Multiplex live single-cell transcriptional analysis demarcates cellular functional heterogeneity
- Massachusetts General Hospital, United States
- Tufts University, United States
Abstract
A fundamental goal in the biological sciences is to determine how individual cells with varied gene expression profiles and diverse functional characteristics contribute to development, physiology, and disease. Here, we report a novel strategy to assess gene expression and cell physiology in single living cells. Our approach utilizes fluorescently-labeled mRNA-specific anti-sense RNA probes and dsRNA-binding protein to identify the expression of specific genes in real-time at single-cell resolution via FRET. We use this technology to identify distinct myocardial subpopulations expressing the structural proteins myosin heavy chain α and myosin light chain 2a in real-time during early differentiation of human pluripotent stem cells. We combine this live-cell gene expression analysis with detailed physiologic phenotyping to capture the functional evolution of these early myocardial subpopulations during lineage specification and diversification. This live-cell mRNA imaging approach will have wide ranging application wherever heterogeneity plays an important biological role.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files.
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Author details
Funding
American Heart Association (Predoctoral Fellowship)
- Ayhan Atmanli
National Heart, Lung, and Blood Institute (Progenitor Cell Biology Consortium (PCBC) Jump Start Award)
- Ayhan Atmanli
National Heart, Lung, and Blood Institute (U01HL100408-01)
- Ibrahim Domian
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Atmanli et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Multiplex live single-cell transcriptional analysis demarcates cellular functional heterogeneity
eLife 8:e49599.
https://doi.org/10.7554/eLife.49599
