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Fluorescence lifetime clocks quantify senescence and aging

Nature Aging volume 5, pages 2532–2545 (2025) Cite this article

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Abstract

Epigenetic and omics-based clocks have provided invaluable tools to quantify aging, yet these clocks do not provide direct readouts of aging in real-time in living systems. As methylation changes in nucleolar ribosomal DNA are reliably associated with aging and cellular senescence, we hypothesized that shifts in rRNA species could be leveraged to generate image-based clocks using selective dyes. Here we engineer sensitive and photostable hybrid polymethine dyes selective for rRNA. We present a fluorescence lifetime imaging strategy to visually quantify age- and cellular senescence-dependent nucleolar RNA changes that bypasses requirements for extensive sample preparation such as DNA isolation and enables in vivo, real-time age quantification. We demonstrate resolution through cellular to organismal scales and demonstrate translatability by generating clocks from cells and tissues, as well as Caenorhabditis elegans, mice and human samples. Our fluorescence lifetime imaging strategy thus enables in vivo measurements of aging and senescence and expands the toolbox for aging biology research and translation.

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Fig. 1: Engineering FLPRNA dyes and in vitro characterization.
The alternative text for this image may have been generated using AI.
Fig. 2: S-FLIM in living cells.
The alternative text for this image may have been generated using AI.
Fig. 3: Identifying early TIS and quantitatively screening antineoplastic drugs with different propensities to induce TIS.
The alternative text for this image may have been generated using AI.
Fig. 4: Using S-FLIM to generate fluorescence lifetime aging clocks.
The alternative text for this image may have been generated using AI.
Fig. 5: S-FLIM enables real-time identifying of dynamic aging of living C. elegans.
The alternative text for this image may have been generated using AI.

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Data availability

RNA-sequencing data are publicly available here: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1311725 and bisulfite sequencing (DNA methylation) data are publicly available here: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1312265. Source data are provided. All data supporting the current study are available within the paper and its Supplementary Information or from the corresponding author upon reasonable request.

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Acknowledgements

This work was supported by National Key Research and Development Program (2023YFA1802000 to Z.G.), NSFC/China (22225805, 32121005, 32394001, T2488302 and 22378122 to Z.G., Z.G., Z.G., W.-H.Z. and C.Y., respectively), Shanghai Science and Technology Innovation Action Plan (No. 23J21901600 to Z.G.), Shanghai Frontier Science Research Base of Optogenetic Techniques for Cell Metabolism (Shanghai Municipal Education Commission, grant 2021 Sci & Tech 03-28 to Z.G.), and Science and Technology Commission of Shanghai Municipality (grant No. 24DX1400200 to Z.G.). We thank M. Zhu (Renji Hospital, Shanghai Jiao Tong University) for carrying out volunteer in different age recruitment and sample collection, and A. Shao (Jiangnan University), M. Zhao, J. Huang, Y. Zhang, J. Yang, W. Zhang and X. Zhao (East China University of Science and Technology) for culturing cells.

Author information

Author notes

  1. These authors contributed equally: Chenxu Yan, Caiqi Liu.

Authors and Affiliations

  1. Key Laboratory for Advanced Materials and Joint International Research Laboratory of Precision Chemistry and Molecular Engineering, Feringa Nobel Prize Scientist Joint Research Center, Institute of Fine Chemicals, Frontiers Science Center for Materiobiology and Dynamic Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, China

    Chenxu Yan, Caiqi Liu, Xingyuan Zhao, Sirui Lu, Xiaoqing Fu, Wennan Li, Juan Li, Dan Li, Yongkang Yao, Yutao Zhang, Wei-Hong Zhu & Zhiqian Guo

  2. School of Life Science and Technology, ShanghaiTech University, Shanghai, China

    Bofang Liu & Huanhu Zhu

  3. State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China

    Qiaoqiao Zheng, Ping Shi & Zhiqian Guo

  4. Center of Photosensitive Chemicals Engineering, East China University of Science and Technology, Shanghai, China

    Wei-Hong Zhu

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  1. Chenxu Yan
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Contributions

