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  • Protocol
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Molecular recording using DNA Typewriter

Abstract

Recording molecular information to genomic DNA is a powerful means of investigating topics ranging from multicellular development to cancer evolution. With molecular recording based on genome editing, events such as cell divisions and signaling pathway activity drive specific alterations in a cell’s DNA, marking the genome with information about a cell’s history that can be read out after the fact. Although genome editing has been used for molecular recording, capturing the temporal relationships among recorded events in mammalian cells remains challenging. The DNA Typewriter system overcomes this limitation by leveraging prime editing to facilitate sequential insertions to an engineered genomic region. DNA Typewriter includes three distinct components: DNA Tape as the ‘substrate’ to which edits accrue in an ordered manner, the prime editor enzyme, and prime editing guide RNAs, which program insertional edits to DNA Tape. In this protocol, we describe general design considerations for DNA Typewriter, step-by-step instructions on how to perform recording experiments by using DNA Typewriter in HEK293T cells, and example scripts for analyzing DNA Typewriter data (https://doi.org/10.6084/m9.figshare.22728758). This protocol covers two main applications of DNA Typewriter: recording sequential transfection events with programmed barcode insertions by using prime editing and recording lineage information during the expansion of a single cell to many. Compared with other methods that are compatible with mammalian cells, DNA Typewriter enables the recording of temporal information with higher recording capacities and can be completed within 4–6 weeks with basic expertise in molecular cloning, mammalian cell culturing and DNA sequencing data analysis.

Key points

  • DNA Typewriter is a CRISPR genome editing-based method for recording the temporal order of molecular events by tracing the physical order of unique barcodes along a DNA Tape array.

  • Compared with other existing methods, DNA Typewriter is highly multiplexable, unidirectional and sequential, capturing thousands of insertions in the precise order in which they occur, and it is active in living mammalian cells, including HEK293T, mouse embryonic stem cells and fibroblasts.

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Fig. 1: Molecular recording by using DNA Typewriter.
Fig. 2: Overview of recording the order of transfections by using DNA Typewriter.
Fig. 3: Overview of recording single-cell lineage information by using DNA Typewriter.

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Data availability

Example data files have been deposited to Figshare (https://doi.org/10.6084/m9.figshare.22728758.v1)37. Plasmids to clone in pegRNAs and DNA Tape have been deposited to Addgene (cat. nos. 200029 for lentiviral backbone construct and 200030 for piggyBAC backbone construct).

Code availability

Along with the example data, example scripts that can be directly used to analyze example data files have been deposited to Figshare (https://doi.org/10.6084/m9.figshare.22728758.v1)37. For recording the order of transfection, we have included an example script (TAPE_text_sorting.ipynb) to determine the order of transfected barcodes from paired-end sequencing data. For generating a single-cell lineage tree, we run a first custom script (TAPE_10X_read2fromBAM.ipynb) to extract the single-cell barcode information along with edits in captured DNA Tape molecules. The output can then be used in the second custom script (DNATypewriter_SingleCellLineage_Rscript.ipynb) to plot the lineage tree on the basis of the shared patterns of edited DNA Tapes from single cells.

References

  1. Sheth, R. U. & Wang, H. H. DNA-based memory devices for recording cellular events. Nat. Rev. Genet. 19, 718–732 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Farzadfard, F. & Lu, T. K. Emerging applications for DNA writers and molecular recorders. Science 361, 870–875 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Lear, S. K. & Shipman, S. L. Molecular recording: transcriptional data collection into the genome. Curr. Opin. Biotechnol. 79, 102855 (2023).

    Article  CAS  PubMed  Google Scholar 

  4. Sheth, R. U., Yim, S. S., Wu, F. L. & Wang, H. H. Multiplex recording of cellular events over time on CRISPR biological tape. Science 358, 1457–1461 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Tang, W. & Liu, D. R. Rewritable multi-event analog recording in bacterial and mammalian cells. Science 360, eaap8992 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Farzadfard, F. et al. Single-nucleotide-resolution computing and memory in living cells. Mol. Cell 75, 769–780.e4 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Bhattarai-Kline, S. et al. Recording gene expression order in DNA by CRISPR addition of retron barcodes. Nature 608, 217–225 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Shipman, S. L., Nivala, J., Macklis, J. D. & Church, G. M. Molecular recordings by directed CRISPR spacer acquisition. Science 353, aaf1175 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Shipman, S. L., Nivala, J., Macklis, J. D. & Church, G. M. CRISPR–Cas encoding of a digital movie into the genomes of a population of living bacteria. Nature 547, 345–349 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Schmidt, F., Cherepkova, M. Y. & Platt, R. J. Transcriptional recording by CRISPR spacer acquisition from RNA. Nature 562, 380–385 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Schmidt, F. et al. Noninvasive assessment of gut function using transcriptional recording sentinel cells. Science 376, eabm6038 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Choi, J. et al. A time-resolved, multi-symbol molecular recorder via sequential genome editing. Nature 608, 98–107 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Anzalone, A. V. et al. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature 576, 149–157 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Chen, P. J. & Liu, D. R. Prime editing for precise and highly versatile genome manipulation. Nat. Rev. Genet. 24, 161–177 (2023).

    Article  CAS  PubMed  Google Scholar 

  15. Rodriguez-Fraticelli, A. & Morris, S. A. In preprints: the fast-paced field of single-cell lineage tracing. Development 149, dev200877 (2022).

