Application of dual-view oblique plane microscopy to small-molecule compound screening across 3D glioblastoma stem cell spheroids with single-cell resolution

Abstract

Recent advances and increasing adoption of 3-dimensional (3D) model systems, such as tumour spheroids and organoids, attempt to more faithfully recapitulate the pathophysiology and heterogeneity observed in patients' tumours, with the goal of reducing high attrition rates observed in late stage drug development. While established high content imaging systems provide the spatial resolution and throughput necessary to place 3D models at the earliest stages of drug discovery, they yield limited information on disease heterogeneity or drug response at the single cell level in 3D. Improvements in single-cell RNA-Seq are transforming our understanding of disease trajectories and therapy response, however this technology is too expensive and laborious for high throughput screening. Here we demonstrate the high content screening capabilities of a compact and low cost light-sheet fluorescence microscopy platform called dual-view oblique plane microscope (dOPM). We apply the dOPM to screen a small library of compounds in a 3D glioblastoma (GBM) stem cell spheroid model expressing the FUCCI cell cycle reporter. We benchmark the performance and compare the outputs of the dOPM GBM spheroid assay with standard 2D and 3D spheroids assays using established spinning disk confocal high content platforms. In a proof-of-principle small molecule compound screen we demonstrate that the dOPM performs to accepted standards of reproducibility for high throughput screening in a 96-well plate format. We further demonstrate the ability of the dOPM to capture the heterogeneity across multiple spheroids within an individual well and provide single cell level data within each individual 3D spheroid. We propose that further development of the opensource dOPM platform will support the advancement of 3D high content phenotypic screening assays from cell population measurements to highly quantitative single cell analysis across 3D space and time dimensions.