To develop a novel imaging-based single cell RNA-sequencing (scRNA-Seq) platform that allows capturing of spatiotemporal information and cellular behavior of the sequenced cells within tissue.
scRNA-Seq generates transcriptomic profile for individual cells, allowing elucidation of sophisticated heterogeneous gene expression and splicing patterns in a seemingly homogeneous cell population. Current isolation of single cells for scRNA-Seq involves complete tissue disruption, thus inevitably destroying key information regarding position and behavior of cells in the tissue.
The present invention “4D-Seq” harnesses two-photon microscopy and DNA-labelling techniques to enable capturing of cellular spatial and time-varying information within the tissue prior to scRNA-seq analysis. This spatial information can then be correlated in turn with 2P microscopy data of the same tissue, effectively linking scRNA-Seq with visualized environmental parameters as well as time-dependent behaviors such as migration, and cell-cell interactions in tumor microenvironments.
Investigators at University of California, San Francisco, have invented new technology to capture spatial information in scRNA-seq experiments. The invention involves labelling of cells within tissues by attachment of oligonucleotide barcodes to the surface of cells in a light-dependent manner. Two-photon microscopy will be used to image the tissue, as well as photo-activate oligonucleotide barcodes to label cells in specific regions at any desired time. The spatial information derived from imaging can then be correlated with scRNA-seq data using barcode sequences, thereby providing researchers with spatial information about gene expression patterns within tissues.
To develop & commercialize the technology as a spatiotemporal imaging platform for correlating gene expression with in situ cellular behaviors.
Pre-Clinical
Proof of Concept Data Pending
Patent Pending
Single Cell RNA Sequencing, 4-dimensional Sequencing, Transcriptomics, Spatial/Temporal Information, Barcoding, Cancer, Live Tissue Imaging