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Spatial mapping of cellular senescence: emerging challenges and opportunities

Nature Aging volume 3, pages 776–790 (2023)Cite this article

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Abstract

Cellular senescence is a well-established driver of aging and age-related diseases. There are many challenges to mapping senescent cells in tissues such as the absence of specific markers and their relatively low abundance and vast heterogeneity. Single-cell technologies have allowed unprecedented characterization of senescence; however, many methodologies fail to provide spatial insights. The spatial component is essential, as senescent cells communicate with neighboring cells, impacting their function and the composition of extracellular space. The Cellular Senescence Network (SenNet), a National Institutes of Health (NIH) Common Fund initiative, aims to map senescent cells across the lifespan of humans and mice. Here, we provide a comprehensive review of the existing and emerging methodologies for spatial imaging and their application toward mapping senescent cells. Moreover, we discuss the limitations and challenges inherent to each technology. We argue that the development of spatially resolved methods is essential toward the goal of attaining an atlas of senescent cells.

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Fig. 1: Senescence is a complex cell fate that alters almost every aspect of cell biology.
Fig. 2: Senescence communicates with neighboring cells and alters their function via the SASP.
Fig. 3: Spatially resolved methods for mapping senescent cells and studying senescence-associated pathology.
Fig. 4: Examples of exploratory strategies used by the University of Minnesota Tissue Mapping Center to identify senescence in liver samples using both the 10x Genomics Visium and the NanoString GeoMx platforms.
Fig. 5: Image data analysis of senescent cells.
Fig. 6: Nuclear morphology predicts senescence in tissues.

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Acknowledgements

This research was supported by the NIH Common Fund, through the Office of Strategic Coordination and the Office of the NIH Director under awards UG3CA268103 (J.F.P., A.B.L., S.V., D.J.), U54AG075931 (A.U.G., A.L.M., D.B., H.C., J.K.A., M.B., M. Königshoff., O.E., Q.H., T.K.), UG3CA268202 (N.N.), U54AG075941 (J.H.C.), UG3CA268091 (J.H.L.), UG3CA268096 (R.D., X.F.), U54AG075931 (Z.B.-J.), U24CA268108 (Z.B.-J.), U54AG076041 (L.J.N., A.C.N., E.L.T., S.P., F.R., G.B.), U54AG075936 (A.R.Z., Z.J.), U54AG079758 (P.D.A., Q.Z., R.A.P.), U54AG076040 (H.P., J.P.), U54 AG075932 (D.F., A.A.G., C.B., F.W., I.H.), UG3CA268112 (V.S., M. Kumar.). We thank A. Impagliazzo for her work on the illustrations.

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Authors and Affiliations

  1. Aging Institute, University of Pittsburgh School of Medicine/UPMC and Division of Pulmonary, Allergy and Critical Care Medicine, Allergy, Critical Care and Sleep Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA

    Aditi U. Gurkar, Delphine Beaulieu, Jonathan K. Alder, Melanie Königshoff, Marta Bueno, Oliver Eickelberg & Qianjiang Hu

  2. Buck Institute for Research on Aging, Novato, CA, USA

    Akos A. Gerencser, Christopher Benz, David Furman, Fei Wu, Indra Heckenbach & Morten Scheibye-Knudsen

  3. Dorothy M. Davis Heart and Lung Research Institute, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, the Ohio State University, Columbus, OH, USA

    Ana L. Mora & Timur Khaliullin

  4. Department of Laboratory Medicine and Pathology, Department of Biochemistry, Molecular Biology and Biophysics, Department of Neuroscience and Institute on the Biology of Aging and Metabolism, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA

    Andrew C. Nelson, Elizabeth L. Thompson, Fernanda Rodriguez, Grant Barthel, Laura J. Niedernhofer, Samuel Peters & Thomas Pengo

  5. Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine and Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA

    Anru R. Zhang & Zhicheng Ji

  6. Department of Physiology and Biomedical Engineering, Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, MN, USA

    Anthony B. Lagnado, Diana Jurk, Stella Victorelli & João F. Passos

  7. Department of Biomedical Engineering, Yale University, New Haven, CT, USA

    Archibald Enninful

  8. Stanford 1000 Immunomes Project, Stanford School of Medicine, Stanford University, Stanford, CA, USA

    David Furman

  9. Instituto de Investigaciones en Medicina Traslacional (IIMT), Universidad Austral, Pilar, Argentina

    David Furman

  10. Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

    Hao Chen & Ziv Bar-Joseph

  11. Columbia University Irving Medical Center and New York Genome Center, Columbia University, New York, NY, USA

    Hemali Phatnani & Joana Petrescu

  12. The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA

    Jeffrey H. Chuang

  13. Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA

    Jeremy Horrell, Miiko Sokka & Nicola Neretti

  14. Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA

    Jun Hee Lee

  15. Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, Stanford, CA, USA

    Manoj Kumar & Vidyani Suryadevara

  16. Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA

    Peter D. Adams & Rebecca A. Porritt

  17. University of California, San Diego, CA, USA

    Quan Zhu

  18. Department of Biochemistry, Institute for Protein Design and Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, WA, USA

    Runze Dong & Xiaonan Fu

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Contributions

All authors contributed to writing the manuscript and reviewed and approved of its submission for publication. A.U.G., M.B., V.S., O.E., J.K.A. and J.F.P. contributed to the Main; J.F.P., D.J., Q.H., D.B., S.V., N.N., M.S., J.H., J.P. and H.P. contributed to Low-plex imaging methods; G.B., F.R., A.C.N., A.B.L., M. Kumar., L.J.N., S.P. and E.L.T. contributed to High-plex imaging methods; A.E., J.H.L., T.K., A.L.M., X.F., R.D., A.C.N., P.D.A., Q.Z. and R.A.P. contributed to Spatial transcriptomics; J.H.C., H.C., T.P., Z.J., Z.B.-J and A.A.G. contributed to Image data analysis of senescent cells; A.A.G., C.B., D.F., F.W., M.S.K. and I.H. contributed to Use of deep learning methods to identify senescent cells. J.F.P. designed and coordinated the writing of the Review.

Corresponding author

Correspondence to João F. Passos.

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Competing interests

J.H.L. is an inventor on pending patent applications related to Seq-Scope. All other authors declare no competing interests.

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Nature Aging thanks Jesus Gil, Kristina Kirschner, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Gurkar, A.U., Gerencser, A.A., Mora, A.L. et al. Spatial mapping of cellular senescence: emerging challenges and opportunities. Nat Aging 3, 776–790 (2023). https://doi.org/10.1038/s43587-023-00446-6

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