Imaging and analysis for simultaneous tracking of fluorescent biosensors in barcoded cells
We recently developed a biosensor barcoding approach for highly multiplexed tracking of molecular activities in live cells. In this protocol, we detail the labeling of cells expressing different genetically encoded fluorescent biosensors with a pair of barcoding proteins and parallel imaging. Signal...
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Veröffentlicht in: | STAR protocols 2022-09, Vol.3 (3), p.101611-101611, Article 101611 |
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Sprache: | eng |
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Zusammenfassung: | We recently developed a biosensor barcoding approach for highly multiplexed tracking of molecular activities in live cells. In this protocol, we detail the labeling of cells expressing different genetically encoded fluorescent biosensors with a pair of barcoding proteins and parallel imaging. Signals from cells with the same barcodes are then pooled together to obtain the dynamics of the corresponding biosensor activity. We describe the steps involved in cell barcoding, image acquisition, and analysis by deep learning models.
For complete details on the use and execution of this protocol, please refer to Yang et al. (2021).
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•Cells expressing different biosensors can be barcoded for simultaneous imaging•Spectral imaging is used to resolve multiple red barcoding proteins•Deep learning models accelerate barcode reading during image analysis
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
We recently developed a biosensor barcoding method for highly multiplexed tracking of molecular activities in live cells. In this protocol, we detail the labeling of cells expressing different genetically encoded fluorescent biosensors with a pair of barcoding proteins and parallel imaging. Signals from cells with the same barcodes are then pooled together to obtain the dynamics of the corresponding biosensor activity. We describe the steps involved in cell barcoding, image acquisition, and analysis by deep learning models. |
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ISSN: | 2666-1667 2666-1667 |
DOI: | 10.1016/j.xpro.2022.101611 |