Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry
Abstract Aging heterogeneity in tissue-regenerative cells leads to variable therapeutic outcomes, complicating quality control and clinical predictability. Conventional analytical methods relying on labeling or cell lysis are destructive and incompatible with downstream therapeutic applications. Her...
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| Format: | Article |
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Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61590-8 |
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| author | Youngho Song Inwoo Seo Changyu Tian Jiseon An Seongcheol Park Jiyu Hyun Seunghyuk Jung Hyun Su Park Hyun-Ji Park Suk Ho Bhang Soo-Yeon Cho |
| author_facet | Youngho Song Inwoo Seo Changyu Tian Jiseon An Seongcheol Park Jiyu Hyun Seunghyuk Jung Hyun Su Park Hyun-Ji Park Suk Ho Bhang Soo-Yeon Cho |
| author_sort | Youngho Song |
| collection | DOAJ |
| description | Abstract Aging heterogeneity in tissue-regenerative cells leads to variable therapeutic outcomes, complicating quality control and clinical predictability. Conventional analytical methods relying on labeling or cell lysis are destructive and incompatible with downstream therapeutic applications. Here we show a label-free, nondestructive single-cell analysis platform based on nanosensor chemical cytometry (NCC), integrated with automated hardware and deep learning. nIR fluorescent single-walled carbon nanotube arrays in a microfluidic channel, together with photonic nanojet lensing, extract four key aging phenotypes (cell size, shape, refractive index, and H2O2 efflux) from flowing cells in a high-throughput manner. Approximately 105 cells are quantified within 1 h, and NCC phenotype data were used to construct virtual aging trajectories in 3D space. The resulting phenotypic heterogeneity aligns with RNA-sequencing gene-expression profiles, enabling reliable prediction of therapeutic efficacy. The platform rapidly identifies optimally aged cells without perturbation, providing a robust tool for real-time monitoring and quality control in regenerative-cell manufacturing. |
| format | Article |
| id | doaj-art-bc3b0558d59846e9955acb22994fbfe4 |
| institution | DOAJ |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-bc3b0558d59846e9955acb22994fbfe42025-08-20T03:05:15ZengNature PortfolioNature Communications2041-17232025-07-0116111610.1038/s41467-025-61590-8Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometryYoungho Song0Inwoo Seo1Changyu Tian2Jiseon An3Seongcheol Park4Jiyu Hyun5Seunghyuk Jung6Hyun Su Park7Hyun-Ji Park8Suk Ho Bhang9Soo-Yeon Cho10School of Chemical Engineering, Sungkyunkwan UniversitySchool of Chemical Engineering, Sungkyunkwan UniversitySchool of Chemical Engineering, Sungkyunkwan UniversitySchool of Chemical Engineering, Sungkyunkwan UniversitySchool of Chemical Engineering, Sungkyunkwan UniversitySchool of Chemical Engineering, Sungkyunkwan UniversityDepartment of Applied Chemistry & Biological Engineering, Ajou UniversitySchool of Chemical Engineering, Sungkyunkwan UniversityAdvanced College of Bio-Convergence Engineering, Ajou UniversitySchool of Chemical Engineering, Sungkyunkwan UniversitySchool of Chemical Engineering, Sungkyunkwan UniversityAbstract Aging heterogeneity in tissue-regenerative cells leads to variable therapeutic outcomes, complicating quality control and clinical predictability. Conventional analytical methods relying on labeling or cell lysis are destructive and incompatible with downstream therapeutic applications. Here we show a label-free, nondestructive single-cell analysis platform based on nanosensor chemical cytometry (NCC), integrated with automated hardware and deep learning. nIR fluorescent single-walled carbon nanotube arrays in a microfluidic channel, together with photonic nanojet lensing, extract four key aging phenotypes (cell size, shape, refractive index, and H2O2 efflux) from flowing cells in a high-throughput manner. Approximately 105 cells are quantified within 1 h, and NCC phenotype data were used to construct virtual aging trajectories in 3D space. The resulting phenotypic heterogeneity aligns with RNA-sequencing gene-expression profiles, enabling reliable prediction of therapeutic efficacy. The platform rapidly identifies optimally aged cells without perturbation, providing a robust tool for real-time monitoring and quality control in regenerative-cell manufacturing.https://doi.org/10.1038/s41467-025-61590-8 |
| spellingShingle | Youngho Song Inwoo Seo Changyu Tian Jiseon An Seongcheol Park Jiyu Hyun Seunghyuk Jung Hyun Su Park Hyun-Ji Park Suk Ho Bhang Soo-Yeon Cho Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry Nature Communications |
| title | Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry |
| title_full | Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry |
| title_fullStr | Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry |
| title_full_unstemmed | Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry |
| title_short | Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry |
| title_sort | unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry |
| url | https://doi.org/10.1038/s41467-025-61590-8 |
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