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Platform technology for selective single cell RNA sequencing of transient events

University of British Columbia

Cells are encapsulated decision-making units that measure external stimuli, process incoming information, and develop appropriate responses. A key window into cellular decision-making are the transcriptional programs enacted after specific events. Recent advances in transcriptome analysis by single cell RNA sequencing have revealed the remarkable transcriptional heterogeneity between cells. However, current methods are unable to investigate the changes of the transcriptional profile adopted by specific cells after specific events. This dissertation presents See-N-Seq, a new method to selectively extract RNA from single cells identified by imaging in order to perform transcriptome profiling after specific events. Our process involves embedding the cell sample in a permeable hydrogel in a microwell, and then photo-patterning a second impermeable hydrogel inside the permeable hydrogel. Non-target cells are encapsulated in the impermeable hydrogel, while target cells are encapsulated in the permeable hydrogel. Target cells can then be lysed to release RNA, which is then captured, barcoded, reverse transcribed, amplified, and sequenced at high-depth. We initially tested this process by extracting single cell RNA from mixtures of transgenic cancer cells, which is then analyzed using qPCR. We demonstrated the utility of this technology by sequencing RNA from an in vitro model of immune synapses formed between Jurkat cells and Raji cells with Staphylococcal enterotoxin E (SEE) super-antigen. The RNA from synapse formed single cell pairs were selected and sequenced as well as non-synapse formed single cell pairs at 0, 4, 24 hour time points. As a control, RNA from the bulk and single cell samples of Jurkat cells and Raji cells were also sequenced. The transcriptome sequencing data showed an average of 0.39 +/- 0.11 million unique transcripts for each cell or cell pair, which represent most of the mRNA in single cells. Furthermore, we confirmed the potential for Jurkat cells to adopt divergent transcriptional programs at 24 hours after synapsing. Together, these results demonstrate the potential of See-N-Seq to uncover decision-making processes in critical single cells that ultimately lead to health and disease outcomes.

Text

2023-04-30

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/74228

Mechanical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/