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Angeli, V.

Publications and source records attributed to Angeli, V..

2 recordsLinked to original sources

Microdomes: Micro-engineered Microdome arrays enable standardised and shear-free 3D biology with full-spectrum optical imaging compatibility

Three-dimensional cellular models such as organoids and spheroids hold major promise for developmental biology, disease modelling and precision medicine, yet their large-scale production and analysis remain constrained by handling-induced shear stress, sample fragility, positional instability and limited compatibility with advanced imaging workflows. Here, we introduce Microdomes, dense arrays of open-top, dome-shaped microcavities. Each cavity holds a single specimen in its own miniature aquarium, accessed through a narrow apical opening that admits cells, medium, matrix and staining reagents while shielding it from the shear generated during routine pipetting. Each Microdomes chip accommodates more than 100 spheroids or organoids, supporting diverse cell types, co-culture formats and both matrix-free and matrix-embedded culture. All specimens are retained through prolonged culture, repeated medium exchange, fixation and immunostaining. Because every specimen occupies a fixed, addressable position against a thin transparent film, the same spheroid can be relocated and re-imaged over weeks of culture and across microscopes, from array-wide overviews to subcellular details, without transfer, embedding or other perturbation. Microdomes also support AI-based automated segmentation, from whole-spheroid outlines to individual nuclei in 3D, using common image analysis software. Microdomes thereby turn each array into a self-contained quality control unit, providing specimen-level traceability that organoid production pipelines currently lack.

cell biology↗

Open Source ImmGen: network perspective on metabolic diversity among mononuclear phagocytes

We dissect metabolic variability of mononuclear phagocyte (MNP) subpopulations across different tissues through integrative analysis of three large scale datasets. Specifically, we introduce ImmGen MNP Open Source dataset that profiled 337 samples and extended previous ImmGen effort which included 202 samples of mononuclear phagocytes and their progenitors. Next, we analysed Tabula Muris Senis dataset to extract data for 51,364 myeloid cells from 18 tissues. Taken together, a compendium of data assembled in this work covers phagocytic populations found across 38 different tissues. To analyse common metabolic features, we developed novel network-based computational approach for unbiased identification of key metabolic subnetworks based on cellular transcriptional profiles in large-scale datasets. Using ImmGen MNP Open Source dataset as baseline, we define 9 metabolic subnetworks that encapsulate the metabolic differences within mononuclear phagocytes, and demonstrate that these features are robustly found across all three datasets, including lipid metabolism, cholesterol biosynthesis, glycolysis, and a set of fatty acid related metabolic pathways, as well as nucleotide and folate metabolism. We systematically define major features specific to macrophage and dendritic cell subpopulations. Among other things, we find that cholesterol synthesis appears particularly active within the migratory dendritic cells. We demonstrate that interference with this pathway through statins administration diminishes migratory capacity of the dendritic cells in vivo. This result demonstrates the power of our approach and highlights importance of metabolic diversity among mononuclear phagocytes.

immunology↗