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bioRxiv · 10.1101/2024.10.23.619855

Genetically-Encoded Fluorescence Barcodes for Single-Cell Analysis

Abstract

Genetically-encoded, single-cell barcodes are broadly useful for experimental tasks such as lineage tracing or genetic screens. For such applications, a barcode library would ideally have high diversity (many unique barcodes), non-destructive identification (repeated measurements in the same cells or population), and fast, inexpensive readout (many cells and conditions). Current nucleic acid barcoding methods generate high diversity but require destructive and slow/expensive readout, and current fluorescence barcoding methods are non-destructive, fast, and inexpensive to readout but lack high diversity. We recently proposed theory for how fluorescent protein combinations may generate a high-diversity barcode library with non-destructive, fast and inexpensive identification. Here, we present an initial experimental proof-of-concept by generating a library of [~]150 barcodes from two-way combinations of 18 fluorescent proteins, 61 of which are tested experimentally. We use a pooled cloning strategy to generate a barcode library that is validated to contain every possible combination of the 18 fluorescent proteins. Experimental results using single mammalian cells and spectral flow cytometry demonstrate excellent classification performance of individual fluorescent proteins, with the exception of mTFP1, and of most evaluated barcodes, with many true positive rates >99%. The library is compatible with genetic screening for hundreds of genes (or gene pairs) and lineage tracing hundreds of clones. This work lays a foundation for greater diversity libraries (potentially [~]105 and more) generated from hundreds of spectrally-resolvable tandem fluorescent protein probes.

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BibTeXRIS

Lu, X., Pritko, D. J., Abravanel, M. E., Huggins, J. R., Ogunleye, F., Biswas, T., Ashy, K. C., Woods, S. K., Livingston, M. W., Blenner, M., Birtwistle, M. R.. 2024-10-24. Genetically-Encoded Fluorescence Barcodes for Single-Cell Analysis. https://doi.org/10.1101/2024.10.23.619855

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