Litcius/Paper detail

Automated multimodal fluorescence microscopy for hyperplex spatial-proteomics: Coupling microfluidic-based immunofluorescence to high resolution, high sensitivity, three-dimensional analysis of histological slides

Laura Furia, Simone Pelicci, Federica Perillo, Maddalena M. Bolognesi, Pier Giuseppe Pelicci, Federica Facciotti, Giorgio Cattoretti, Mario Faretta

2022Frontiers in Oncology10 citationsDOIOpen Access PDF

Abstract

transcriptomics are now providing revolutionary tools to achieve the comprehension of the molecular basis of cancer and to progress towards personalized medicine to fight the disease. The complexity of these tasks requires a continuous interplay among different technologies during all the phases of the experimental procedures. New tools are thus needed and their characterization in terms of performances and limits is mandatory to reach the best resolution and sensitivity. We propose here a new experimental pipeline to obtain an optimized costs-to-benefits ratio thanks to the alternate employment of automated and manual procedures during all the phases of a multiplexing experiment from sample preparation to image collection and analysis. A comparison between ultra-fast and automated immunofluorescence staining and standard staining protocols has been carried out to compare the performances in terms of antigen saturation, background, signal-to-noise ratio and total duration. We then developed specific computational tools to collect data by automated analysis-driven fluorescence microscopy. Computer assisted selection of targeted areas with variable magnification and resolution allows employing confocal microscopy for a 3D high resolution analysis. Spatial resolution and sensitivity were thus maximized in a framework where the amount of stored data and the total requested time for the procedure were optimized and reduced with respect to a standard experimental approach.

Topics & Concepts

Computer scienceMicroscopySensitivity (control systems)MultiplexingMicroscopeResolution (logic)Artificial intelligenceData miningBiomedical engineeringBiological systemPattern recognition (psychology)OpticsPhysicsElectronic engineeringBiologyMedicineTelecommunicationsEngineeringAdvanced Biosensing Techniques and ApplicationsSingle-cell and spatial transcriptomicsAdvanced Fluorescence Microscopy Techniques