A Fully-Automated Senescence Test (FAST) for the high-throughput quantification of senescence-associated markers
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Abstract
Abstract Cellular senescence is a major driver of aging and age-related diseases. Quantification of senescent cells remains challenging due to the lack of senescence-specific markers and generalist, unbiased methodology. Here, we describe the Fully-Automated Senescence Test (FAST), an image-based method for the high-throughput, single-cell assessment of senescence in cultured cells. FAST quantifies three of the most widely adopted senescence-associated markers for each cell imaged: senescence-associated β-galactosidase activity (SA-β-Gal) using X-Gal, proliferation arrest via lack of 5-ethynyl-2’-deoxyuridine (EdU) incorporation, and enlarged morphology via increased nuclear area. The presented workflow entails microplate image acquisition, image processing, data analysis, and graphing. Standardization was achieved by i) quantifying colorimetric SA-β-Gal via optical density; ii) implementing staining background controls; iii) automating image acquisition, image processing, and data analysis. In addition to the automated threshold-based scoring, a multivariate machine learning approach is provided. We show that FAST accurately quantifies senescence burden and is agnostic to cell type and microscope setup. Moreover, it effectively mitigates false-positive senescence marker staining, a common issue arising from culturing conditions. Using FAST, we compared X-Gal with fluorescent C 12 FDG live-cell SA-β-Gal staining on the single-cell level. We observed only a modest correlation between the two, indicating that those stains are not trivially interchangeable. Finally, we provide proof of concept that our method is suitable for screening compounds that modify senescence burden. This method will be broadly useful to the aging field by enabling rapid, unbiased, and user-friendly quantification of senescence burden in culture, as well as facilitating large-scale experiments that were previously impractical.
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The model of senescence induction using ionizing radiation has been well established and proven to yield highly robust senescence induction.
“In general, this model of senescence induction using ionizing radiation (IR), has been well established and has proven to yield highly robust senescence induction as demonstrated in the Campisi lab [10, 20, 21] and many other labs.”
From Senescent cell heterogeneity and responses to senolytic treatment are related to cell cycle status during senescence induction (2025) · cites this paper as [21]
The Methods (Senescence induction; page unavailable) describe a previously reported ionizing-radiation protocol, and the Results (Automation of the senescence marker scoring; page unavailable) report significant differences in senescence markers between irradiated and control cells. These passages support the use and effectiveness of the model in this study, but do not establish that induction is highly robust across the Campisi lab and many other labs. (LLM, conf=0.83)
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- Authors
- Neri, F., Takajjart, S. N., Lerner, C. A., Desprez, P.-Y., Schilling, B., Campisi, J., & Gerencser, A. A.
- Affiliations
- University of Southern California (US)
- Buck Institute for Research on Aging (US)
- Corresponding author
- Schilling, Birgit
- Gerencser, Akos A.
- ORCID
- Venue
- GeroScience
- Published
- 2024-06-13
- Volume
- 46
- Issue
- 5
- Pages
- 4185-4202
- ISSN
- 2152-4041 (ISSN-L)
- 2509-2723
- PMC
- PMC11336018
- OpenAlex
- W4399644314
- Cited by
- 17
- References
- 46
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 3
- FWCI
- 4.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- GeroScience (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by-nd)
- Funders
- National Institutes of Health
- National Institute on Aging (RF1AG068908, U01AG060906, P01AG017242, P01AG066591, U54AG075932)
- Topics
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Keywords
- cellular senescence, senescence-associated β-galactosidase, EdU incorporation, nuclear area, X-gal staining, aging
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