Federica Dal Bello

Mrs. Federica Dal Bello

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 July 2020 in Cells
Verified
Journal Article
Open access
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Ana Paula Magalhães RebeloAna Paula Magalhães Rebelo
Ana Paula Magalhães Rebelo
FBFederica Dal Bello
Federica Dal Bello
Tomas KnedlikTomas Knedlik
Tomas Knedlik
NKNatasha Kaar
Natasha Kaar
FVFabio Volpin
Fabio Volpin
Marta GiacomelloMarta Giacomello
Marta Giacomello
Contact sites between mitochondria and endoplasmic reticulum (ER) are points in which the two organelles are in close proximity. Due to their structural and functional complexity, their exploitation as pharmacological targets has never been considered so far. Notwithstanding, the number of compounds described to target proteins residing at these interfaces either directly or indirectly is rising. Here we provide original insight into mitochondria–ER contact sites (MERCs), with a comprehensive overview of the current MERCs pharmacology. Importantly, we discuss the considerable potential of MERCs to become a druggable target for the development of novel therapeutic strategies.

5 April 2023 in Cells
Verified
Journal Article
Open access
PDF file
CVCaterina Vianello
Caterina Vianello
FBFederica Dal Bello
Federica Dal Bello
SSSANG HUN SHIN
SANG HUN SHIN
SSSara Schiavon
Sara Schiavon
Camilla BeanCamilla Bean
Camilla Bean
Marta GiacomelloMarta Giacomello
Marta Giacomello
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.