Optical microscopy provides many important readouts for cell-based studies.  Increasingly for drug discovery and for systems biology there is an increasing desire to translate microscopy-based studies of cell biology to automated higher throughput measurements or assays. Compared to manual microscopy experiments, the automated meaurement of 1000s of cells, imaged in 100s of fields of view, confers vastly increased statistical robustness of the subsequent analysis and caneliminate operator bias. Conventional high throughput screening (HTS) approaches, e.g. using flow cytometry or multiwell plate readers, can enable the rapid measurement of fluorescence from of tens of thousands of cells but such techniques typically provide no sub-cellular image data. Increasingly, there is interest in fluorescence and other imaging assays implemented in automated multiwell plate microscopes or imaging cytometers to facilitate high content analysis (HCA) - the automated imaging of fixed or live samples with subcellular resolution at high throughput. Such HCA instrumentation must enable hundreds to thousands of microscopy images to be obtained with minimum user intervention and typically automated acquisition is combined with automated sophisticated image analysis routines. This presents significant challenges in terms of data acquisition, analysis and storage, but enables scientific questions to be addressed on an unprecedented scale and HCA is being increasingly utilised in academic research as well as in the pharmaceutical industry. The power of HCA is illustrated by assays based on automated time lapse microscopy of live cells systematically modified, e.g., by siRNA to silence specific genes, that screen for candidates associated with particular phenotypes. This was exemplified at a high level of sophistication by the “Mitocheck” assay1 to identify the genes involved in mitosis, and today screens are envisaged based on automated imaging whole organisms such as zebrafish2. We have been particularly interested in developing FLIM-based HCA technology to screen for protein interactions and other cell signalling processes using FRET-based readouts and in extending HCA to super-resolved microscopy and HCA of 3-D cell cultures and other disease models. 

1 Neumann, B., Held, M., Liebel, U., Erfle, H., Rogers, P., Pepperkok, R. and Ellenberg, J., Nature Methods, 3 (2006) 385
2 Pardo-Martin, C., Chang, T.-Y., Koo, B. K., Gilleland, C. L., Wasserman, S. C. and Yanik, M. F., Nature Methods, 7 (2010) 634