Poster S6 - Using gRNA Based Neutral Barcodes to Study Cancer Evolution

Introduction: DNA barcoding is an emerging technology to study cellular memory and evolution. When random DNA barcodes are introduced to cells they allow precise tracking of lineages, for example after fluorescence activated sorting with a cell-state marker or after selection with therapy. Earlier technologies worked solely through DNA sequencing. However, recent technologies allow researchers to identify lineages in single-cell RNA sequencing data by expressing the barcodes as RNA. The CROP-seq technology, which expresses gRNAs that are detectable in single-cell RNA sequencing, provides a new strategy to barcode cells. By using random gRNAs, as opposed to gene targeting gRNAs, we can track cell lineages without interfering with their phenotype. The expression of these gRNAs further allows us to isolate cells using a recovery system, in which the gRNAs activate an artificial promoter. This isolation step is often necessary to study ultra-rare lineages such as targeted therapy resistant lineages prior to treatment.

Materials and

Methods: Semi-random 20 base pair gRNAs were cloned into a CROP-seq backbone. We replaced the puromycin selection marker of this backbone with nuclear localized EGFP for ease of virus titration and to allow tracking with live-cell microscopy. This barcoding system was tested on a model of EGFR driven non-small cell lung cancer by infecting 10,000 cells with unique barcodes and growing them in the presence of diverse EGFR inhibitors. We then PCR amplified and sequenced barcodes from genomic DNA isolated from these populations. We furthermore developed barcoded subclones of cancer cells to test our lineage isolation system.

Results, Conclusions, and Discussions: We developed a high complexity library to track cell lineages. By achieving a high complexity (~28 million barcodes) we can avoid independent incorporation of barcodes by unrelated cells. Lineage sizes were determined from genomic DNA after treating an EGFR mutated non-small cell lung cancer cell line with various EGFR inhibitors. We also confirmed that library barcodes could be detected using single-cell RNA sequencing technologies. Finally, a system to isolate barcodes is being tested in our cell lines.

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