SpheroidAnalyseR-an online platform for analyzing data from 3D spheroids or organoids grown in 96-well plates

Rhiannon Barrow; Joseph N Wilkinson; Yichen He; Martin Callaghan; Anke Brüning-Richardson; Mark Dunning; Lucy F Stead

doi:10.14440/jbm.2022.388

SpheroidAnalyseR-an online platform for analyzing data from 3D spheroids or organoids grown in 96-well plates

J Biol Methods. 2022 Nov 23;9(4):e163. doi: 10.14440/jbm.2022.388. eCollection 2022.

Authors

Rhiannon Barrow¹, Joseph N Wilkinson¹, Yichen He², Martin Callaghan³, Anke Brüning-Richardson⁴, Mark Dunning⁵, Lucy F Stead¹

Affiliations

¹ Leeds Institute of Medical Research at St James's, Wellcome Trust Brenner Building, St James's University Hospital, Leeds LS9 7TF, West Yorkshire, UK.
² Department of Animal and Plant Sciences, Alfred Denny Building, The University of Sheffield, Western Bank, Sheffield S10 2TN, UK.
³ Research Software Engineer Group, IT Services, University of Leeds, Leeds LS2 9JT, UK.
⁴ The University of Huddersfield School of Applied Sciences, Queensgate, Huddersfield HD1 3DH, West Yorkshire, UK.
⁵ Bioinformatics Core, The University of Sheffield Medical School, Beech Hill Road, Sheffield S10 2RX, UK.

Abstract

Spheroids and organoids are increasingly popular three-dimensional (3D) cell culture models. Spheroid models are more physiologically relevant to a tumor compared to two-dimensional (2D) cultures and organoids are a simplified version of an organ with similar composition. Spheroids are often only formed from a single cell type which does not represent the situation in vivo. However, despite this, both spheroids and organoids can be used in cell migration studies, disease modelling and drug discovery. A drawback of these models is, however, the lack of appropriate analytical tools for high throughput imaging and analysis over a time course. To address this, we have developed an R Shiny app called SpheroidAnalyseR: a simple, fast, effective open-source app that allows the analysis of spheroid or organoid size data generated in a 96-well format. SpheroidAnalyseR processes and analyzes datasets of image measurements that can be obtained via a bespoke software, described herein, that automates spheroid imaging and quantification using the Nikon A1R Confocal Laser Scanning Microscope. However, templates are provided to enable users to input spheroid image measurements obtained by user-preferred methods. SpheroidAnalyseR facilitates outlier identification and removal followed by graphical visualization of spheroid measurements across multiple predefined parameters such as time, cell-type and treatment(s). Spheroid imaging and analysis can, thus, be reduced from hours to minutes, removing the requirement for substantial manual data manipulation in a spreadsheet application. The combination of spheroid generation in 96-well ultra-low attachment microplates, imaging using our bespoke software, and analysis using SpheroidAnalyseR toolkit allows high throughput, longitudinal quantification of 3D spheroid growth whilst minimizing user input and significantly improving the efficiency and reproducibility of data analysis. Our bespoke imaging software is available from https://github.com/GliomaGenomics. SpheroidAnalyseR is available at https://spheroidanalyser.leeds.ac.uk, and the source code found at https://github.com/GliomaGenomics.

Keywords: R Shiny; confocal; organoids; spheroids.