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A computational platform for robotized fluorescence microscopy (I): High‐content image‐based cell‐cycle analysis
Author(s) -
Furia Laura,
Pelicci Pier Giuseppe,
Faretta Mario
Publication year - 2013
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.22266
Subject(s) - cytometry , computer science , microscopy , fluorescence microscope , image analysis , confocal , microscope , high content screening , computer vision , artificial intelligence , flow cytometry , image processing , digital image , optics , fluorescence , chemistry , biology , image (mathematics) , physics , microbiology and biotechnology , cell , biochemistry
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 fulfill 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 © 2012 International Society for Advancement of Cytometry