Mapping cell-cell fusion at single-cell resolution

Gardner, A. L.; Zheng, L.; Howland, K. K.; Saunders, A.; Ramirez, A.; Parker, P.; Iloegbunam, C.; Morgan, D.; Jost, T. A.; Brock, A.

doi:10.1101/2024.12.11.627873

bioRxiv · 10.1101/2024.12.11.627873

Mapping cell-cell fusion at single-cell resolution

Gardner, A. L.·Zheng, L.·Howland, K. K.·Saunders, A.·Ramirez, A.·Parker, P.·Iloegbunam, C.·Morgan, D.·Jost, T. A.·Brock, A.

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Abstract

Cell-cell fusion is a tightly controlled process in the human body known to be involved in fertilization, placental development, muscle growth, bone remodeling, and viral response. Fusion between cancer cells results first in a whole-genome doubled state, which may be followed by the generation of aneuploidies; these genomic alterations are known drivers of tumor evolution. The role of cell-cell fusion in cancer progression and treatment response has been understudied due to limited experimental systems for tracking and analyzing individual fusion events. To meet this need, we developed a molecular toolkit to map the origins and outcomes of individual cell fusion events within a tumor cell population. This platform, ClonMapper Duo ( CMDuo), identifies cells that have undergone cell-cell fusion through a combination of reporter expression and engineered fluorescence-associated index sequences paired to randomly generated nucleotide barcodes. scRNA-seq of the indexed barcodes enables the mapping of each set of parental cells and fusion progeny throughout the cell population. In triple-negative breast cancer cells CMDuo uncovered subclonal transcriptomic hybridization and unveiled distinct cell-states which arise in direct consequence of homotypic cell-cell fusion. CMDuo is a platform that enables mapping of cell-cell fusion events in high-throughput single cell data and enables the study of cell fusion in disease progression and therapeutic response.

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Gardner, A. L., Zheng, L., Howland, K. K., Saunders, A., Ramirez, A., Parker, P., Iloegbunam, C., Morgan, D., Jost, T. A., Brock, A.. 2024-12-14. Mapping cell-cell fusion at single-cell resolution. https://doi.org/10.1101/2024.12.11.627873

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