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.
Authors
- Yue Wu (ORCID: https://orcid.org/0000-0001-7680-9285)
- Seok‐Hyun Yun (ORCID: https://orcid.org/0000-0002-8176-9916)
- Sarah Forward
- Hao Yan (ORCID: https://orcid.org/0000-0002-5268-7153)
- Nicola Martino (ORCID: https://orcid.org/0000-0002-4639-2930)
- Geoffrey W. Abbott (ORCID: https://orcid.org/0000-0003-4552-496X)
- Zhu Han
- Kwon‐Hyeon Kim (ORCID: https://orcid.org/0000-0002-2822-9240)
- Marissa Fahlberg (ORCID: https://orcid.org/0000-0002-2597-7147)
- Sheldon J. J. Kwok (ORCID: https://orcid.org/0000-0001-7880-0401)
Institutions
- Broad Institute (US)
- Harvard University (US)
- Massachusetts General Hospital (US)
- Harvard–MIT Division of Health Sciences and Technology (US)
- Center for Systems Biology (US)
- Massachusetts Institute of Technology (US)
- Tsinghua University (CN)
Publication Details
- Journal
- Light Science & Applications
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1038/s41377-025-01809-x
- Citations
- 3
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 2.42
Funders
- National Institutes of Health