Spatially resolved high throughput lineage tracing by targeted in situ DNA diversification

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Project Summary Cell division and differentiation are fundamental processes in biology. Lineage information for individual cells in an adult represents the missing key to understanding the origins of different cell types and how cells choose certain developmental trajectories. However, lineage tracing, especially that at a high resolution, is technically demanding. We reason that an ideal lineage tracing tool must meet two requirements: (1) a programable recording mechanism with large storage capacity that labels every cell division in a developmental window of interest, and (2) an error-robust readout mechanism that can reveal the lineage labels in individual cells without disrupting their spatial distribution. With these two requirements in mind, we propose to develop a widely applicable tool for spatially resolved single-cell lineage tracing. Our lineage tracing tool constitutes two modular key technologies: targeted in situ DNA diversification for lineaging recording and 2D multiplexed imaging for lineaging reading. To enable dynamic tracing at single-cell resolution, every cell division must be uniquely labeled, and these lineage labels must be stable and inheritable. To this end, we will develop a targeted in situ DNA diversification technology using base editors, which are precise genome-editing agents that introduce C:G to T:A or A:T to G:C transitions in double-stranded DNA. Our simulation suggests that by including 20 editable bases for base editors in a short DNA sequence, a maximum of 300k unique reads can be obtained with 20 generations of unrestricted cell division from a single ancestor cells, reinforcing the large sequence diversity that can be accessed by our recording technology. To retrieve these lineage labels from intact tissue samples, we will develop and validate a 2D multiplexed imaging platform that can efficiently read out the mutations generated during lineage recording. In this imaging platform, each editing position will be read out in a sequential way by each hybridization-imaging cycle, and each cassette will be presented by unique color codes in each hybridization-imaging cycle using degenerate probes. This 2D multiplexed imaging platform can efficiently read out the 220 unique labels from 20 editable bases using 5 colors in only 4 imaging cycles, dramatically facilitating the information retrieval process. This multiplexed imaging platform is only made possible by the unique binary functional mode of base editing and is not compatible with the vast majority of CRSIPR-based tracers, which function by introducing random DNA mutations to label cell lineage. Finally, we will apply both technologies for a proof-of-concept tracing experiment in HeLa cells. Collectively, the proposed technologies, once developed, will enable the collection of spatially resolved lineage information from single cells in intact tissues. We expect our tool can be widely applicable to various biological systems.