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Nanosensor-based monitoring of autophagy-associated lysosomal acidification in vivo

Nature Chemical Biology volume 19, pages 1448–1457 (2023)Cite this article

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Abstract

Autophagy is a cellular process with important functions that drive neurodegenerative diseases and cancers. Lysosomal hyperacidification is a hallmark of autophagy. Lysosomal pH is currently measured by fluorescent probes in cell culture, but existing methods do not allow for quantitative, transient or in vivo measurements. In the present study, we developed near-infrared optical nanosensors using organic color centers (covalent sp3 defects on carbon nanotubes) to measure autophagy-mediated endolysosomal hyperacidification in live cells and in vivo. The nanosensors localize to the lysosomes, where the emission band shifts in response to local pH, enabling spatial, dynamic and quantitative mapping of subtle changes in lysosomal pH. Using the sensor, we observed cellular and intratumoral hyperacidification on administration of mTORC1 and V-ATPase modulators, revealing that lysosomal acidification mirrors the dynamics of S6K dephosphorylation and LC3B lipidation while diverging from p62 degradation. This sensor enables the transient and in vivo monitoring of the autophagy–lysosomal pathway.

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Fig. 1: Synthesis of pH-responsive OCC–DNA complexes.
Fig. 2: OCC–DNA complexes respond to endolysosomal pH.
Fig. 3: Nanosensor response under modulation of V-ATPase in live cells.
Fig. 4: Dynamic response to V-ATPase and mTORC modulation in live cells.
Fig. 5: In vivo nanosensor response to V-ATPase and mTORC modulation.
Fig. 6: In vivo dynamic monitoring of autophagy induction.

Data availability

Source data are provided with this paper.

Code availability

LABVIEW code for data acquisition and MATLAB codes for data analysis in this article are available in the public GitHub repository (github.com/mijinee/HellerLab_MSKCC).

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Acknowledgements

We thank Memorial Sloan Kettering Cancer Center (MSKCC) Molecular Cytology Core Facility for assistance with AFM imaging, sample processing for immunofluorescence and confocal microscopy, and image analysis. We also thank the Center for Translational Pathology at Weill Cornell Medicine for immunohistochemistry. We thank C. O’Mara at the Daniel Bachovchin lab (MSKCC) for the NLRP3 inflammasome experiment. We thank P. Jena for assistance with image processing and analysis. The graphical abstract, Fig. 3a and Supplementary Figs. 2 and 11 were created with BioRender.com. This work was supported in part by the National Science Foundation CAREER Award (grant no. 1752506 to D.A.H.), the National Cancer Institute (grant no. R01-CA215719 to D.A.H. and Cancer Center Support grant no. P30-CA008748 to D.A.H., H.A. and Y.M.L.), the National Institutes of Health (NIH) Common Fund (grant no. DP2-HD075698 to D.A.H.), the Department of Defense Congressionally Directed Medical Research Program (W81XWH2210563 to D.A.H.), the American Cancer Society Research Scholar grant (no. GC230452 to D.A.H.), the Ara Parseghian Medical Research Fund (to D.A.H.), the Honorable Tina Brozman Foundation (to D.A.H.), the Ovarian Cancer Research Alliance and the Edmée Firth Fund for Research in Ovarian Cancer (grant no. CRDGAI-2023-3-1003 to D.A.H.), the Pershing Square Sohn Cancer Research Alliance (to D.A.H.), the New York State Biodefense Commercialization Fund (to D.A.H.), the Expect Miracles Foundation—Financial Services Against Cancer (to D.A.H.), the Louis and Rachel Rudin Foundation (to D.A.H.), the Experimental Therapeutics Center of MSKCC (to D.A.H. and Y.M.L.), Mr. William H. Goodwin and Mrs. Alice Goodwin and the Commonwealth Foundation for Cancer Research (to D.A.H. and Y.M.L.), the JPB Foundation (to Y.M.L.) and the William Randolph Hearst Fund in Experimental Therapeutics (to Y.M.L.). M.K. was supported by the NIH (grant no. K99-EB033580) and the Marie-Josée Kravis Women in Science Endeavor Postdoctoral Fellowship. Z.Y. was supported by the Ann Schreiber Mentored Investigator Award (Ovarian Cancer Research Fund) and Young Investigator 2019 (Kaleidoscope of Hope). R.L. was supported by an NIH T32 training grant (no. T32-GM73546), J.W. was supported by an NIH T32 training grant (no. T32-GM136640-Tan). D.W. was supported by NIH T32 training grants (nos. T32-GM141949 and T32-CA062948). R.F. was supported by the Alfred Benzon Foundation Fellowship. Y.H.W. acknowledges support from the National Science Foundation (grant nos. CHE-1904488 and CHE-2204202).

Author information

Author notes

  1. Zvi Yaari

    Present address: School of Pharmacy, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel

  2. These authors contributed equally: Mijin Kim, Chen Chen.

Authors and Affiliations

  1. Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Mijin Kim, Chen Chen, Zvi Yaari, Rune Frederiksen, Ewelina Randall, Jaina Wollowitz, Christian Cupo, Janki Shah, Daniel Worroll, Rachel E. Lagenbacher, Dana Goerzen, Yue-Ming Li, Heeseon An & Daniel A. Heller

  2. Weill Cornell Medicine, Cornell University, New York, NY, USA

    Chen Chen, Jaina Wollowitz, Rachel E. Lagenbacher, Dana Goerzen, Yue-Ming Li, Heeseon An & Daniel A. Heller

  3. Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Chen Chen & Jaina Wollowitz

  4. Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, USA

    Xiaojian Wu & YuHuang Wang

  5. Maryland NanoCenter, University of Maryland, College Park, MD, USA

    YuHuang Wang

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Contributions

M.K., C. Chen, R.F., D.A.H., H.A. and Y.H.W. conceived the idea. M.K., C. Chen, R.F. and D.A.H. designed experiments. M.K., C. Chen, and D.A.H. analyzed the data. M.K., E.R. and X.W. performed nanosensor synthesis. M.K., C. Chen, R.F., E.R., J.W., C. Cupo, R.E.L., D.W.W., R.L. and D.G. performed in vitro experiments. M.K., C. Chen, Z.Y. and J.S. performed in vivo experiments. M.K., C. Chen and D.A.H. wrote the manuscript. Y.M.L., H.A. and Y.H.W. edited the manuscript.

