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Inducible CRISPR–Cas9 screening platform to interrogate non-proliferative cellular states

Nature Protocols (2025)Cite this article

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Abstract

CRISPR screens have revolutionized the study of diverse biological processes, particularly in cancer research. Both pooled and arrayed CRISPR screens have facilitated the identification of essential genes for cell survival and proliferation, drivers of drug resistance and synthetic lethal interactions. However, applying loss-of-function CRISPR screening to non-proliferative states remains challenging, largely because of slower editing and the poor sensitivity of identifying guide RNAs that ‘drop out’ in a population of non-dividing cells. Here, we present a detailed protocol to accomplish this, using an inducible Cas9 system that offers precise temporal control over Cas9 expression. This inducible system allows gene editing to occur only after the non-proliferative state is fully established. We describe the complete procedure for generating an inducible Cas9-expressing model and for measuring editing efficiency by using flow cytometry. In addition, we discuss how to optimize key parameters for performing successful CRISPR screens in various non-proliferative states. We describe a detailed workflow for performing a screen in senescent cells to identify senolytic targets. This protocol is accessible to researchers with experience in molecular biology techniques and can be completed in 8–12 weeks, from the generation of an inducible Cas9 cell line clone to the analysis of a CRISPR screen for hit identification. These techniques can be applied by researchers across different fields, including stem cell differentiation, immune cell development, aging and cancer research.

Key points

  • This advanced inducible Cas9 (iCas9) screening platform provides precise temporal control of genome editing, enabling the initiation of editing only after cells have entered a desired non-proliferative state.

  • It addresses key technical considerations to overcome challenges associated with previous methods, including the speed of editing in non-dividing cells, and how to optimize the signal-to-noise ratio for correct hit identification.

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Fig. 1: Protocol overview.
Fig. 2: Overview of senescence and iCas9 cell line validation.
Fig. 3: Layout of the senolytic inducible CRISPR screen.
Fig. 4: Anticipated results for the inducible CRISPR–Cas9 screening platform.

Data availability

Source data for Fig. 4 have been provided as Supplementary Information. Other data supporting the paper can be found as source data with the primary papers, references4,12. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank members of the Wang, Bernards and Beijersbergen laboratories for helpful discussion and insightful feedback. This work was supported by the 2024ZD0525004 from the National Health Commission of the PRC-Noncommunicable Chronic Diseases-National Science and Technology Major Project (to L.W.); 2024YFA0918403 from the National Key Research and Development Program of China (to L.W.); W2432050, W2421020 and 82372695 from the National Natural Science Foundation of China (to L.W.); 2024A04J6484 from the Guangdong Basic and Applied Basic Research Foundation (to L.W.); YTP-SYSUCC-0055 from the Young Talents Program of Sun Yat-sen University Cancer Center (to L.W.); the European Research Council as ERC-787925 (to R.B.); 19-051-ASP from the Mark Foundation (to R.B.); ASP-II grant-Bernards 2023 (to R.B.); KWF-12539 from the Dutch Cancer Society (to R.B.); LSH-TKI-LSHM20083 from Health Holland (to R.B.); and KWF lnfrastructure lnitiatives ScreeninC 12539 (to R.L.B.).

Author information

Authors and Affiliations

  1. Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Gabriele Casagrande Raffi & Rene Bernards

  2. Division of Molecular Carcinogenesis, NKI Robotics and Screening Center, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Hendrik J. Kuiken, Cor Lieftink & Roderick L. Beijersbergen

  3. State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, China

    Liqin Wang

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  1. Gabriele Casagrande Raffi
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  2. Hendrik J. Kuiken
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  3. Cor Lieftink
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  4. Rene Bernards
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  5. Roderick L. Beijersbergen
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Contributions

G.C.R., R.L.B., R.B., H.J.K., C.L. and L.W. contributed to the conceptualization of the manuscript. All authors contributed to the evaluation, execution, writing and revision of the manuscript.

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Correspondence to Rene Bernards, Roderick L. Beijersbergen or Liqin Wang.

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R.B. and L.W. are shareholders of Oncosence. The other authors declare no competing interests.

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Nature Protocols thanks Roland Rad and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Key references

Wang, L. et al. Nat. Cancer 3, 1284–1299 (2022): https://doi.org/10.1038/s43018-022-00462-2

Casagrande Raffi, G. et al. Proc. Natl Acad. Sci. USA 121, e2417724121 (2024): https://doi.org/10.1073/pnas.2417724121

Chen, M. et al. Cell Rep. Med. 5, 101471 (2024): https://doi.org/10.1016/j.xcrm.2024.101471

Source data

Source Data Fig. 4

Images of SA β-Gal quantification (Fig. 4a, available in cited literature), unprocessed western blots (Fig. 4b), values of curve growth for iCas9 clones (Fig. 4c), unprocessed images and gating strategy for flow cytometry images (Fig. 4d), data for screen analysis (Fig. 4e,f, available as source data in cited literature), values of gene hits for senolytic screen (Fig. 4g) and senescent versus parental arm hit ranking (Fig. 4h)

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Casagrande Raffi, G., Kuiken, H.J., Lieftink, C. et al. Inducible CRISPR–Cas9 screening platform to interrogate non-proliferative cellular states. Nat Protoc (2025). https://doi.org/10.1038/s41596-025-01251-8

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