All the experiments were conducted by C.Y., C.L., X.Z., S.L., X.F., W.L., J.L., D.L., Y.Y. and Y.Z., with the supervision of W.-H.Z. and Z.G. B.L. and H.Z. provided useful ideas in designing worm experiments. Q.Z. and P.S. provided technical support in Western blot, RT-qPCR and RNA gel electrophoresis. All authors analyzed the data and contributed to the paper writing.

Corresponding author

Correspondence to Zhiqian Guo.

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Nature Aging thanks Wei Wang, Yuan Guo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 S-FLIM for sensing the micropolarity governed by senescence-dependent mature/pre rRNA ratios.

a, Schematic of the S-FLLIM approach for quantitative sensing and real-time tracking of senescence/aging in living cells. b, S-FLIM for multiscale aging biology applications: identifying cellular senescence in living cells and fresh tissues; tracking a “fluorescence lifetime clock” for mouse and human; identifying longevity phenotypes based on the fluorescence lifetime clock for living C. elegans. c, Schematic diagram of ribosomal RNA (rRNA) processing. In the nucleolus, ribosomal DNA (rDNA) is transcribed to form pre-rRNA, which is further sheared and processed to form mature rRNA (mainly including 28s rRNA, 18s rRNA), and they assemble with ribosomal proteins. d, e, Reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis demonstrates that pre-rRNA content decreased in both senescent A549 (d) and 293T (e). p = 1.81 × 10−5 for Doxo group, p = 4.88 × 10−5 for MLN4924 group in d; p = 1.04 × 10−7 for Doxo group, p = 2.75 × 10−6 for MLN4924 group in e. Data are presented as mean values ± s.d. from three independent biological replicates. f, g, RNA gel electrophoresis analysis demonstrates that the ratio of 28s rRNA/pre-rRNA content increased in senescent A549. Data are presented as mean values ± s.d. from three independent biological replicates. p = 0.00620 for Doxo group, p = 0.00548 for MLN4924 group in g. h-j, FLIM images (h) and fluorescence lifetime statistics (i and j) of proliferating or senescent HeLa cells’ nucleoli; FLP1 or FLP4 (10 μM) was added 1 h prior to imaging. FLIM results clearly show that only micropolarity-sensitive FLP1 exhibits an obvious difference in fluorescence lifetime in the nucleoli of proliferating (3.0 ns) and senescent cells (1.0 ns), while FLP4 exhibits the same fluorescence lifetime (1.5 ns) in the nucleoli. Data in i are presented as mean values ± s.d. from n = 10 independent biological replicates. Data in j are presented as mean values ± s.d. from independent biological replicates (n = 12 for control group, n = 10 for Doxo group). Statistical significance was calculated using two tailed t-test. *P<0.05, **P<0.01, ***P<0.001.

Source Data

Extended Data Fig. 2 Cellular Model of pre-rRNA/ mature rRNA decrease in nucleoli.

