Large-scale combinatorial optical barcoding of cells with laser particles
Abstract The identification of individual cells is crucial for advancements in single-cell analysis. Optically readable barcodes provide a means to distinguish and track cells through repeated, non-destructive measurements. Traditional fluorophore-based methods are limited by the finite number of un...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Publishing Group
2025-04-01
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| Series: | Light: Science & Applications |
| Online Access: | https://doi.org/10.1038/s41377-025-01809-x |
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| author | Nicola Martino Hao Yan Geoffrey Abbott Marissa Fahlberg Sarah Forward Kwon-Hyeon Kim Yue Wu Han Zhu Sheldon J. J. Kwok Seok-Hyun Yun |
| author_facet | Nicola Martino Hao Yan Geoffrey Abbott Marissa Fahlberg Sarah Forward Kwon-Hyeon Kim Yue Wu Han Zhu Sheldon J. J. Kwok Seok-Hyun Yun |
| author_sort | Nicola Martino |
| collection | DOAJ |
| description | Abstract The identification of individual cells is crucial for advancements in single-cell analysis. Optically readable barcodes provide a means to distinguish and track cells through repeated, non-destructive measurements. Traditional fluorophore-based methods are limited by the finite number of unique barcodes they can produce. Laser particles (LPs), which emit narrowband peaks over a wide spectral range, have emerged as a promising technology for single-cell barcoding. Here, we demonstrate the use of multiple LPs to generate combinatorial barcodes, enabling the identification of a vast number of live cells. We introduce a theoretical framework for estimating the number of LPs required for unique barcodes and the expected identification error rate. Additionally, we present an improved LP-tagging method that is highly effective across a variety of cell types and evaluate its biocompatibility. Our experimental results show successful barcoding of several million cells, closely matching our theoretical predictions. This research marks a significant step forward in the scalability of LP technology for single-cell tracking and analysis. |
| format | Article |
| id | doaj-art-0939f7221fcb416981d665f31f6a2cd5 |
| institution | OA Journals |
| issn | 2047-7538 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Light: Science & Applications |
| spelling | doaj-art-0939f7221fcb416981d665f31f6a2cd52025-08-20T01:54:20ZengNature Publishing GroupLight: Science & Applications2047-75382025-04-0114111710.1038/s41377-025-01809-xLarge-scale combinatorial optical barcoding of cells with laser particlesNicola Martino0Hao Yan1Geoffrey Abbott2Marissa Fahlberg3Sarah Forward4Kwon-Hyeon Kim5Yue Wu6Han Zhu7Sheldon J. J. Kwok8Seok-Hyun Yun9Harvard Medical School and Wellman Center for Photomedicine, Massachusetts General HospitalHarvard Medical School and Wellman Center for Photomedicine, Massachusetts General HospitalLASE Innovation Inc.LASE Innovation Inc.LASE Innovation Inc.Harvard Medical School and Wellman Center for Photomedicine, Massachusetts General HospitalHarvard Medical School and Wellman Center for Photomedicine, Massachusetts General HospitalLASE Innovation Inc.LASE Innovation Inc.Harvard Medical School and Wellman Center for Photomedicine, Massachusetts General HospitalAbstract The identification of individual cells is crucial for advancements in single-cell analysis. Optically readable barcodes provide a means to distinguish and track cells through repeated, non-destructive measurements. Traditional fluorophore-based methods are limited by the finite number of unique barcodes they can produce. Laser particles (LPs), which emit narrowband peaks over a wide spectral range, have emerged as a promising technology for single-cell barcoding. Here, we demonstrate the use of multiple LPs to generate combinatorial barcodes, enabling the identification of a vast number of live cells. We introduce a theoretical framework for estimating the number of LPs required for unique barcodes and the expected identification error rate. Additionally, we present an improved LP-tagging method that is highly effective across a variety of cell types and evaluate its biocompatibility. Our experimental results show successful barcoding of several million cells, closely matching our theoretical predictions. This research marks a significant step forward in the scalability of LP technology for single-cell tracking and analysis.https://doi.org/10.1038/s41377-025-01809-x |
| spellingShingle | Nicola Martino Hao Yan Geoffrey Abbott Marissa Fahlberg Sarah Forward Kwon-Hyeon Kim Yue Wu Han Zhu Sheldon J. J. Kwok Seok-Hyun Yun Large-scale combinatorial optical barcoding of cells with laser particles Light: Science & Applications |
| title | Large-scale combinatorial optical barcoding of cells with laser particles |
| title_full | Large-scale combinatorial optical barcoding of cells with laser particles |
| title_fullStr | Large-scale combinatorial optical barcoding of cells with laser particles |
| title_full_unstemmed | Large-scale combinatorial optical barcoding of cells with laser particles |
| title_short | Large-scale combinatorial optical barcoding of cells with laser particles |
| title_sort | large scale combinatorial optical barcoding of cells with laser particles |
| url | https://doi.org/10.1038/s41377-025-01809-x |
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