High content analysis of histone acetylation in human cells and tissues

There is increasing demand for automated image analysis of cell nuclei to be fast, objective and informative. Here, we have developed a high content analysis method for quantifying histone acetylation within any given population of cells. To demonstrate the utility of this method we quantified the effect of valproic acid (VPA) on histone H3 acetylation levels in SK-N-SH cells, a human neuroblastomal cell line. VPA, commonly used for treatment of bipolar disorder and epilepsy, has also been shown to act as a histone deacetylase inhibitor (HDACi), and to maintain the N-terminals of susceptible histones in an acetylated and transcriptionally active state. The Discovery-1™ (Molecular Devices) platform was used for automated image acquisition of immunolabelled cells. Multiple parameters of labelled nuclei were analysed in 1.82 s per image using the built-in count nuclei assay from MetaMorph™ (Molecular Devices) image analysis software. Data were presented in two forms: summary graphs or heterogeneity profiles using frequency distributions within GraphPad Prism (SmartDrawNet). Results showed that VPA increased histone H3 acetylation in a concentration- and time-dependent manner in SK-N-SH cells. The same analysis was shown to accurately quantify histone acetylation changes in human tissue sections also. Trichostatin A, a known HDACi was used to validate VPA action. Western blotting was used to validate the specificity of the antibodies. Overall these data demonstrate that this novel method for quantifying average treatment effects and the heterogeneity within any given population of cells, is fast, reproducible and can be applied to many different cellular contexts (immunocyto- and immunohisto-chemistry).

Research highlights▶ High content image analysis tool to quantify multiparametric changes in labeled cells. ▶ 3 days processing time (from cell plating to statistical assessment) of drug effects in vitro. ▶ Simple tool for assessment of epigenetic cell state in many different biological contexts.