Dataset Information

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry.

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.

SUBMITTER: Malavolta M

PROVIDER: S-EPMC9406876 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Publications

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry.

Malavolta Marco M Giacconi Robertina R Piacenza Francesco F Strizzi Sergio S Cardelli Maurizio M Bigossi Giorgia G Marcozzi Serena S Tiano Luca L Marcheggiani Fabio F Matacchione Giulia G Giuliani Angelica A Olivieri Fabiola F Crivellari Ilaria I Beltrami Antonio Paolo AP Serra Alessandro A Demaria Marco M Provinciali Mauro M

Cells 20220812 16

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 ...[more]

PMID: 36010584

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Project description:Mitochondria are highly dynamic organelles whose fusion and fission play an increasingly important role in a number of both normal and pathological cellular functions. Despite the increased interest in mitochondrial dynamics, robust, and quantitative methods to analyze mitochondrial fusion and fission activity in intact cells have not been developed. The current state-of-the art method to measure mitochondrial fusion activity is the polyethylene glycol (PEG) fusion assay in which cells expressing distinct mitochondrially-targeted fluorescent proteins (FPs) are fused together and mitochondrial fusion activity is determined by the rate at which color mixing occurs. Although this assay is useful, cell-cell fusion events are rare, and finding the number of fused cells required to generate statistically rigorous data is both tedious and time-consuming. Furthermore, the data-collection methods available for fluorescence microscopy lead to inherent selection biases that are difficult to control for. To that end, we have developed an unbiased and high-throughput method to detect, image, and analyze fused cells using the Amnis ImagestreamX™ MKII. With IDEAS™ software, we developed algorithms for identifying the fused cells (two nuclei within a single cell), distinguishing them from cell aggregates. Additionally, using the fluorescence localization of the mitochondrially-targeted fluorescent proteins (YFP and DsRed), we applied a modified co-localization algorithm to identify those cells that had a high co-localization score indicating mitochondrial fusion activity. These algorithms were tested using negative controls (FPs associated with fusion deficient mitochondria) and positive controls (cells expressing both FPs in the same mitochondria). Once validated these algorithms could be applied to test samples to evaluate the degree of mitochondrial fusion in cells with various genetic mutations. Ultimately, this new method is the first robust, high-throughput way to directly measure mitochondrial fusion in intact cells. Given how many cellular processes are being linked mitochondrial dynamics, this technique will provide a powerful new tool in the study of this important organelle. © 2016 International Society for Advancement of Cytometry.

Dataset Information

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry.

Publications

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry.

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