genetic-barcoding-with-fluorescent-proteins-for-multiplexed

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Fluorescent proteins, fluorescent dyes and fluorophores in general have revolutionized the field of molecular cell biology. In particular, the discovery ...

San Diego State University

The discovery of the green fluorescent protein from Aequorea victoria has revolutionized the field of cell and molecular biology. Since its discovery a growing panel of fluorescent proteins, fluorophores and fluorescent-coupled staining methodologies, have expanded the analytical capabilities of flow cytometry. Here, we exploit the power of genetic engineering to barcode individual cells with genes encoding fluorescent proteins. For genetic engineering, we utilize retroviral technology, which allows for the expression of ectopic genetic information in a stable manner in mammalian cells. We have genetically barcoded both adherent and nonadherent cells with different fluorescent proteins. Multiplexing power was increased by combining both the number of distinct fluorescent proteins, and the fluorescence intensity in each channel. Moreover, retroviral expression has proven to be stable for at least a 6-month period, which is critical for applications such as biological screens. We have shown the applicability of fluorescent barcoded multiplexing to cell-based assays that rely themselves on genetic barcoding, or on classical staining protocols. Fluorescent genetic barcoding gives the cell an inherited characteristic that distinguishes it from its counterpart. Once cell lines are developed, no further manipulation or staining is required, decreasing time, nonspecific background associated with staining protocols, and cost. The increasing number of discovered and/or engineered fluorescent proteins with unique absorbance/emission spectra, combined with the growing number of detection devices and lasers, increases multiplexing versatility, making fluorescent genetic barcoding a powerful tool for flow cytometry-based analysis.

Darin Abbadessa

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