    Article  CAS  PubMed  Google Scholar 

  16. Sankaran, V. G., Weissman, J. S. & Zon, L. I. Cellular barcoding to decipher clonal dynamics in disease. Science 378, eabm5874 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Jones, M. G., Yang, D. & Weissman, J. S. New tools for lineage tracing in cancer in vivo. Annu. Rev. Cancer Biol. 7, e32888 (2023).

    Article  Google Scholar 

  18. McKenna, A. et al. Whole-organism lineage tracing by combinatorial and cumulative genome editing. Science 353, aaf7907 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Chan, M. M. et al. Molecular recording of mammalian embryogenesis. Nature 570, 77–82 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Bowling, S. et al. An engineered CRISPR-Cas9 mouse line for simultaneous readout of lineage histories and gene expression profiles in single cells. Cell 181, 1693–1694 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Quinn, J. J. et al. Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts. Science 371, eabc1944 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Simeonov, K. P. et al. Single-cell lineage tracing of metastatic cancer reveals selection of hybrid EMT states. Cancer Cell 39, 1150–1162 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Yang, D. et al. Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution. Cell 185, 1905–1923.e25 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Chen, P. J. et al. Enhanced prime editing systems by manipulating cellular determinants of editing outcomes. Cell 184, 5635–5652.e29 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lin, Q. et al. Prime genome editing in rice and wheat. Nat. Biotechnol. 38, 582–585 (2020).

    Article  CAS  PubMed  Google Scholar 

  26. Bosch, J. A., Birchak, G. & Perrimon, N. Precise genome engineering in Drosophila using prime editing. Proc. Natl Acad. Sci. Usa. 118, e2021996118 (2021).

    Article  CAS  PubMed  Google Scholar 

  27. Tong, Y., Jørgensen, T. S., Whitford, C. M., Weber, T. & Lee, S. Y. A versatile genetic engineering toolkit for E. coli based on CRISPR-prime editing. Nat. Commun. 12, 5206 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Chen, W. et al. Multiplex genomic recording of enhancer and signal transduction activity in mammalian cells. Preprint at bioRxiv https://doi.org/10.1101/2021.11.05.467434 (2021).

  29. Nelson, J. W. et al. Engineered pegRNAs improve prime editing efficiency. Nat. Biotechnol. 40, 402–410 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Ferreira da Silva, J. et al. Prime editing efficiency and fidelity are enhanced in the absence of mismatch repair. Nat. Commun. 13, 760 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Koeppel, J. et al. Prediction of prime editing insertion efficiencies using sequence features and DNA repair determinants. Nat. Biotechnol. 41, 1446–1456 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Li, M. et al. Transient inhibition of p53 enhances prime editing and cytosine base-editing efficiencies in human pluripotent stem cells. Nat. Commun. 13, 6354 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Kalhor, R. et al. Developmental barcoding of whole mouse via homing CRISPR. Science 361, eaat9804 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Loveless, T. B. et al. Molecular recording of sequential cellular events into DNA. Preprint at bioRxiv https://doi.org/10.1101/2021.11.05.467507 (2021).

  35. Petri, K. et al. CRISPR prime editing with ribonucleoprotein complexes in zebrafish and primary human cells. Nat. Biotechnol. 40, 189–193 (2022).

    Article  CAS  PubMed  Google Scholar 

  36. Clement, K. et al. CRISPResso2 provides accurate and rapid genome editing sequence analysis. Nat. Biotechnol. 37, 224–226 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Liao, H. & Choi, J. DNA Typewriter scripts. Figshare https://doi.org/10.6084/m9.figshare.22728758.v1 (2023).

  38. Doman, J. L., Sousa, A. A., Randolph, P. B., Chen, P. J. & Liu, D. R. Designing and executing prime editing experiments in mammalian cells. Nat. Protoc. 17, 2431–2468 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank R. Daza, B. Martin, H. Kim and J. Nathans for feedback on this manuscript and protocol. We thank members of Jay Shendure’s laboratory for developing the DNA Typewriter platform as well as David Liu’s laboratory for developing and improving the prime-editing technology. This work is supported by a grant from the Paul G. Allen Frontiers Group (Allen Discovery Center for Cell Lineage Tracing to J.S.) and the National Human Genome Research Institute (UM1HG011586 to J.S. and K99HG012973 to J.C.). H.L. is supported by the NSF Graduate Research Fellowship Program (DGE-2140004). J.C. was a Howard Hughes Medical Institute Fellow of the Damon Runyon Cancer Research Foundation (DRG-2403-20). J.S. is an investigator of the Howard Hughes Medical Institute.

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Contributions

This protocol is based on a paper by J.C. and J.S. H.L. and J.C. contributed equally and wrote the manuscript and prepared the figures. J.S. supervised the research and wrote parts of the manuscript. All authors edited the manuscript.

Corresponding authors

Correspondence to Junhong Choi or Jay Shendure.

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Competing interests

The University of Washington has filed a patent application partially based on this work, in which J.C. and J.S. are listed as inventors. J.S. is on the scientific advisory board, a consultant, and/or a co-founder of Prime Medicine, Cajal Neuroscience, Guardant Health, Maze Therapeutics, Camp4 Therapeutics, Phase Genomics, Adaptive Biotechnologies, Scale Biosciences, Sixth Street Capital and Pacific Biosciences. H.L. declares no competing interests.

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Nature Protocols thanks Nozomu Yachie and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Key reference using this protocol

Choi, J. et al. Nature 608, 98–107 (2022): https://doi.org/10.1038/s41586-022-04922-8

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Liao, H., Choi, J. & Shendure, J. Molecular recording using DNA Typewriter. Nat Protoc 19, 2833–2862 (2024). https://doi.org/10.1038/s41596-024-01003-0

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