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Article

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry

by
Marco Malavolta
1,*,
Robertina Giacconi
1,
Francesco Piacenza
1,
Sergio Strizzi
1,
Maurizio Cardelli
1,
Giorgia Bigossi
1,
Serena Marcozzi
1,
Luca Tiano
2,
Fabio Marcheggiani
2,
Giulia Matacchione
3,
Angelica Giuliani
3,
Fabiola Olivieri
3,4,
Ilaria Crivellari
5,
Antonio Paolo Beltrami
5,
Alessandro Serra
6,
Marco Demaria
7 and
Mauro Provinciali
1
1
Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy
2
Department of Life and Environmental Sciences, Polytechnical University of Marche, 60121 Ancona, Italy
3
Department of Clinical and Molecular Sciences, DISCLIMO, Polytechnical University of Marche, 60121 Ancona, Italy
4
Center of Clinical Pathology and Innovative Therapy, IRCCS INRCA, 60121 Ancona, Italy
5
Department of Medicine (DAME), University of Udine, 33100 Udine, Italy
6
Luminex B.V., Het Zuiderkruis 1, 5215 MV ‘s-Hertogenbosch, The Netherlands
7
European Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen (UMCG), 9713 AV Groningen, The Netherlands
*
Author to whom correspondence should be addressed.
Cells 2022, 11(16), 2506; https://doi.org/10.3390/cells11162506
Submission received: 20 June 2022 / Revised: 8 August 2022 / Accepted: 10 August 2022 / Published: 12 August 2022
(This article belongs to the Collection Molecular Mechanisms to Target Cellular Senescence in Aging and Disease)
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Abstract

Cellular senescence is a hallmark of aging and a promising target for therapeutic approaches. The identification of senescent cells requires multiple biomarkers and complex experimental procedures, resulting in increased variability and reduced sensitivity. Here, we propose a simple and broadly applicable imaging flow cytometry (IFC) method. This method is based on measuring autofluorescence and morphological parameters and on applying recent artificial intelligence (AI) and machine learning (ML) tools. We show that the results of this method are superior to those obtained measuring the classical senescence marker, senescence-associated beta-galactosidase (SA-β-Gal). We provide evidence that this method has the potential for diagnostic or prognostic applications as it was able to detect senescence in cardiac pericytes isolated from the hearts of patients affected by end-stage heart failure. We additionally demonstrate that it can be used to quantify senescence “in vivo” and can be used to evaluate the effects of senolytic compounds. We conclude that this method can be used as a simple and fast senescence assay independently of the origin of the cells and the procedure to induce senescence.
Keywords: cellular senescence; imaging flow cytometry; senolytics; replicative senescence; artificial intelligence and machine learning cellular senescence; imaging flow cytometry; senolytics; replicative senescence; artificial intelligence and machine learning

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MDPI and ACS Style

Malavolta, M.; Giacconi, R.; Piacenza, F.; Strizzi, S.; Cardelli, M.; Bigossi, G.; Marcozzi, S.; Tiano, L.; Marcheggiani, F.; Matacchione, G.; et al. Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry. Cells 2022, 11, 2506. https://doi.org/10.3390/cells11162506

AMA Style

Malavolta M, Giacconi R, Piacenza F, Strizzi S, Cardelli M, Bigossi G, Marcozzi S, Tiano L, Marcheggiani F, Matacchione G, et al. Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry. Cells. 2022; 11(16):2506. https://doi.org/10.3390/cells11162506

Chicago/Turabian Style

Malavolta, Marco, Robertina Giacconi, Francesco Piacenza, Sergio Strizzi, Maurizio Cardelli, Giorgia Bigossi, Serena Marcozzi, Luca Tiano, Fabio Marcheggiani, Giulia Matacchione, and et al. 2022. "Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry" Cells 11, no. 16: 2506. https://doi.org/10.3390/cells11162506

APA Style

Malavolta, M., Giacconi, R., Piacenza, F., Strizzi, S., Cardelli, M., Bigossi, G., Marcozzi, S., Tiano, L., Marcheggiani, F., Matacchione, G., Giuliani, A., Olivieri, F., Crivellari, I., Beltrami, A. P., Serra, A., Demaria, M., & Provinciali, M. (2022). Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry. Cells, 11(16), 2506. https://doi.org/10.3390/cells11162506

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