Large-scale combinatorial optical barcoding of cells with laser particles

IF 20.6 Q1 OPTICS
Nicola Martino, Hao Yan, Geoffrey Abbott, Marissa Fahlberg, Sarah Forward, Kwon-Hyeon Kim, Yue Wu, Han Zhu, Sheldon J. J. Kwok, Seok-Hyun Yun
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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.

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来源期刊
Light-Science & Applications
Light-Science & Applications 数理科学, 物理学I, 光学, 凝聚态物性 II :电子结构、电学、磁学和光学性质, 无机非金属材料, 无机非金属类光电信息与功能材料, 工程与材料, 信息科学, 光学和光电子学, 光学和光电子材料, 非线性光学与量子光学
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803
审稿时长
2.1 months
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