Monitoring drug-induced signaling inhibition and adaptive resistance by live-cell microscopy

Genetically identical cells that are experiencing similar extracellular conditions can still be phenotypically distinct from one another. Phenotypic variation in key traits can impact cellular fitness and have clinical importance, as has been reported for variation in bacterial persistence during antibiotic treatment and variation in drug resistance among cancer cells. Cell-cell variability is typically studied with methods amenable to high-throughput measurements such as flow-cytometry, yet these methods are unsuitable for monitoring dynamic phenotypes that change and evolve over time. Cellular signaling represents an important class of dynamic phenotypes that remain inaccessible for exploration with end-time point measurements. Here, we describe an experimental and computational pipeline for quantifying signaling activity using live-cell fluorescent reporters. Importantly, the method we outline for automated image analysis builds on free software with a graphical user interface and does not require any training in computer programing. This method can be used to track hundreds of individual cells in time-lapse microscopy experiments and is therefore suitable for detecting cell-cell variation in signaling dynamics, as we recently showed for the Ras/ERK cascade in melanoma cell-lines.