We also conducted a separate experiment in which cells were exposed to the transcriptional inhibitor actinomycin D (0.2 μM [ActD] for 2 hours). Consistent with our expectation, RNA denaturing gel electrophoresis and qPCR showed that cells treated with ActD had a much higher mature/pre rRNA ratio compared to untreated control cells. a-c, Reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis demonstrates that pre-rRNA content decreased in cells exposed to the transcriptional inhibitor actinomycin D (0.2 μM [ActD] for 2 hours). p = 1.28 × 10−4 in a, p = 6.70 × 10−4 in b, p = 2.06 × 10−7 in c. d, e, RNA gel electrophoresis analysis demonstrates that the ratio of 28s rRNA/pre-rRNA content increased in cells exposed to ActD. Data in a-e are presented as mean values ± s.d. from three independent biological replicates. p = 0.0192 in d, p = 9.70 × 10−4 in e. f, Schematic representation of a mammalian nucleolus in an unperturbed nucleus (left) and a nucleus with inhibited RNA polymerase I (Pol I) activity by ActD (right). The nucleolus is composed of three layers: the granular component (GC), the dense fibrillar component (DFC) and the fibrillar centre (FC). When transcription is inhibited by ActD, mammalian nucleoli undergo a characteristic change called ‘nucleolar segregation’. In such a segregated state, nucleoli become spherical, and the transcription machinery accumulates at the periphery of the GC, forming structures called ‘nucleolar caps’. g, Confocal fluorescence images of HeLa cells in the absence/presence of ActD with FLP1 (10 μM, for 1 h). For cells treated with ActD, the FC was separated from the GC to form “caps” at the nucleolar periphery. h-k, FLIM images (h and j) and fluorescence lifetime statistics (i and k) of cells’ nucleoli in the absence/presence of ActD (0.2 μM for 2 h); FLP1 (10 μM) was added 1 h prior to imaging. Data in i are presented as mean values ± s.d. from n = 15 independent biological replicates. Data in k are presented as mean values ± s.d. from n = 7 independent biological replicates. Similar with senescent cells, nucleoli of cells treated with ActD exhibit shorter fluorescence lifetimes than proliferating cells. Statistical significance was calculated using two tailed t-test. *P<0.05, **P<0.01, ***P<0.001.

Source Data

Extended Data Fig. 3 Super-resolution mapping of RNA within nucleoli in living cells.

a, Super-resolution fluorescence images (by using structured illumination microscopy, SIM) of live HeLa cells with FLP1 (10 μM treatment for 1 h) and Hoechst 33342 (10 μM treatment for 0.5 h). SIM imaging results clearly show that RNA (lighting-up by FLP1) in nucleoli is mainly distributed in the dense fibrillar component (DFC) and granular component (GC) (“bright part” of the nucleole), rather than in the fibrillar centre (FC) (“dark part” within the nucleoli). b, SIM images of live mouse neutrophils; FLP1 was added (10 μM) 1 h prior to imaging. c, Schematic diagram of the neutrophil nucleus structure. Neutrophils generally possess multilobed nucleus with 2-5 lobes. And the RNA-containing granules are dispersed around the chromatin. d, Confocal fluorescence microscopic images of live HeLa cells with FLPRNA dyes including FLP1 (λex = 580 nm; λem = 630-750 nm), FLP2 (λex = 715 nm; λem = 730-830 nm), FLP3 (λex = 600 nm; λem = 675-775 nm), and FLP4 (λex = 660 nm; λem = 675-750 nm). FLPRNA dye was added (10 μM) 1 h prior to imaging. e, The signal-to-noise ratio of nucleolar imaging (by calculating the ratio of the average fluorescent gray value of nucleolar region to chromatin region) with FLPRNA dyes. Data are presented as mean values ± s.d. from three independent biological replicates. f-h, Colocalization images of live HeLa cells with FLP1 (10 μM) and Hoechst 33342 (commercialized DNA staining dye; 10 μM; λex = 405 nm; λem = 440-500 nm) (f) or SYTO (commercialized RNA staining dye; 0.5 μM; λex = 490 nm; λem = 510-550 nm) (g and h). FLP1 demonstrates a notable colocalization effect with SYTO in the nucleolus, providing compelling evidence for the effective lighting-up of RNA in nucleoli by using FLP1.

