Fast in vitro protocol for the visualization and quantitative high-throughput analysis of sprouting angiogenesis by confocal microscopy

• Published in: STAR protocols 2021-09, Vol.2 (3), p.100690-100690, Article 100690
• Main Authors: Kempers, Lanette, van der Bijl, Ivo, van Stalborch, Anne-Marieke D., Ponsioen, Bas, Margadant, Coert
• Format: Article
• Language: English
• Subjects: Cell Biology; Cell culture; Cell-based Assays; Developmental biology; High Throughput Screening; Microscopy; Molecular Biology; Protocol
• ISSN: 2666-1667; 2666-1667
• DOI: 10.1016/j.xpro.2021.100690

We describe an optimized, cost-effective, reproducible, and robust protocol to study sprouting angiogenesis in glass-bottom 96-well plates by confocal microscopy, ideal for screening of drug or shRNA libraries. Effective and stable knockdown of gene expression in primary endothelial cells is achieved by lentiviral transduction. Dynamic behavior of individual cells and fluorescent proteins is analyzed by time-lapse imaging, while competitive advantages in tip cell formation are assessed using mixtures of differentially labeled cell populations. Finally, we present a macro for high-throughput analysis. For complete information on the use and execution of this protocol, please refer to van der Bijl et al. (2020) and Kempers et al. (2021). [Display omitted] •High-throughput microscopy analysis of sprouting angiogenesis for drug/shRNA screening•Analysis of dynamic cell and protein behavior during sprouting by time-lapse microscopy•Mosaic assays to image competitive advantages in tip cell behavior•Macro for fast automated quantitative analysis We describe an optimized, cost-effective, reproducible, and robust protocol to study sprouting angiogenesis in glass-bottom 96-well plates by confocal microscopy, ideal for screening of drug or shRNA libraries. Effective and stable knockdown of gene expression in primary endothelial cells is achieved by lentiviral transduction. Dynamic behavior of individual cells and fluorescent proteins is analyzed by time-lapse imaging, while competitive advantages in tip cell formation are assessed using mixtures of differentially labeled cell populations. Finally, we present a macro for high-throughput analysis.