Nicola Martino, Hao Yan, Geoffrey Abbott, Marissa Fahlberg, Sarah Forward, Kwon-Hyeon Kim, Yue Wu, Han Zhu, Sheldon J. J. Kwok, Seok-Hyun Yun
{"title":"激光粒子细胞的大规模组合光学条形码","authors":"Nicola Martino, Hao Yan, Geoffrey Abbott, Marissa Fahlberg, Sarah Forward, Kwon-Hyeon Kim, Yue Wu, Han Zhu, Sheldon J. J. Kwok, Seok-Hyun Yun","doi":"10.1038/s41377-025-01809-x","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":18069,"journal":{"name":"Light-Science & Applications","volume":"36 1","pages":""},"PeriodicalIF":20.6000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large-scale combinatorial optical barcoding of cells with laser particles\",\"authors\":\"Nicola Martino, Hao Yan, Geoffrey Abbott, Marissa Fahlberg, Sarah Forward, Kwon-Hyeon Kim, Yue Wu, Han Zhu, Sheldon J. J. Kwok, Seok-Hyun Yun\",\"doi\":\"10.1038/s41377-025-01809-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":18069,\"journal\":{\"name\":\"Light-Science & Applications\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":20.6000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Light-Science & Applications\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.1038/s41377-025-01809-x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Light-Science & Applications","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.1038/s41377-025-01809-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPTICS","Score":null,"Total":0}
Large-scale combinatorial optical barcoding of cells with laser particles
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.