Source Data

Extended Data Fig. 4 Quantifying multiple cellular senescent models and mouse kidney aging via S-FLIM.

a, Confocal fluorescence microscopic and FLIM images of proliferating (untreated control) and senescent A549 cells incubated with FLP1 (10 µM for 1 h) In FLIM images, nucleoli of proliferating cells had much longer fluorescence lifetimes (shown as red signals) than those of senescent cells (shown as green signals). b, Fluorescence lifetime histograms based on FLIM imaging of the nucleolar region of A549. c, Fluorescence lifetime statistics in nucleoli of proliferating and senescent A549. Data are presented as mean values ± s.d. from n = 18 independent biological replicates. d, General overview of FLIM imaging of human lung fibroblastic cells MRC-5 cells (the number of divisions is limited, and long-term growth can cause natural aging) with different population doubling levels (PDL) incubated with FLP1. Fibroblasts reached replicative senescence after comparable numbers of population doubling levels (PDL) in cell culture. e, f, FLIM images (e) and fluorescence lifetime statistics (f) of MRC-5 cells (PDL4, PDL10, and PDL14) with FLP1(10 μM, for 1 h). Data in f are presented as mean values ± s.d. from independent biological replicates (n = 16 for PDL4, n = 19 for PDL10 and PDL14). Nucleoli of PDL4 cells show much longer fluorescence lifetime than those of senescent cells (PDL10 and PDL14). g, Immunoblotting against p53, p21, and p16 protein expression levels in MRC-5 cells of PDL4, PDL10, and PDL14. Indeed, the senescence at PDL10 (after 6 PDLs) appears rapid. This accelerated phenotype likely represents an interplay between intrinsic replicative exhaustion and laboratory-specific culture conditions that may amplify senescence signatures. h, General overview of the procedure for isolation and FLIM imaging of mouse kidney tissue at different ages. Considering individual aging is associated with kidney aging, we used a vibratome to obtain fresh kidney sections to examine the kidney cell nucleolar fluorescence lifetime of wild-type C57BL/6J mice aged in 2 months and 20 months. i, j, FLIM images (i) and fluorescence lifetime statistics (j) of mouse kidney tissue (incubated with FLP1 10 μM, for 1 h) of different ages. Data are presented as mean values ± s.d. from n = 8 biologically independent mice for different age groups. Nucleoli of young mouse’s kidney tissue exhibit much longer fluorescence lifetimes (shown as red signals) than those of aging mouse’s kidney tissue (shown as yellow signals). Statistical significance was calculated using two tailed t-test. In vivo FLIM measurements in aging mouse kidneys provide direct evidence that nucleolar τ decay is a conserved hallmark of physiological aging. This establishes S-FLIM as a visualized tool for tracking fundamental aging mechanisms in live mammals.

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Extended Data Fig. 5 S-FLIM for revealing early therapy-induced senescence and screening TIS drugs.

a, Representative FLIM images of HeLa cells’ nucleoli from 0 to 96 hours of etoposide (2 μM) culture; FLP1 was added (10 μM) 1 h prior to imaging. b, Representative FLIM images for control HeLa cells and HeLa cells exposed to the aforementioned 4 antineoplastic drugs (1 μM for 96 h); FLP1 (10 μM) was added 1 h prior to imaging.

Extended Data Fig. 6 Quantifying human aging via S-FLIM of living blood cells.

a,b, FLIM images (a) and fluorescence lifetime statistics (b) of neutrophils (incubated with FLP1 10 μM for 1 h) of 29 volunteers with different ages. Data are presented as mean values ± s.d. from biologically independent human for each group (n = 11 for young group, n = 10 for middle aged group, n = 8 for aged group). The fluorescence lifetime of neutrophils gradually decreases with the age of volunteers. p = 2.97 × 10−7 for young-middle aged, p = 5.29 × 10−6 for middle aged-aged, p = 1.40 × 10−8 for young-aged. Statistical significance was calculated using two tailed t-test. ****P<0.0001.

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Yan, C., Liu, C., Liu, B. et al. Fluorescence lifetime clocks quantify senescence and aging. Nat Aging 5, 2532–2545 (2025). https://doi.org/10.1038/s43587-025-01001-1

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