SCITO-SEQ: SINGLE CELL COMBINATORIAL INDEXED CYTOMETRY SEQUENCING
Researchers at UCSF have developed SCITO-seq, a new workflow for single cell sequencing-based proteomics.
The use of DNA to barcode and tag antibodies has created new opportunities to use sequencing to profile the molecular properties of thousands of cells simultaneously. Furthermore, DNA-barcoded antibodies coupled with advances in microfluidics have enabled droplet-based single cell sequencing (dsc-seq) to profile the surface proteomes of cells. The major limitation of current dsc-seq workflows is the high cost associated with profiling each cell, precluding its use in applications where thousands or millions of cells are required.
Stage of Research
The inventors introduce SCITO-seq, a single cell proteomics workflow that combines split-pool indexing and commercially available dsc-seq to enable cost-effective profiling of cell surface proteins, scalable to 105-106 cells. SCITO-seq utilizes advances in droplet-based microfluidics for combinatorial indexing of antibody-derived pool and droplet barcodes to reduce library construction and sequencing costs. Protein expression profiles for cells simultaneously encapsulated in a single drop are resolved by the combinatorial index of pool and droplet barcodes. The inventors demonstrate the feasibility and scalability of SCITO-seq in mixed species experiments and by profiling peripheral blood mononuclear cells using a panel of 28 antibodies in one microfluidic reaction.
Applications
Advantages
Stage of Development
Research – in vitro
Publications
Hwang B, Lee DS, Tamaki W, et al. SCITO-seq: single-cell combinatorial indexed cytometry sequencing. bioRxiv. 2020. Doi: 10.1101/2020.03.27012633
Related Web Links
https://www.yelabUCSF.org
Keywords
Single cell, single cell analysis, antibody, microfluidics, droplet-based single cell sequencing, dsc-seq, proteomics
Reference
CZB-157F, UCSF SF2020-186