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Published January 5, 2017 | Accepted Version + Supplemental Material
Journal Article Open

Synthetic recording and in situ readout of lineage information in single cells


Reconstructing the lineage relationships and dynamic event histories of individual cells within their native spatial context is a long-standing challenge in biology. Many biological processes of interest occur in optically opaque or physically inaccessible contexts, necessitating approaches other than direct imaging. Here, we describe a new synthetic system that enables cells to record lineage information and event histories in the genome in a format that can be subsequently read out in single cells in situ. This system, termed Memory by Engineered Mutagenesis with Optical In situ Readout (MEMOIR), is based on a set of barcoded recording elements termed scratchpads. The state of a given scratchpad can be irreversibly altered by Cas9-based targeted mutagenesis, and read out in single cells through multiplexed single-molecule RNA fluorescence hybridization (smFISH). To demonstrate a proof of principle of MEMOIR, we engineered mouse embryonic stem (ES) cells to contain multiple scratchpads and other recording components. In these cells, scratchpads were altered in a progressive and stochastic fashion as cells proliferated. Analysis of the final states of scratchpads in single cells in situ enabled reconstruction of the lineage trees of cell colonies. Combining analysis of endogenous gene expression with lineage reconstruction in the same cells further allowed inference of the dynamic rates at which ES cells switch between two gene expression states. Finally, using simulations, we showed how parallel MEMOIR systems operating in the same cell can enable recording and readout of dynamic cellular event histories. MEMOIR thus provides a versatile platform for information recording and in situ, single cell readout across diverse biological systems.

Additional Information

© 2016 Macmillan Publishers Limited, part of Springer Nature. Received 30 June 2016; Accepted 11 November 2016; Published online 21 November 2016. We thank Martin Budd and Hanqing Li for helpful suggestions. We thank Roy Kishony, and members of the Elowitz and Cai labs for discussions and comments on the manuscript. This research was supported by the Allen Distinguished Investigator Program, through The Paul G. Allen Frontiers Group, NIH R01HD075605 and K99GM118910 (to S.H.), the Gordon and Betty Moore Foundation Grant GBMF2809 to the Caltech Programmable Molecular Technology Initiative, and the Beckman Institute pilot program. Author Contributions: K.L.F. and J.M.L. performed the experiments with assistance from S.H., J.C., K.K.C., Z.S.S.; K.L.F. and S.H. analyzed the data; S.H. performed the simulations; M.B.E. and L.C. supervised the project. All authors wrote the manuscript.

Attached Files

Accepted Version - nihms-1016385.pdf

Supplemental Material - nature20777-s1.pdf

Supplemental Material - nature20777-s2.xlsx

Supplemental Material - nature20777-s3.xlsx


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