Corresponding author

Correspondence to Daniel A. Heller.

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Competing interests

D.A.H. is a cofounder and officer with equity interest in Lime Therapeutics, Inc., cofounder with equity interest in Selectin Therapeutics Inc. and Resident Diagnostics, Inc., and a member of the scientific advisory board of Concarlo Therapeutics, Inc., Nanorobotics Inc. and Mediphage Bioceuticals, Inc. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Characterization of OCC-DNA response in various buffer/media conditions.

Emission wavelengths of a-c, E11 and d-f, E11- of the OCC-DNA complexes at varying buffer pH and media conditions in phosphate buffered saline. The metal ion concentrations tested are physiologically relevant ranges. All data are presented as mean values and error bars denote standard deviation from N = 3 technical replicates (a-f). g, Frequency distribution of standard deviations of ΔE ( = E11- – E11) wavelength shifts of triplicate measurements of a-f.

Source data

Extended Data Fig. 2 Protein concentration effects on OCC-DNA optical response.

The dynamic range of the OCC-DNA response to pH at increasing concentrations of: a, bovine serum albumin and b, fetal bovine serum. All data are presented as mean values and error bars denote standard deviation from N = 3 technical replicates (a,b).

Source data

Extended Data Fig. 3 Viscosity effects on OCC-DNA optical response.

Emission wavelengths of a, E11 and b, E11- of the OCC-DNA complexes at varying buffer pH and glycerol. All data are presented as mean values and error bars denote standard deviation from N = 3 technical replicates (a,b).

Source data

Extended Data Fig. 4 Cell viability in response to OCC-DNA complexes.

Single-dose (0.01 mg/L) OCC-DNA cell viability of SKOV3, OVCAR3, HEK293, HeLa, MEF, RM1, and Myc-CaP cell lines, measured via CellTiter-Glo 2.0, after 72 hours of incubation. No statistically significant differences were observed between the PBS control groups (gray) and the treatment groups (red) in all the tested cell lines. All data are presented as mean values and error bars denote standard deviation of triplicates for each condition.

Source data

Extended Data Fig. 5 OCC-DNA responses in 8 cell lines.

The emission response (ΔE = E11- – E11) of OCC-DNAs in live cells upon exposure to HEPES or MES buffer solutions of varying pHs with monensin (see Methods). All data are presented as mean values and error bars denote standard deviation from N = 3–25 biological replicates.

Source data

Extended Data Fig. 6 Inhibitor-mediated alterations of nanosensor response to pH.

The emission response (ΔE = E11- – E11) of nanosensors in live SKOV3 cells upon exposure to HEPES or MES buffer solutions of varying pHs with monensin (see Methods). Cells were treated with DMSO (black), 100 µM EN6 (red), 100 nM bafilomycin A1 (blue), 250 nM torin 1 (green) for 4 hours prior to pH measurements. Data are presented as mean values and error bars denote standard deviation from N = 25 each DMSO, EN6, and Baf A1 point, and N = 25, 24, and 21 for pH 7, 5.06, and 3.16 for torin 1 as biological replicates.

Source data

Extended Data Fig. 7 Nanosensor response in autophagy-defective cells.

a, ATG7 expression by western blotting confirmed the knockout of ATG7 in the HEK293T cell line used herein. The emission wavelength response (ΔE = E11- – E11) of OCC-DNAs in live b, wild type and c, ATG7-/- HEK293T cells upon exposure to HEPES or MES buffer solutions of varying pHs in the presence of monensin (see Methods). Cells were treated with DMSO (black) or 250 nM torin 1 (blue) for 4 hours prior to pH measurements. All data are presented as mean values and error bars denote standard deviation from N = 10 technical replicates (b,c). Original gel images are in Supplementary Fig. 24.

Source data

Extended Data Fig. 8 Time-dependent fluorescence intensity changes of intratumorally-injected nanosensors.

Quantification of total emission intensity of nanosensors in solid tumours of mice after injection. Fluorescence measurements were performed with a near-infrared preclinical hyperspectral imager with 730 nm excitation. Data are presented as mean values and error bars denote standard deviation from N = 5 biological replicates.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–24 and Supplementary References.

Reporting Summary

Supplementary Video 1

NIR fluorescence video of OCC–DNA complexes in live SKOV3 cells.

Supplementary Data 1

Source data for Supplementary Figs.

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Fig. 4

Unprocessed western blots/gels for actin, LC3B, P62 and pS6K.

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Extended Data Fig. 1

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Extended Data Fig. 7a

Unprocessed western blots/gels for actin and FIP200.

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Kim, M., Chen, C., Yaari, Z. et al. Nanosensor-based monitoring of autophagy-associated lysosomal acidification in vivo. Nat Chem Biol 19, 1448–1457 (2023). https://doi.org/10.1038/s41589-023-01364-9

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