Hardware automation and software development have allowed a dramatic increase of throughput in both acquisition and analysis of images by associating an optimized statistical significance with fluorescence microscopy. Despite the numerous common points between fluorescence microscopy and flow cytometry (FCM), the enormous amount of applications developed for the latter have found relatively low space among the modern high-resolution imaging techniques. With the aim to fill this gap, we developed a novel computational platform named A.M.I.CO. (Automated Microscopy for Image-Cytometry) for the quantitative analysis of images from widefield and confocal robotized microscopes. Thanks to the setting up of both staining protocols and analysis procedures, we were able to recapitulate many FCM assays. In particular, we focused on the measurement of DNA content and the reconstruction of cell-cycle profiles with optimal parameters. Standard automated microscopes were employed at the highest optical resolution (200 nm), and white-light sources made it possible to perform an efficient multiparameter analysis. DNA-and protein-content measurements were complemented with image-derived information on their intracellular spatial distribution. Notably, the developed tools create a direct link between image-analysis and acquisition. It is therefore possible to isolate target populations according to a definite quantitative profile, and to relocate physically them for diffraction-limited data acquisition. Thanks to its flexibility and analysis-driven acquisition, A.M.I.CO. can integrate flow, image-stream and laser-scanning cytometry analysis, providing high-resolution intracellular analysis with a previously unreached statistical relevance. ' 2013 International
Society for Advancement of Cytometry
Key termsimage-cytometry; cell-cycle; automated microscopy; image analysis LIMITED sample availability, as for material of clinical origin, and a poor statistical representation of targeted cell populations, for example, stem cells, can make the comprehension of biological heterogeneity a very challenging task (1-4). High-content approaches have been consequently developed to extend the number of simultaneously analyzable parameters (5-7).Flow cytometry (FCM) is a powerful technique that provides statistically relevant measurements. Quantification at single-cell level, elevated content, fast acquisition, and contained analysis time make it a very valuable tool for the identification of rare cell populations. In addition, enormous advances in limiting the required amount of sample per analysis have also been achieved by system miniaturization (7-11).This excellent "statistical resolution" is, however, coupled to a complete absence of an intracellular view and, to date, fluorescence microscopy maintains its leadership in providing a high-resolution description of the inner cell compartments. Nevertheless, technological efforts have tried to fill the imaging gap between FCM and fluorescence microscopy, leading to the development of ...