SINGLE-CELL CULTURE AND SEQUENCING WITH LIPID-MODIFIED OLIGOS

SINGLE-CELL CULTURE AND SEQUENCING WITH LIPID-MODIFIED OLIGOS

Researchers at UCSF have developed methods for sequencing a single cell from a cell culture sample and obtaining morphologic or phenotypic measurements and information by combining sequencing approaches and spatial hashing (e.g. barcoding) at a single cell level.

There exists a need in the state of the art for a method of obtaining morphological or phenotypic measurements and information linked with sequence information at the single-cell level. Current spatial transcriptomics technologies require dead tissues and are not compatible with live cell cultures. Current single-cell sequencing technologies do not include spatial indexes that allow users to map single-cell RNAseq data to cell morphology. Methods to integrate cell morphology and gene expression are limited by throughput and either require sacrificing detection efficiency and/or the number of genes probed.

Stage of Research

The inventors have developed methods for the high-throughput integration of single-cell long-term culture, imaging, and RNA-seq without the need for specialized substrates. The method utilizes lipid-modified oligonucleotides (LMO) to spatially label cultured single cells grown on any surface. The cells are resuspended into solution, for example by trypsinization, and then subjected to a standard single-cell sequencing platform. This invention enables imaging-based phenotypic observation on live cultured cells, which can be unambiguously linked with transcriptome information.

Applications

Enabling the discovery of oncogenic cells based on imaging
Enabling selection of engineered cells lines (e.g., CAR-T) that have desired cell-cell interaction properties; for example cells that kill cancer cells
Sequencing cells with in-situ spatial hashing/barcoding
High-throughput integration of single-cell morphology and transcriptome for individual neurons
Paired spatial transcriptomics and force profiling for single cell analysis
Integrating transcriptome and metabolome for pathway engineering of valuable metabolites

Advantages

Compatibility with live cell cultures
Inclusion of spatial indexes that allow users to map single-cell RNAseq data to cell morphology
Compatibility with high-throughput methods
Compatible with long-term cell culture and high resolution-imaging
Single-cell precision

Stage of Development

Research – in vitro

Publications

WO2023/107598