek, Rob email: robert.sladek@mcgill.ca organization: Department of Human Genetics, McGill University, Department of Medicine, McGill University, McGill University and Genome Quebec Innovation Centre – sequence: 5 givenname: Thomas J surname: Hudson fullname: Hudson, Thomas J organization: Department of Molecular Genetics, University of Toronto, Department of Medical Biophysics, University of Toronto, Ontario Institute for Cancer Research |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/21324195$$D View this record in MEDLINE/PubMed |
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| Snippet | Background
Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional regulation... Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional regulation and Systems... Background Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional regulation... Abstract Background: Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional... Abstract Background Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional... |
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| SubjectTerms | Animal Genetics and Genomics Animals Automation Cancer Cell development (Biology) Cell division Cell Line Cloning Colleges & universities DNA microarrays Experiments Gene Expression Profiling Genetic transcription Genomes Genomics Heterogeneity High-Throughput Nucleotide Sequencing - methods Life Sciences Medical research Methodology Methodology Article Microarrays Microbial Genetics and Genomics Microscopy Microscopy, Fluorescence Oligonucleotide Array Sequence Analysis - methods Plant Genetics and Genomics Plasmids Promoter Regions, Genetic Proteins Proteomics Single-Cell Analysis Transcription, Genetic Transcriptomic methods Transfection |
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| Title | The living microarray: a high-throughput platform for measuring transcription dynamics in single cells |
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