Discriminating cellular heterogeneity using microwell-based RNA cytometry

Ivan K. Dimov (), Rong Lu, Eric P. Lee, Jun Seita, Debashis Sahoo, Seung-min Park, Irving L. Weissman and Luke P. Lee
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Ivan K. Dimov: Biomolecular Nanotechnology Center, Berkeley Sensor and Actuator Center, University of California
Rong Lu: Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine
Eric P. Lee: Biomolecular Nanotechnology Center, Berkeley Sensor and Actuator Center, University of California
Jun Seita: Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine
Debashis Sahoo: Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine
Seung-min Park: Biomolecular Nanotechnology Center, Berkeley Sensor and Actuator Center, University of California
Irving L. Weissman: Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine
Luke P. Lee: Biomolecular Nanotechnology Center, Berkeley Sensor and Actuator Center, University of California

Nature Communications, 2014, vol. 5, issue 1, 1-12

Abstract: Abstract Discriminating cellular heterogeneity is important for understanding cellular physiology. However, it is limited by the technical difficulties of single-cell measurements. Here we develop a two-stage system to determine cellular heterogeneity. In the first stage, we perform multiplex single-cell RNA cytometry in a microwell array containing over 60,000 reaction chambers. In the second stage, we use the RNA cytometry data to determine cellular heterogeneity by providing a heterogeneity likelihood score (HLS). Moreover, we use Monte-Carlo simulation and RNA cytometry data to calculate the minimum number of cells required for detecting heterogeneity. We apply this system to characterize the RNA distributions of ageing-related genes in a highly purified mouse haematopoietic stem cell population. We identify genes that reveal novel heterogeneity of these cells. We also show that changes in expression of genes such as Birc6 during ageing can be attributed to the shift of relative portions of cells in the high-expressing subgroup versus low-expressing subgroup.

Date: 2014
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DOI: 10.1038/ncomms4451

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