| Autor: |
Caterina Vianello, Federica Dal Bello, Sang Hun Shin, Sara Schiavon, Camilla Bean, Ana Paula Magalhães Rebelo, Tomáš Knedlík, Emad Norouzi Esfahani, Veronica Costiniti, Rodrigo S. Lacruz, Giuseppina Covello, Fabio Munari, Tommaso Scolaro, Antonella Viola, Elena Rampazzo, Luca Persano, Sara Zumerle, Luca Scorrano, Alessio Gianelle, Marta Giacomello |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Cells; Volume 12; Issue 7; Pages: 1089 |
| Popis: |
Recent proteomic, metabolomic, and transcriptomic studies have highlighted a connection between changes in mitochondria physiology and cellular pathophysiological mechanisms. Secondary assays to assess the function of these organelles appear fundamental to validate these -omics findings. Although mitochondrial membrane potential is widely recognized as an indicator of mitochondrial activity, high-content imaging-based approaches coupled to multiparametric to measure it have not been established yet. In this paper, we describe a methodology for the unbiased high-throughput quantification of mitochondrial membrane potential in vitro, which is suitable for 2D to 3D models. We successfully used our method to analyze mitochondrial membrane potential in monolayers of human fibroblasts, neural stem cells, spheroids, and isolated muscle fibers. Moreover, by combining automated image analysis and machine learning, we were able to discriminate melanoma cells from macrophages in co-culture and to analyze the subpopulations separately. Our data demonstrated that our method is a widely applicable strategy for large-scale profiling of mitochondrial activity. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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