The characterization of chemogenomic libraries with respect to their general effect on cellular health represents essential data for the annotation of phenotypic responses. Here, we describe a multidimensional high-content live cell assay that allows to examine cell viability in different cell lines, based on their nuclear morphology as well as modulation of small molecules of tubulin structure, mitochondrial health, and membrane integrity. The protocol monitors cells during a time course of 48 h using osteosarcoma cells, human embryonic kidney cells, and untransformed human fibroblasts as an example. The described protocol can be easily established and it can be adapted to other cell lines or other parameters important for cellular health.
Keywords: Cell viability; High-content imaging; Machine learning; Multiplex; Phenotypic screening.
© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.