Poster
Overview
Single cell analysis is a critical approach to tease out nuanced information in any biological system. Combinatorial barcoding is an extremely efficient method for scRNA-seq at scale, achieving both sensitivity in gene detection and flexibility in sample input. This approach, however, is challenging when starting with sample inputs of less than 100,000 cells. To address this, we have developed a modified fixation and cell capture method for low sample inputs that is compatible with the combinatorial barcoding approach. This allows researchers working with low sample inputs to fix, store and barcode their cells efficiently without the need for costly or specialized instruments. This approach can be used to fix and profile up to 384 samples in parallel, results in a shorter workflow, and enables consistent handling (which minimizes both experimental error and burden on scaling). This method maintains the stability of fixed samples at -80℃ and capture efficiency remains consistently high for inputs as low as 10,000 cells. The workflow maximizes sample recovery while providing accurate and comprehensive results of transcriptional changes from experimental perturbations.
As proof-of-concept we screened a cancer drug panel with cell input amounts between 10,000 - 20,000 cells per treatment. Robust cell capture minimizes loss during drug perturbations resulting in consistent gene detection. Whole transcriptome analysis using Evercode WT identifies changes in gene expression associated with each drug class and cell type. Results of the screen validate putative drug targets in the panel. Additionally, panel-based perturbation allows for detection of off-target impacts at scale. This work demonstrates the combination of low input fixation with combinatorial barcoding to enable high throughput cancer drug and compound screening.